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NASA NTRS2014

The Status of Spacecraft Bus and Platform Technology Development Under the NASA ISPT Program

The In-Space Propulsion Technology (ISPT) program is developing spacecraft bus and platform technologies that will enable or enhance NASA robotic science missions. The ISPT program is currently developing technology in three areas that include Propulsion System Technologies, Entry Vehicle Technologies, and Systems Mission Analysis. ISPTs propulsion technologies include: 1) NASAs Evolutionary Xenon Thruster (NEXT) ion propulsion system, a 0.6-7 kW throttle-able gridded ion system; 2) a Hall-effect electric propulsion (HEP) system for sample return and low cost missions; 3) the Advanced Xenon Flow Control System (AXFS); ultra-lightweight propellant tank technologies (ULTT); and propulsion technologies for a Mars Ascent Vehicle (MAV). The AXFS and ULTT are two component technologies being developed with nearer-term flight infusion in mind, whereas NEXT and the HEP are being developed as EP systems. ISPTs entry vehicle technologies are: 1) Aerocapture technology development with investments in a family of thermal protection system (TPS) materials and structures; guidance, navigation, and control (GNC) models of blunt-body rigid aeroshells; and aerothermal effect models; and 2) Multi-mission technologies for Earth Entry Vehicles (MMEEV) for sample return missions. The Systems Mission Analysis area is focused on developing tools and assessing the application of propulsion, entry vehicle, and spacecraft bus technologies to a wide variety of mission concepts. Several of the ISPT technologies are related to sample return missions and other spacecraft bus technology needs like: MAV propulsion, MMEEV, and electric propulsion. These technologies, as well as Aerocapture, are more vehicle and mission-focused, and present a different set of technology development challenges. These in-space propulsion technologies are applicable, and potentially enabling for future NASA Discovery, New Frontiers, Flagship and sample return missions currently under consideration. This paper provides a brief overview of the ISPT program, describing the development status and technology infusion readiness.

electric propulsion↗
NASA NTRS2014

NASA Workshop on Hybrid (Mixed-Actuator) Spacecraft Attitude Control

At the request of the Science Mission Directorate Chief Engineer, the NASA Technical Fellow for Guidance, Navigation & Control assembled and facilitated a workshop on Spacecraft Hybrid Attitude Control. This multi-Center, academic, and industry workshop, sponsored by the NASA Engineering and Safety Center (NESC), was held in April 2013 to unite nationwide experts to present and discuss the various innovative solutions, techniques, and lessons learned regarding the development and implementation of the various hybrid attitude control system solutions investigated or implemented. This report attempts to document these key lessons learned with the 16 findings and 9 NESC recommendations.

Dennehy, Cornelius J.↗
NASA NTRS2015

Interfacing and Verifying ALHAT Safe Precision Landing Systems with the Morpheus Vehicle

The NASA Autonomous precision Landing and Hazard Avoidance Technology (ALHAT) project developed a suite of prototype sensors to enable autonomous and safe precision landing of robotic or crewed vehicles under any terrain lighting conditions. Development of the ALHAT sensor suite was a cross-NASA effort, culminating in integration and testing on-board a variety of terrestrial vehicles toward infusion into future spaceflight applications. Terrestrial tests were conducted on specialized test gantries, moving trucks, helicopter flights, and a flight test onboard the NASA Morpheus free-flying, rocket-propulsive flight-test vehicle. To accomplish these tests, a tedious integration process was developed and followed, which included both command and telemetry interfacing, as well as sensor alignment and calibration verification to ensure valid test data to analyze ALHAT and Guidance, Navigation and Control (GNC) performance. This was especially true for the flight test campaign of ALHAT onboard Morpheus. For interfacing of ALHAT sensors to the Morpheus flight system, an adaptable command and telemetry architecture was developed to allow for the evolution of per-sensor Interface Control Design/Documents (ICDs). Additionally, individual-sensor and on-vehicle verification testing was developed to ensure functional operation of the ALHAT sensors onboard the vehicle, as well as precision-measurement validity for each ALHAT sensor when integrated within the Morpheus GNC system. This paper provides some insight into the interface development and the integrated-systems verification that were a part of the build-up toward success of the ALHAT and Morpheus flight test campaigns in 2014. These campaigns provided valuable performance data that is refining the path toward spaceflight infusion of the ALHAT sensor suite.

Carson, John M., III↗
NASA NTRS2014

Evolution of MPCV Service Module Propulsion and GNC Interface Requirements

The Orion Multi-Purpose Crew Vehicle Service Module Propulsion Subsystem provides propulsion for the integrated Crew and Service Module. Updates in the exploration architecture between Constellation and MPCV as well as NASA's partnership with the European Space Agency have resulted in design changes to the SM Propulsion Subsystem and updates to the Propulsion interface requirements with Guidance Navigation and Control. This paper focuses on the Propulsion and GNC interface requirement updates between the Constellation Service Module and the European Service Module and how the requirement updates were driven or supported by architecture updates and the desired use of hardware with heritage to United States and European spacecraft for the Exploration Missions, EM-1 and EM-2.

spacecraft propulsion↗
NASA NTRS2013

SMAP Instrument Mechanical System Engineering

The Soil Moisture Active Passive (SMAP) mission, scheduled for launch by the end of 2014, is being developed to measure the soil moisture and soil freeze/thaw state on a global scale over a three-year period. The accuracy, resolution, and global coverage of SMAP measurements are invaluable across many science and applications disciplines including hydrology, climate, carbon cycle, and the meteorological, environment, and ecology applications communities. The SMAP observatory is composed of a despun bus and a spinning instrument platform that includes both a deployable 6 meter aperture low structural frequency Astromesh reflector and a spin control system. The instrument section has engendered challenging mechanical system issues associated with the antenna deployment, flexible antenna pointing in the context of a multitude of disturbances, spun section mass properties, spin control system development, and overall integration with the flight system on both mechanical and control system levels. Moreover, the multitude of organizations involved, including two major vendors providing the spin subsystem and reflector boom assembly plus the flight system mechanical and guidance, navigation, and control teams, has led to several unique system engineering challenges. Capturing the key physics associated with the function of the flight system has been challenging due to the many different domains that are applicable. Key interfaces and operational concepts have led to complex negotiations because of the large number of organizations that integrate with the instrument mechanical system. Additionally, the verification and validation concerns associated with the mechanical system have had required far-reaching involvement from both the flight system and other subsystems. The SMAP instrument mechanical systems engineering issues and their solutions are described in this paper.

mechanical systems.↗
NASA NTRS2013

Mars Science Laboratory Entry Descent and Landing Simulation Using DSENDS

The most recent planetary science mission to Mars is Mars Science Laboratory (MSL) with the Curiosity rover, launched November 26, 2011 and landed at Gale Crater on August 6, 2012. This spacecraft was the first use at Mars of a complete closed-loop Guidance Navigation and Control (GN&C) system, including guided entry with a lifting body that greatly reduces dispersions during the Entry, Descent and Landing (EDL) phase to achieve a 25 km x 20 km landing error relative to the selected Gale Crater landing target. In order to confirm meeting the above landing criteria, high-fidelity simulation of the EDL phase is required. The tool used for 6DOF EDL trajectory verification analysis is Dynamics Simulator for Entry, Descent and Surface landing (DSENDS), which is a high-fidelity simulation tool from JPLs Dynamics and Real-Time Simulation Laboratory for the development, test and operations of aero-flight vehicles. DSENDS inherent capability is augmented for MSL with project-specific models of atmosphere, aerodynamics, sensors and thrusters along with GN&C flight software to enable high-fidelity trajectory simulation. This paper will present the model integration and independent verification experience of the JPL EDL trajectory analysis team.

Mars↗
NASA NTRS2012

Applications of Nanosats to Planetary Exploration

NanoSat technology has opened Earth orbit to extremely low-cost science missions through a common interface that provides greater launch accessibility. A natural question is the role that CubeSat-derived NanoSats could play to increase the science return of deep space missions. We do not consider single instrument nano-satellites as likely to complete entire Discovery-class missions alone, but believe that nano-satellites could augment larger missions to significantly increase science return. The key advantages offered by these mini-spacecrafts over previous planetary probes is the common availability of advanced subsystems that open the door to a large variety of science experiments, including new guidance, navigation and control capabilities. In this paper, multiple NanoSat science applications are suggested that could take advantage of these features. We also address the significant challenges and questions that remain as obstacles to the use of nano-satellites in deep space missions. Finally, we provide some thoughts on a development roadmap toward interplanetary usage of NanoSpacecraft.

Klesh, Andrew T.↗
NASA NTRS2011

Enabling the Capture and Sharing of NASA Technical Expertise Through Communities of Practice

Historically, engineers at the National Aeronautics and Space Administration (NASA) had few opportunities or incentives to share their technical expertise across the Agency. Its center- and project- focused culture often meant that knowledge never left organizational and geographic boundaries. With increasingly complex missions, the closeout of the Shuttle Program, and a new generation entering the workforce, developing a knowledge sharing culture became critical. To address this need, the Office of the Chief Engineer established communities of practice on the NASA Engineering Network. These communities were strategically aligned with NASA's core competencies in such disciplines as avionics, flight mechanics, life support, propulsion, structures, loads and dynamics, human factors, and guidance, navigation, and control. This paper describes the process used to identify and develop communities, from establishing simple websites that compiled discipline-specific resources to fostering a knowledge-sharing environment through collaborative and interactive technologies. It includes qualitative evidence of improved availability and transfer of knowledge. It focuses on pivotal capabilities that increased knowledge exchange such as a custom-made Ask An Expert system, community contact lists, publication of key resources, and submission forms that allowed any user to propose content for the sites. It discusses the peer relationships that developed through the communities and the leadership and infrastructure that made them possible.

Topousis, Daria E.↗
NASA NTRS2013

Dynamics and Control of a Disordered System in Space

In this paper, we present some ideas regarding the modeling, dynamics and control aspects of granular spacecraft. Granular spacecraft are complex multibody systems composed of a spatially disordered distribution of a large number of elements, for instance a cloud of N grains in orbit, with N greater than 10(exp 3). These grains can be large (Cubesat-size) or small (mm-size), and can be active, i.e., a fully equipped vehicle capable sensing their own position and attitude, and enabled with propulsion means, or entirely passive. The ultimate objective would be to study the behavior of the single grains and of large ensembles of grains in orbit and to identify ways to guide and control the shape of a cloud composed of these grains so that it can perform a useful function in space, for instance, as an element of an optical imaging system for astrophysical applications. This concept, in which the aperture does not need to be continuous and monolithic, would increase the aperture size several times compared to large NASA observatories such as ATLAST, allowing for a true Terrestrial Planet Imager that would be able to resolve exo-planet details and do meaningful spectroscopy on distant world. In the paper, we address the modeling and autonomous operation of a distributed assembly (the cloud) of large numbers of highly miniaturized space-borne elements (the grains). A multi-scale, multi-physics model is proposed of the dynamics of the cloud in orbit, as well as a control law for cloud shape maintenance, and preliminary simulation studies yield an estimate of the computational effort, indicating a scale factor of approximately N(exp 1.4) as a function of the number of grains. A granular spacecraft can be defined as a collection of a large number of space-borne elements (in the 1000s) designed and controlled such that a desirable collective behavior emerges, either from the interactions among neighboring grains, and/or between the grains and the environment. In this paper, each grain is considered to be a highly miniaturized spacecraft which has limited size and mass, hence it has limited actuation, limited propulsive capability, limited power, limited sensing, limited communication, limited computational resources, limited range of motion, limited lifetime, and may be expendable. The modeling and dynamics of clouds of vehicles is more challenging than with conventional vehicles because we are faced with a probabilistic vehicle composed of a large number of physically disconnected vehicles. First, different scales of motion occur simultaneously in a cloud: translations and rotations of the cloud as a whole (macro-dynamics), relative rotation and translation of one cloud member with respect to another (meso-dynamics), and individual cloud member dynamics (micro-dynamics). Second, the control design needs to be tolerant of the system complexity, of the system architecture (centralized vs. decentralized large scale system control) as well as robust to un-modeled dynamics and noise sources. Figure 1, top left, shows the kinematic parameters of a 1000 element cloud in orbit. The motion of the system is described with respect to a local vertical-local horizontal (LV-LH) orbiting reference frame (x,y,z)=F(sub ORF) of origin O(sub ORF) which rotates with mean motion omega and orbital semi-major axis R(sub 0). The orbital geometry at the initial time is defined in terms of its six orbital elements, and the orbital dynamics equation for point O(sub ORF) is propagated forward in time under the influence of the gravitational field of the primary and other external perturbations, described below. The origin of this frame coincides with the initial position of the center of mass of the system, and the coordinate axes are z along the local vertical, x toward the flight direction, and y in the orbit normal direction. The assumptions we used to model the dynamics are as follows: 1) The inertial frame is fixed at Earth's center. 2) The orbiting Frame ORF follows Keplerian orbit. 3) the cloud system dynamics is referred to ORF. 4) the attitude of each grain uses the principal body frame as body fixed frame. 5) the atmosphere is assumed to be rigidly rotating with the Earth. Regarding the grains forming the cloud: 1) each grain is modeled as a rigid body; 2) a simple attitude estimator provides attitude estimates, 3) a simple guidance logic commands the position and attitude of each grain, 4) a simple local feedback controller based on PD control of local states is used to stabilize the attitude of the vehicle. Regarding the cloud: 1) the cloud as a whole is modeled as an equivalent rigid body in orbit, and 2) an associated graph establishes agent connectivity and enables coupling between modes of motion at the micro and macro scales; 3) a simple guidance and estimation logic is modeled to estimate and command the attitude of this equivalent rigid body; 4) a cloud shape maintenance controller is based on the dynamics of a stable virtual truss in the orbiting frame. Regarding the environmental perturbations acting on the cloud: 1) a non-spherical gravity field including JO (Earth's spherical field) zonal component, J2 (Earth's oblateness) and J3 zonal components is implemented; 2) atmospheric drag is modeled with an exponential model; 3) solar pressure is modeled assuming the Sun is inertially fixed; and 4) the Earth's magnetic field is model using an equivalent dipole model. The equations of motion are written in a referential system with respect to the origin of the orbiting frame and the state is propagated forward in time using an incremental predictor-corrector scheme. A representative cloud with varying number of grains is simulated to identify the limitations in computation time as the number of grains grows. We derive a control law to track a desired surface in the ORF (equivalently to maintain a reference cloud shape) by defining an error from a desired surface shape, and designing a control law that is exponentially stable and reduces the tracking error to zero. Figure 1 (top right) shows a comparison of various requirements for simulation of single spacecraft vs. granular spacecraft, indicating the high degree of complexity that needs to be taken into consideration. The ORF components of control force required by one of the grains is, for this particular case, in the micro-Newton range. However, no attempt has been made yet to reconfigure (or re-orient) the cloud configuration internally, for which forces in the milli-Newton level are expected, depending on the time required to do the reconfiguration. Figure 1, bottom, shows the computation time as a function of the number of grains, indicating an order N(exp 1.43) scaling on a 8 Gb, 1067 MHz RAM MacOSX computer with a 3.06 GHz Intel Core 2 Duo processor. With this metric, the same simulation for a system of N=1000 grains would take 5.4 hours, and 146 hours (i.e., 6 days) for a system with N=10,000 grains. Therefore, efficient ways to simulate this complex system, where not only the time scales of natural system dynamics, but also the sampling times of the Guidance, Navigation, and Control are included, remain to be explored. Additional details on the cloud modeling, dynamics, and control will be described in the paper.

simulation↗
NASA NTRS2013

Mars Science Laboratory Entry Descent and Landing Simulation Using DSENDS

The most recent planetary science mission to Mars was Mars Science Laboratory (MSL) with the Curiosity rover, launched November 26, 2011 and landed at Gale Crater on August 6, 2012. This spacecraft was the first use at Mars of a complete closed-loop Guidance Navigation and Control (GN&C) system, including guided entry with a lifting body that greatly reduces dispersions during the Entry, Descent and Landing (EDL) phase to achieve a 25 km X 20 km landing error relative to the selected Gale Crater landing target. In order to confirm meeting the above landing criteria, high-fidelity simulation of the EDL phase is required. The tool used for 6DOF EDL trajectory verification analysis is Dynamics Simulator for Entry, Descent and Surface landing (DSENDS), which is a high-fidelity simulation tool from JPLs Dynamics and Real-Time Simulation Laboratory for the development, test and operations of aero-flight vehicles. DSENDS inherent capability is augmented for MSL with project-specific models of atmosphere, aerodynamics, sensors and thrusters along with GN&C flight software to enable high-fidelity trajectory simulation. This paper will present the model integration and independent verification experience of the JPL EDL trajectory analysis team.

Burkhart, P. Daniel↗
NASA NTRS2012

Nano-Satellite Secondary Spacecraft on Deep Space Missions

NanoSat technology has opened Earth orbit to extremely low-cost science missions through a common interface that provides greater launch accessibility. They have also been used on interplanetary missions, but these missions have used one-off components and architectures so that the return on investment has been limited. A natural question is the role that CubeSat-derived NanoSats could play to increase the science return of deep space missions. We do not consider single instrument nano-satellites as likely to complete entire Discovery-class missions alone,but believe that nano-satellites could augment larger missions to significantly increase science return. The key advantages offered by these mini-spacecrafts over previous planetary probes is the common availability of advanced subsystems that open the door to a large variety of science experiments, including new guidance, navigation and control capabilities. In this paper, multiple NanoSat science applications are investigated, primarily for high risk/high return science areas. We also address the significant challenges and questions that remain as obstacles to the use of nano-satellites in deep space missions. Finally, we provide some thoughts on a development roadmap toward interplanetary usage of NanoSpacecraft.

Klesh, Andrew T.↗
NASA NTRS2010

Enceladus Plume Density Modeling and Reconstruction for Cassini Attitude Control System

In 2005, Cassini detected jets composed mostly of water, spouting from a set of nearly parallel rifts in the crust of Enceladus, an icy moon of Saturn. During an Enceladus flyby, either reaction wheels or attitude control thrusters on the Cassini spacecraft are used to overcome the external torque imparted on Cassini due to Enceladus plume or jets, as well as to slew the spacecraft in order to meet the pointing needs of the on-board science instruments. If the estimated imparted torque is larger than it can be controlled by the reaction wheel control system, thrusters are used to control the spacecraft. Having an engineering model that can predict and simulate the external torque imparted on Cassini spacecraft due to the plume density during all projected low-altitude Enceladus flybys is important. Equally important is being able to reconstruct the plume density after each flyby in order to calibrate the model. This paper describes an engineering model of the Enceladus plume density, as a function of the flyby altitude, developed for the Cassini Attitude and Articulation Control Subsystem, and novel methodologies that use guidance, navigation, and control data to estimate the external torque imparted on the spacecraft due to the Enceladus plume and jets. The plume density is determined accordingly. The methodologies described have already been used to reconstruct the plume density for three low-altitude Enceladus flybys of Cassini in 2008 and will continue to be used on all remaining low-altitude Enceladus flybys in Cassini's extended missions.

Sarani, Siamak↗
NASA NTRS2010

Preliminary Characterization of the Altair Lunar Lander Slosh Dynamics and Some Implications for the Thrust Vector Control Design

This paper describes a conceptual design of the Thrust Vector Control (TVC) system and preliminary modeling of propellant slosh, for the Altair Lunar Lander. Altair is a vehicle element of the NASA Constellation Program aimed at returning humans to the moon. Guidance, Navigation, and Control (GN&C) is the measurement and control of spacecraft position, velocity, and attitude in support of mission objectives. One key GN&C function is the commanding of effectors that control attitude and impart delta V on the vehicle, utilizing both reaction control system (RCS) thrusters and throttling and TVC gimbaling of the vehicle main engine. Both the Altair descent and ascent modules carry fuel tanks. During thrusting maneuvers, the sloshing of liquid fuels in partially filled tanks can interact with the controlled system in such a way as to cause the overall system to be unstable. These fuel tanks must be properly placed, relative to the spacecraft's c.m., to avoid any unstable interactions. Following this will be a discussion of propellant slosh modeling work performed for the present vehicle configuration, including slosh frequency and participatory fluid mass predictions. Knowing the range of slosh mode frequencies over mission phases, the TVC bandwidth must be carefully selected so as not to excite the slosh modes at those frequencies. The likely need to increase the damping factor of slosh modes via baffles will also be discussed. To conclude, a discussion of operations procedures aimed at minimizing TVC-slosh interactions will be given.

Lee, Allan Y.↗
NASA NTRS2014

LunarCubes: Application of the Cubesat Paradigm to Lunar Missions

We have evaluated the application of the CubeSat Paradigm for deep space exploration, often referred to as LunarCube. Over the course of this year, we conducted systems definition and design activities, with focus on enhanced guidance, navigation, and control as well as propulsion requirements for cislunar space operation, thermal requirements and communication as dominant drivers for long duration operation on the lunar surface. The end result is costeffective, generic design(s) for a cross-section of future high priority space or surface payloads for planetary, heliophysics, and astrophysics disciplines, the requirements for which are described.

Lunar↗
NASA NTRS2015

Understanding International GNC Hardware Trends

An industry-wide survey of guidance, navigation and control (GNC) sensors, namely star trackers, gyros, and sun sensors was undertaken in 2014, in which size, mass, power, and various performance metrics were recorded for each category. A multidimensional analysis was performed, looking at the spectrum of available sensors, with the intent of identifying gaps in the available capability range. Mission types that are not currently well served by the available components were discussed, as well as some missions that would be enabled by filling gaps in the component space. This paper continues that study, with a focus on reaction wheels and magnetometers, as well as with updates to the listings of star trackers, gyros, and sun sensors. Also discussed are a framework for making the database available to the community at large, and the continued maintenance of this database and the analysis of its contents.

Greenbaum, Adam↗
NASA NTRS2015

A Vehicle Management End-to-End Testing and Analysis Platform for Validation of Mission and Fault Management Algorithms to Reduce Risk for NASAs Space Launch System

The engineering development of the National Aeronautics and Space Administration's (NASA) new Space Launch System (SLS) requires cross discipline teams with extensive knowledge of launch vehicle subsystems, information theory, and autonomous algorithms dealing with all operations from pre-launch through on orbit operations. The nominal and off-nominal characteristics of SLS's elements and subsystems must be understood and matched with the autonomous algorithm monitoring and mitigation capabilities for accurate control and response to abnormal conditions throughout all vehicle mission flight phases, including precipitating safing actions and crew aborts. This presents a large and complex systems engineering challenge, which is being addressed in part by focusing on the specific subsystems involved in the handling of off-nominal mission and fault tolerance with response management. Using traditional model-based system and software engineering design principles from the Unified Modeling Language (UML) and Systems Modeling Language (SysML), the Mission and Fault Management (M&FM) algorithms for the vehicle are crafted and vetted in Integrated Development Teams (IDTs) composed of multiple development disciplines such as Systems Engineering (SE), Flight Software (FSW), Safety and Mission Assurance (S&MA) and the major subsystems and vehicle elements such as Main Propulsion Systems (MPS), boosters, avionics, Guidance, Navigation, and Control (GNC), Thrust Vector Control (TVC), and liquid engines. These model-based algorithms and their development lifecycle from inception through FSW certification are an important focus of SLS's development effort to further ensure reliable detection and response to off-nominal vehicle states during all phases of vehicle operation from pre-launch through end of flight. To test and validate these M&FM algorithms a dedicated test-bed was developed for full Vehicle Management End-to-End Testing (VMET). For addressing fault management (FM) early in the development lifecycle for the SLS program, NASA formed the M&FM team as part of the Integrated Systems Health Management and Automation Branch under the Spacecraft Vehicle Systems Department at the Marshall Space Flight Center (MSFC). To support the development of the FM algorithms, the VMET developed by the M&FM team provides the ability to integrate the algorithms, perform test cases, and integrate vendor-supplied physics-based launch vehicle (LV) subsystem models. Additionally, the team has developed processes for implementing and validating the M&FM algorithms for concept validation and risk reduction. The flexibility of the VMET capabilities enables thorough testing of the M&FM algorithms by providing configurable suites of both nominal and off-nominal test cases to validate the developed algorithms utilizing actual subsystem models such as MPS, GNC, and others. One of the principal functions of VMET is to validate the M&FM algorithms and substantiate them with performance baselines for each of the target vehicle subsystems in an independent platform exterior to the flight software test and validation processes. In any software development process there is inherent risk in the interpretation and implementation of concepts from requirements and test cases into flight software compounded with potential human errors throughout the development and regression testing lifecycle. Risk reduction is addressed by the M&FM group but in particular by the Analysis Team working with other organizations such as S&MA, Structures and Environments, GNC, Orion, Crew Office, Flight Operations, and Ground Operations by assessing performance of the M&FM algorithms in terms of their ability to reduce Loss of Mission (LOM) and Loss of Crew (LOC) probabilities. In addition, through state machine and diagnostic modeling, analysis efforts investigate a broader suite of failure effects and associated detection and responses to be tested in VMET to ensure reliable failure detection, and confirm responses do not create additional risks or cause undesired states through interactive dynamic effects with other algorithms and systems. VMET further contributes to risk reduction by prototyping and exercising the M&FM algorithms early in their implementation and without any inherent hindrances such as meeting FSW processor scheduling constraints due to their target platform - the ARINC 6535-partitioned Operating System, resource limitations, and other factors related to integration with other subsystems not directly involved with M&FM such as telemetry packing and processing. The baseline plan for use of VMET encompasses testing the original M&FM algorithms coded in the same C++ language and state machine architectural concepts as that used by FSW. This enables the development of performance standards and test cases to characterize the M&FM algorithms and sets a benchmark from which to measure their effectiveness and performance in the exterior FSW development and test processes. This paper is outlined in a systematic fashion analogous to a lifecycle process flow for engineering development of algorithms into software and testing. Section I describes the NASA SLS M&FM context, presenting the current infrastructure, leading principles, methods, and participants. Section II defines the testing philosophy of the M&FM algorithms as related to VMET followed by section III, which presents the modeling methods of the algorithms to be tested and validated in VMET. Its details are then further presented in section IV followed by Section V presenting integration, test status, and state analysis. Finally, section VI addresses the summary and forward directions followed by the appendices presenting relevant information on terminology and documentation.

Trevino, Luis↗
NASA NTRS2015

Non-Linear Slosh Damping Model Development and Validation

Propellant tank slosh dynamics are typically represented by a mechanical model of spring mass damper. This mechanical model is then included in the equation of motion of the entire vehicle for Guidance, Navigation and Control (GN&C) analysis. For a partially-filled smooth wall propellant tank, the critical damping based on classical empirical correlation is as low as 0.05%. Due to this low value of damping, propellant slosh is potential sources of disturbance critical to the stability of launch and space vehicles. It is postulated that the commonly quoted slosh damping is valid only under the linear regime where the slosh amplitude is small. With the increase of slosh amplitude, the critical damping value should also increase. If this nonlinearity can be verified and validated, the slosh stability margin can be significantly improved, and the level of conservatism maintained in the GN&C analysis can be lessened. The purpose of this study is to explore and to quantify the dependence of slosh damping with slosh amplitude. Accurately predicting the extremely low damping value of a smooth wall tank is very challenging for any Computational Fluid Dynamics (CFD) tool. One must resolve thin boundary layers near the wall and limit numerical damping to minimum. This computational study demonstrates that with proper grid resolution, CFD can indeed accurately predict the low damping physics from smooth walls under the linear regime. Comparisons of extracted damping values with experimental data for different tank sizes show very good agreements. Numerical simulations confirm that slosh damping is indeed a function of slosh amplitude. When slosh amplitude is low, the damping ratio is essentially constant, which is consistent with the empirical correlation. Once the amplitude reaches a critical value, the damping ratio becomes a linearly increasing function of the slosh amplitude. A follow-on experiment validated the developed nonlinear damping relationship. This discovery can lead to significant savings by reducing the number and size of slosh baffles in liquid propellant tanks.

Yang, H. Q.↗