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NASA NTRS2007

Physical Interpretation of the Correlation Between Multi-Angle Spectral Data and Canopy Height

Recent empirical studies have shown that multi-angle spectral data can be useful for predicting canopy height, but the physical reason for this correlation was not understood. We follow the concept of canopy spectral invariants, specifically escape probability, to gain insight into the observed correlation. Airborne Multi-Angle Imaging Spectrometer (AirMISR) and airborne Laser Vegetation Imaging Sensor (LVIS) data acquired during a NASA Terrestrial Ecology Program aircraft campaign underlie our analysis. Two multivariate linear regression models were developed to estimate LVIS height measures from 28 AirMISR multi-angle spectral reflectances and from the spectrally invariant escape probability at 7 AirMISR view angles. Both models achieved nearly the same accuracy, suggesting that canopy spectral invariant theory can explain the observed correlation. We hypothesize that the escape probability is sensitive to the aspect ratio (crown diameter to crown height). The multi-angle spectral data alone therefore may not provide enough information to retrieve canopy height globally

Schull, M. A.↗

NASA NTRS2010

Detection of Multi-Layer and Vertically-Extended Clouds Using A-Train Sensors

The detection of mUltiple cloud layers using satellite observations is important for retrieval algorithms as well as climate applications. In this paper, we describe a relatively simple algorithm to detect multiple cloud layers and distinguish them from vertically-extended clouds. The algorithm can be applied to coincident passive sensors that derive both cloud-top pressure from the thermal infrared observations and an estimate of solar photon pathlength from UV, visible, or near-IR measurements. Here, we use data from the A-train afternoon constellation of satellites: cloud-top pressure, cloud optical thickness, the multi-layer flag from the Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) and the optical centroid cloud pressure from the Aura Ozone Monitoring Instrument (OMI). For the first time, we use data from the CloudSat radar to evaluate the results of a multi-layer cloud detection scheme. The cloud classification algorithms applied with different passive sensor configurations compare well with each other as well as with data from CloudSat. We compute monthly mean fractions of pixels containing multi-layer and vertically-extended clouds for January and July 2007 at the OMI spatial resolution (l2kmx24km at nadir) and at the 5kmx5km MODIS resolution used for infrared cloud retrievals. There are seasonal variations in the spatial distribution of the different cloud types. The fraction of cloudy pixels containing distinct multi-layer cloud is a strong function of the pixel size. Globally averaged, these fractions are approximately 20% and 10% for OMI and MODIS, respectively. These fractions may be significantly higher or lower depending upon location. There is a much smaller resolution dependence for fractions of pixels containing vertically-extended clouds (approx.20% for OMI and slightly less for MODIS globally), suggesting larger spatial scales for these clouds. We also find higher fractions of vertically-extended clouds over land as compared with ocean, particularly in the tropics and summer hemisphere.

Joiner, J.↗

NASA NTRS2011

Multi-Axis Identifiability Using Single-Surface Parameter Estimation Maneuvers on the X-48B Blended Wing Body

The problem of parameter estimation on hybrid-wing-body type aircraft is complicated by the fact that many design candidates for such aircraft involve a large number of aero- dynamic control effectors that act in coplanar motion. This fact adds to the complexity already present in the parameter estimation problem for any aircraft with a closed-loop control system. Decorrelation of system inputs must be performed in order to ascertain individual surface derivatives with any sort of mathematical confidence. Non-standard control surface configurations, such as clamshell surfaces and drag-rudder modes, further complicate the modeling task. In this paper, asymmetric, single-surface maneuvers are used to excite multiple axes of aircraft motion simultaneously. Time history reconstructions of the moment coefficients computed by the solved regression models are then compared to each other in order to assess relative model accuracy. The reduced flight-test time required for inner surface parameter estimation using multi-axis methods was found to come at the cost of slightly reduced accuracy and statistical confidence for linear regression methods. Since the multi-axis maneuvers captured parameter estimates similar to both longitudinal and lateral-directional maneuvers combined, the number of test points required for the inner, aileron-like surfaces could in theory have been reduced by 50%. While trends were similar, however, individual parameters as estimated by a multi-axis model were typically different by an average absolute difference of roughly 15-20%, with decreased statistical significance, than those estimated by a single-axis model. The multi-axis model exhibited an increase in overall fit error of roughly 1-5% for the linear regression estimates with respect to the single-axis model, when applied to flight data designed for each, respectively.

Ratnayake, Nalin A.↗

NASA NTRS2014

Cost Analysis In A Multi-Mission Operations Environment

Spacecraft control centers have evolved from dedicated, single-mission or single missiontype support to multi-mission, service-oriented support for operating a variety of mission types. At the same time, available money for projects is shrinking and competition for new missions is increasing. These factors drive the need for an accurate and flexible model to support estimating service costs for new or extended missions; the cost model in turn drives the need for an accurate and efficient approach to service cost analysis. The National Aeronautics and Space Administration (NASA) Huntsville Operations Support Center (HOSC) at Marshall Space Flight Center (MSFC) provides operations services to a variety of customers around the world. HOSC customers range from launch vehicle test flights; to International Space Station (ISS) payloads; to small, short duration missions; and has included long duration flagship missions. The HOSC recently completed a detailed analysis of service costs as part of the development of a complete service cost model. The cost analysis process required the team to address a number of issues. One of the primary issues involves the difficulty of reverse engineering individual mission costs in a highly efficient multimission environment, along with a related issue of the value of detailed metrics or data to the cost model versus the cost of obtaining accurate data. Another concern is the difficulty of balancing costs between missions of different types and size and extrapolating costs to different mission types. The cost analysis also had to address issues relating to providing shared, cloud-like services in a government environment, and then assigning an uncertainty or risk factor to cost estimates that are based on current technology, but will be executed using future technology. Finally the cost analysis needed to consider how to validate the resulting cost models taking into account the non-homogeneous nature of the available cost data and the decreasing flight rate. This paper presents the issues encountered during the HOSC cost analysis process, and the associated lessons learned. These lessons can be used when planning for a new multi-mission operations center or in the transformation from a dedicated control center to multi-center operations, as an aid in defining processes that support future cost analysis and estimation. The lessons can also be used by mature serviceoriented, multi-mission control centers to streamline or refine their cost analysis process.

Newhouse, M.↗

NASA NTRS2014

Multi-shock Shield Performance at 16.5 MJ for Catalogued Debris

While orbital debris of ten centimeters or more are tracked and catalogued, the difficulty of finding and accurately accounting for forces acting on the objects near the ten centimeter threshold results in both uncertainty of their presence and location. These challenges result in difficult decisions for operators balancing potential costly operational approaches with system loss risk. In this paper, numerical simulations and an experiment using the multi‐shock shield system is described for a cylindrical projectile composed of Nylon, aluminum and void that is approximately 8 cm in diameter and 10 cm in length weighing 670 g impacting the multi‐shock shield normal to the surface with approximately 16.5 MJ of kinetic energy. The multi‐shock shield system has been optimized to facilitate the fragmentation, spread and deceleration of the projectile remnants using hydrodynamic simulations of the impact event. The characteristics and function of each of the layers of the multi‐shock system will be discussed along with considerations for deployment and improvement.

Miller, J. E.↗

NASA NTRS2014

Forward Bay Cover Separation Modeling and Testing for the Orion Multi-Purpose Crew Vehicle

Spacecraft multi‐body separation events during atmospheric descent require complex testing and analysis to validate the flight separation dynamics model and to verify no recontact. NASA Orion Multi‐Purpose Crew Vehicle (MPCV) teams examined key model parameters and risk areas to develop a robust but affordable test campaign in order to validate and verify the Forward Bay Cover (FBC) separation event for Exploration Flight Test‐1 (EFT‐1). The FBC jettison simulation model is highly complex, consisting of dozens of parameters varied simultaneously, with numerous multi‐parameter interactions (coupling and feedback) among the various model elements, and encompassing distinct near‐field, mid‐field, and far‐field regimes. The test campaign was composed of component‐level testing (for example gas‐piston thrusters and parachute mortars), ground FBC jettison tests, and FBC jettison air‐drop tests that were accomplished by a highly multi‐disciplinary team. Three ground jettison tests isolated the testing of mechanisms and structures to anchor the simulation models excluding aerodynamic effects. Subsequently, two air‐drop tests added aerodynamic and parachute parameters, and served as integrated system demonstrations, which had been preliminarily explored during the Orion Pad Abort‐1 (PA‐1) flight test in May 2010. Both ground and drop tests provided extensive data to validate analytical models and to verify the FBC jettison event for EFT‐1, but more testing is required to support human certification, for which NASA and Lockheed Martin are applying knowledge from Apollo and EFT‐1 testing and modeling to develop a robust but affordable human spacecraft capability.

Ali, Yasmin↗

NASA NTRS2018

A Novel Multi-Spacecraft Interplanetary Global Trajectory Optimization Transcription

As the frontier of space exploration continues to advance, so does the design complexity of future interplanetary missions. One avenue of this increasing complexity includes a class of designs known as "Distributed Spacecraft Missions"; missions where multiple spacecraft coordinate to perform shared objectives. Current approaches for the global trajectory optimization of these Multi-Vehicle Missions (MVMs) are prone to shortcomings including laborious iterative design, considerable human-in-the-loop effort, treatment of the multi-vehicle problem as multiple separate trajectory optimization subproblems (resulting in suboptimal solutions where the whole is less than the sum of its parts), and poor handling of coordination objectives and constraints. There are only a handful of software platforms in existence capable of fully-automated, rapid, interplanetary mission and systems global optimization including the Parallel Global Multiobjective Optimizer (PaGMO), the Gravity Assisted Low-thrust Local Optimization Program (GALLOP), and the Evolutionary Mission Trajectory Generator (EMTG). However, none of these tools is capable of performing such tasks for MVM designs. The work outlined in this paper lays the groundwork for a technique to begin addressing these shortcomings. We present a fully-automated technique which frames interplanetary MVMs as Multi-Objective, Multi-Agent Hybrid Optimal Control Problems (MOMA HOCP). First, the basic functionality of this technique is validated on the single-vehicle problem of reproducing the Cassini interplanetary cruise.

Interplanetary↗

NASA NTRS2018

A Novel Multi-Spacecraft Interplanetary Global Trajectory Optimization Transcription

As the frontier of space exploration continues to advance, so does the design complexity of future interplanetary missions. One avenue of this increasing complexity includes a class of designs known as ``Distributed Spacecraft Missions"; missions where multiple spacecraft coordinate to perform shared objectives. Current approaches for the global trajectory optimization of these Multi-Vehicle Missions (MVMs) are prone to shortcomings including laborious iterative design, considerable human-in-the-loop effort, treatment of the multi-vehicle problem as multiple separate trajectory optimization subproblems (resulting in suboptimal solutions where the whole is less than the sum of its parts), and poor handling of coordination objectives and constraints. There are only a handful of software platforms in existence capable of fully-automated, rapid, interplanetary mission and systems global optimization including the Parallel Global Multiobjective Optimizer (PaGMO), the Gravity Assisted Low-thrust Local Optimization Program (GALLOP), and the Evolutionary Mission Trajectory Generator (EMTG). However, none of these tools is capable of performing such tasks for MVM designs. The work outlined in this paper lays the groundwork for a technique to begin addressing these shortcomings. We present a fully-automated technique which frames interplanetary MVMs as Multi-Objective, Multi-Agent Hybrid Optimal Control Problems (MOMA HOCP). First, the basic functionality of this technique is validated on the single-vehicle problem of reproducing the Cassini interplanetary cruise.

Napier, Sean W.↗

NASA NTRS2019

Architectures of Kepler's Multi-Transiting Planetary Systems

More than one-third of the 4700 planet candidates found by NASA's Kepler spacecraft are associated with target stars that have more than one planet candidate, and such "multis" account for the vast majority of candidates that have been verified as true planets. The large number of multis tells us that flat multi-planet systems like our Solar System are common. Virtually all of the candidate planetary systems are stable, as tested by numerical integrations that assume a physically motivated mass-radius relationship. Statistical studies performed on these candidate systems reveal a great deal about the architecture and dynamics of planetary systems, including the typical spacing of orbits and flatness. The characteristics of several of the most interesting confirmed Kepler, K2 & TESS multi-planet systems will also be discussed.

Lissauer, Jack↗

NASA NTRS2015

Multi-Angle Polarimetry: The Once and Future King of Aerosol Remote Sensing

Although aerosols (and their interactions with clouds) are widely known to be one of the most uncertain components of the climate, they remain largely unconstrained in climate simulations. This is because global observations of all the parameters relevant to such simulations - quantity, size, shape, optical properties and chemical composition - are very difficult to simultaneously retrieve from existing remote sensing instruments. The problem can be addressed by maximizing the scene information gathered by a remote sensing instrument, by the use of (passive) multi-spectral, multi-angle and polarimetrically sensitive sensors. These observations, coupled with a radiative transfer model, can be inverted to solve for aerosol parameters. However, the choices to be made when designing an such an observing system and retrieval algorithm are complex, and a variety of approaches have been undertaken by the scientific community. I will review the various multi-spectral, multi-angle, polarimetric observation systems employed for aerosol remote sensing and their corresponding retrieval algorithms. This includes the French Polarization and Directionality of Earth Reflectance (POLDER) instrument, which has been the only such instrument successfully deployed in orbit thus far (most recently from 2004-2013), the NASA Aerosol Polarimetry Sensor (APS) on the ill-fated NASA Glory Mission (launch failure in 2011), potential or planned polarimeters on the NASA Aerosol-Cloud-Ecosystem (ACE) and Pre-Aerosol, Clouds and ocean Ecosystems (PACE) missions, and airborne prototypes from around the world.

Knobelspiesse, Kirk↗

NASA NTRSDate not supplied

Exploring Transfers Between Earth-Moon Halo Orbits via Multi-Objective Reinforcement Learning

Multi-Reward Proximal Policy Optimization, a multi-objective deep reinforcement learning algorithm, is used to examine the design space of low-thrust trajectories for a SmallSat transferring between two libration point orbits in the Earth-Moon system. Using Multi-Reward Proximal Policy Optimization, multiple policies are simultaneously and efficiently trained on three distinct trajectory design scenarios. Each policy is trained to create a unique control scheme based on the trajectory design scenario and assigned reward function: a unique combination of weights scaling competing objectives that guide the spacecraft to the target mission orbit, incentivize faster flight times, and penalize propellant mass usage. Then, the policies are evaluated on the same set of perturbed initial conditions in each scenario to generate the propellant mass usages, flight times, and state discontinuities from a reference trajectory for each control scheme. This solution space of low-thrust trajectories for a SmallSat is used to examine the multi-objective trade space for the trajectory design scenario. By autonomously constructing the solution space, insights into the required propellant mass, flight time, and transfer geometry are rapidly achieved.

Christopher J Sullivan↗

NASA NTRS2021

Estimating Terrestrial Snow Mass via Multi-sensor Assimilation of Synthetic AMSR-E Brightness Temperature Spectral Differences and Synthetic GRACE Terrestrial Water Storage Retrievals

This study explores multi-sensor data assimilation (DA) using synthetic Advanced Microwave Scanning Radiometer (AMSR-E) passive microwave brightness temperature spectral differences (∆T(B)) and synthetic Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage (TWS) retrievals to improve estimates of snow water equivalent (SWE), subsurface water storage, and TWS across snow-covered terrain. Results show that multi-sensor DA improves SWE estimates by reducing the RMSE by 14.1% relative to a model-only simulation. Multi-sensor assimilation also yields the smallest TWS RMSE (reduced by 13.0% relative to a model-only simulation). However, multi-sensor DA does not always yield complementary updates, and can sometimes lead to conflicting changes to SWE, where the assimilation of synthetic ∆T(b) generates positive SWE increments while the assimilation of synthetic TWS removes SWE, which can ultimately degrade the posterior SWE estimates. This synthetic experiment provides useful insight for future DA experiments using real-world AMSR-E/AMSR-2 ∆T(b) observations and GRACE/GRACE-FO TWS retrievals to better characterize terrestrial freshwater storage across regional scales.

Jing Wang↗

NASA NTRSDate not supplied

MULTI-OBJECTIVE REINFORCEMENT LEARNING FOR LOW-THRUST TRANSFER DESIGN BETWEEN LIBRATION POINT ORBITS

Multi-Reward Proximal Policy Optimization (MRPPO) is a multi-objective reinforcement learning algorithm used to construct low-thrust transfers between periodic orbits in multi-body systems. Previous implementations of MRPPO have relied on a predefined reference transfer to successfully train each policy. In this paper, an algorithmic modification labeled the ‘moving reference’, is introduced to autonomously construct these reference trajectories during training. With this modification, MRPPO is used to recover various low-thrust transfers between two periodic orbits in the Earth-Moon circular restricted three-body problem to solve a multi-objective optimization problem. These results are then compared with the solutions recovered via a traditional optimization formulation.

algorithm↗

NASA NTRSDate not supplied

MULTI-OBJECTIVE REINFORCEMENT LEARNING FOR LOW-THRUST TRANSFER DESIGN BETWEEN LIBRATION POINT ORBITS

Christopher J. Sullivan↗

NASA NTRSDate not supplied

Multi-Anvil Experimentation Applied to Planetary Differentiation

Planets undergo differentiation that includes segregation of metal from silicate at high temperatures and pressures ranging from deep planetary core pressures (>300 GPa for Earth)to very shallow conditions of asteroids (<100 MPa).The multi-anvil solid media apparatus accesses the middle part of this range from 3 to 30 GPa –pressure relevant to the interior of Mercury, Venus, Earth, Earth’s Moon, and Mars. Early planets are thought to have experienced high temperatures from a combination of heat sources including radioactive decay, gravitational and accretional heating, and impact processes. These heating events led to melting of mantles and cores, thus requiring an understanding of solid-liquid equilibria in metal-silicate systems. In 2006 we established a multi-anvil facility at NASA-JSC combining an 880 ton press and a Kawai/Walker type module from Rockland Research. Our high PT work has been greatly facilitated by use of the COMPRES multi-anvil assemblies (1). Our recent work has included studies of element partitioning between liquid metal and liquid silicate(e.g., 2), as well as between minerals and melts(e.g., 3), both of which have led to better constraints on the timing and conditions of planetary differentiation(e.g. 4). Several examples involving sustained efforts will be summarized below and for the presentation. The distribution of siderophile (iron-loving) elements between core and mantle is controlled by metal-silicate equilibrium across a wide range of pressures. Therefore, experimentation across this pressure range helps to calibrate elemental partitioning models that can be applied to planets, and used to predict mantle chemistry and composition during planetary differentiation. Our studies have focused on a wide range of siderophile elements (refractory Ni, Co, W, Mo; volatile P, Ga, Cu, Sn, Sb; highly siderophile Au, Pd) that have constrained partitioning, valence, and isotopic fractionation, and applied to Earth, Moon, and Mars. When molten mantles (magma oceans) cool enough to initiate crystallization, the solids precipitate at depth and in large planets this involves high pressure phases like garnet, majorite, akimotoite, and ringwoodite. As these solids precipitate they can segregate from liquid by density contrasts, thus causing elemental fractionation which can be used to decipher timing of differentiation. Mineral/melt and metal/silicate equilibria in our lab have helped to better understand high pressure fractionation of isotopic parent/daughter pairs Hf/W, Mn/Cr, Pd/Ag, Pt/Os, Re/Os, and U/Pb, and their application to Earth, Moon and Mars. There remains great potential for multi-anvil experimentation to shed light on many pressure–dependent aspects of planetary evolution such as core formation, high pressure phase equilibria, redox equilibria, and volatile evolution and storage. References1. Leinenweber, K., et al.(2012) American Mineralogist,97, 353–368. 2.Righter, K., et al.(2020) Geochem. Persp. Lett.15, 1-6.3. Righter, K., et al.(2020) Met. Planet. Sci 55, 2741-2757.4. Righter, K., et al.(2020)Earth and Planetary Science Letters,552, 116590.

pressure↗

NASA NTRSDate not supplied

MULTI-OBJECTIVE REINFORCEMENT LEARNING FOR LOW-THRUST TRANSFER DESIGN BETWEEN LIBRATION POINT ORBITS

Christopher John Sullivan↗

NASA NTRS2021

Exploring Transfers Between Earth-Moon Halo Orbits via Multi-Objective Reinforcement Learning

Multi-Reward Proximal Policy Optimization, a multi-objective deep reinforcement learning algorithm, is used to examine the design space of low-thrust trajectories for a SmallSat transferring between two libration point orbits in the Earth- Moon system. Using Multi-Reward Proximal Policy Optimiza- tion, multiple policies are simultaneously and efficiently trained on three distinct trajectory design scenarios. Each policy is trained to create a unique control scheme based on the trajectory design scenario and assigned reward function: a unique combination of weights scaling competing objectives that guide the spacecraft to the target mission orbit, incentivize faster flight times, and penalize propellant mass usage. Then, the policies are evaluated on the same set of perturbed initial conditions in each scenario to generate the propellant mass usages, flight times, and state discontinuities from a reference trajectory for each control scheme. This solution space of low-thrust trajectories for a SmallSat is used to examine the multi-objective trade space for the trajectory design scenario. By autonomously constructing the solution space, insights into the required propellant mass, flight time, and transfer geometry are rapidly achieved.

Mashiku, Alinda K.↗

NASA NTRS2021

Extending the Licklider Transmission Protocol to Multi-Band Links

Most deep space missions return data to Earth using links operating at a single frequency band. Indeed, their data requirements are low enough that bandwidth regulations do not constrain the system. In contrast, spacecraft such as Kepler or Europa Clipper are transitioning to a new operational paradigm where engineering and science data are transmitted through simultaneous links operating at different frequency bands (henceforth termed multi-band links). This ensures, for instance, that critical data is correctly received using a well characterized X-band link, while science data at a much larger data rate can be returned efficiently (both in terms of bandwidth and energy) through a Ka-band link.Having a spacecraft establish two simultaneous links with a ground station opens a large span of potential improvements for space communications and mission operations. In this paper, we consider the problem of running a Licklider Transmission Protocol (LTP) session over a multi-band link. LTP is an implementation of a selective Automatic Repeat reQuest (ARQ) protocol, i.e. it ensures correct delivery of data over an error prone link with potentially long propagation delays. To maximize its efficiency in deep space environments, LTP operates in deferred-ACK mode and is typically included as one of the core protocols in the Delay Tolerant Networking (DTN) suite.The contributions of this paper are as follows: First, we propose an extension to LTP for multi-band links (denoted MBLTP) and sketch how it can be implemented without modifying the current definition of LTP data units. Next, we develop bounds on the performance of MBLTP when transmitting a single data file over a multi-band link. Three metrics are considered, file expected delivery time, total energy spent and bundle jitter. The results of the analytic model are first benchmarked against simulations to ensure validity, and then compared against the performance of both traditional LTP and Parallel LTP (PLTP).We demonstrate that MBLTP can significantly reduce the latency and jitter with which data products are delivered to destination over a deep space link compared to LTP at moderate energy cost. Similarly, we also demonstrate that MBLTP outperforms PLTP in all considered metrics.

Sanchez Net, Marc↗