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At least 1,441 records · Page 80
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Observations of Aerosol-Radiation-Cloud Interactions in the South-East Atlantic: First Results from the ORACLES Deployments in 2016 and 2017

Southern Africa produces almost a third of the Earths biomass burning (BB) aerosol particles. Particles lofted into the mid-troposphere are transported westward over the South-East (SE) Atlantic, home to one of the three permanent subtropical stratocumulus (Sc) cloud decks in the world. The SE Atlantic stratocumulus deck interacts with the dense layers of BB aerosols that initially overlay the cloud deck, but later subside and often mix into the clouds. These interactions include adjustments to aerosol-induced solar heating and microphysical effects, and their global representation in climate models remains one of the largest uncertainties in estimates of future climate. Hence, new observations over the SE Atlantic have significant implications for regional and global climate change predictions.The low-level clouds in the SE Atlantic have limited vertical extent and therefore present favorable conditions for their exploration with remote sensing. On the other hand, the normal coexistence of BB aerosols and Sc clouds in the same scene also presents significant challenges to conventional remote sensing techniques. We describe first results from NASAs airborne ORACLES (ObseRvations of Aerosols Above Clouds and Their IntEractionS) deployments in September 2016 and August 2017. We emphasize the unique role of polarimetric observations by two instruments, the Research Scanning Polarimeter (RSP) and the Airborne Multi-angle SpectroPolarimeter Imager (AirMSPI), and describe how these instruments help address specific ORACLES science objectives. Initial assessments of polarimetric observation accuracy for key cloud and aerosol properties will be presented, in as far as the preliminary nature of measurements permits.

Redemann, Jens↗
NASA NTRS2017

NASA's Space Launch System: SmallSat Deployment to Deep Space

Leveraging the significant capability it offers for human exploration and flagship science missions, NASA's Space Launch System (SLS) also provides a unique opportunity for lower-cost deep-space science in the form of small-satellite secondary payloads. Current plans call for such opportunities to begin with the rocket's first flight; a launch of the vehicle's Block 1 configuration, capable of delivering 70 metric tons (t) to Low Earth Orbit (LEO), which will send the Orion crew vehicle around the moon and return it to Earth. On that flight, SLS will also deploy 13 CubeSat-class payloads to deep-space destinations. These secondary payloads will include not only NASA research, but also spacecraft from industry and international partners and academia. The payloads also represent a variety of disciplines including, but not limited to, studies of the moon, Earth, sun, and asteroids. While the SLS Program is making significant progress toward that first launch, preparations are already under way for the second, which will see the booster evolve to its more-capable Block 1B configuration, able to deliver 105t to LEO. That configuration will have the capability to carry large payloads co-manifested with the Orion spacecraft, or to utilize an 8.4-meter (m) fairing to carry payloads several times larger than are currently possible. The Block 1B vehicle will be the workhorse of the Proving Ground phase of NASA's deep-space exploration plans, developing and testing the systems and capabilities necessary for human missions into deep space and ultimately to Mars. Ultimately, the vehicle will evolve to its full Block 2 configuration, with a LEO capability of 130 metric tons. Both the Block 1B and Block 2 versions of the vehicle will be able to carry larger secondary payloads than the Block 1 configuration, creating even more opportunities for affordable scientific exploration of deep space. This paper will outline the progress being made toward flying smallsats on the first flight of SLS, and discuss future opportunities for smallsats on subsequent flights.

Robinson, Kimberly F.↗
NASA NTRS2017

NASA's Space Launch System: SmallSat Deployment to Deep Space

Leveraging the significant capability it offers for human exploration and flagship science missions, NASA's Space Launch System (SLS) also provides a unique opportunity for lower-cost deep-space science in the form of small-satellite secondary payloads. Current plans call for such opportunities to begin with the rocket's first flight; a launch of the vehicle's Block 1 configuration, capable of delivering 70 metric tons (t) to Low Earth Orbit (LEO), which will send the Orion crew vehicle around the moon and return it to Earth. On that flight, SLS will also deploy 13 CubeSat-class payloads to deep-space destinations. These secondary payloads will include not only NASA research, but also spacecraft from industry and international partners and academia. The payloads also represent a variety of disciplines including, but not limited to, studies of the moon, Earth, sun, and asteroids. While the SLS Program is making significant progress toward that first launch, preparations are already under way for the second, which will see the booster evolve to its more-capable Block 1B configuration, able to deliver 105t to LEO. That configuration will have the capability to carry large payloads co-manifested with the Orion spacecraft, or to utilize an 8.4-meter (m) fairing to carry payloads several times larger than are currently possible. The Block 1B vehicle will be the workhorse of the Proving Ground phase of NASA's deep-space exploration plans, developing and testing the systems and capabilities necessary for human missions into deep space and ultimately to Mars. Ultimately, the vehicle will evolve to its full Block 2 configuration, with a LEO capability of 130 metric tons. Both the Block 1B and Block 2 versions of the vehicle will be able to carry larger secondary payloads than the Block 1 configuration, creating even more opportunities for affordable scientific exploration of deep space. This paper will outline the progress being made toward flying smallsats on the first flight of SLS, and discuss future opportunities for smallsats on subsequent flights.

Robinson, Kimberly F.↗
NASA NTRS2017

Navigating the Deployment and Downlink Tradespace for Earth Imaging Constellations

Distributed Spacecraft Missions (DSMs) are gaining momentum in their application to Earth Observation (EO) missions owing to their unique ability to increase observation sampling in spatial, spectral, angular and temporal dimensions simultaneously. DSM design includes a much larger number of variables than its monolithic counterpart, therefore, Model-Based Systems Engineering (MBSE) has been often used for preliminary mission concept designs, to understand the trade-offs and interdependencies among the variables. MBSE models are complex because the various objectives a DSM is expected to achieve are almost always conflicting, non-linear and rarely analytical. NASA Goddard Space Flight Center (GSFC) is developing a pre-Phase A tool called Tradespace Analysis Tool for Constellations (TAT-C) to initiate constellation mission design. The tool will allow users to explore the tradespace between various performance, cost and risk metrics (as a function of their science mission) and select Pareto optimal architectures that meet their requirements. This paper will describe the different types of constellations that TAT-C’s Tradespace Search Iterator is capable of enumerating (homogeneous Walker, heterogeneous Walker, precessing type, ad-hoc) and their impact on key performance metrics such as revisit statistics, time to global access and coverage. We will also discuss the ability to simulate phased deployment of the given constellations, as a function of launch availabilities and/or vehicle capability, and show the impact on performance. All performance metrics are calculated by the Data Reduction and Metric Computation module within TAT-C, which issues specific requests and processes results from the Orbit and Coverage module. Our TSI is also capable of generating tradespaces for downlinking imaging data from the constellation, based on permutations of available ground station networks - known (default) or customized (by the user). We will show the impact of changing ground station options for any given constellation, on data latency and required communication bandwidth, which in turn determines the responsiveness of the space system.

Nag, Sreeja↗
NASA NTRS2018

Structural Analysis Methodology for Space Deployable Structures Using Multi-Body Dynamic Solver

The purpose of this paper is to provide detailed structural analysis implementation for space deployable structures using a multi-body dynamic solver. The selected commercial code is MSC/ADAMS. Four benchmark problems are used to evaluate mechanism motion, frictional contacts, and geometrically non-linear large deformation. This paper examines the software functionality, performance, accuracy and ability to solve the benchmark problems. The discussions covered are related to solver convergence, tracking internal force, velocity and acceleration of different parts in each model and comparing results to closed form solutions if available.

Montazersadgh, Farzin↗
NASA NTRS2019

Machine Learning Lifecycle for Earth Science Application: A Practical Insight into Production Deployment

Earth science domain presents unique sets of problems that are increasingly being solved using data driven approaches. The availability of big Earth science data offers immense potential for Machine learning (ML) as evident from numerous research publications lately. However, many of these publications are not ending up as production applications mainly because the data scientists who develop the ML models are now expected to complete the ML lifecycle by deploying and scaling the models in production. We introduce ML lifecycle to the Earth science community including the opportunities and challenges that lie ahead in each phase of the lifecycle. We demonstrate the lifecycle using an Earth science problem that we used ML to address and transitioned to production.

Maskey, Manil↗
NASA NTRS2019

Control and Simulation of a Deployable Entry Vehicle with Aerodynamic Control Surfaces

In this paper, we investigate the static stability of a deployable entry vehicle called the Lifting Nano-ADEPT and design a control system to follow bank angle, angle-of-attack, and sideslip guidance commands. The control design, based on linear quadratic regulator optimal techniques, utilizes aerodynamic control surfaces to track angle-of-attack, sideslip angle, and bank angle commands. We demonstrate, using a nonlinear simulation environment, that the controller is able to accurately track step commands that may come from a guidance algorithm.

Margolis, Benjamin W. L.↗
NASA NTRS2020

Pterodactyl: The Development and Performance of Guidance Algorithms for a Mechanically Deployed Entry Vehicle

Pterodactyl is a NASA Space Technology Mission Directorate (STMD) project focused on developing a design capability for optimal, scalable, Guidance and Control (G&C) solutions that enable precision targeting for Deployable Entry Vehicles (DEVs). This feasibility study is unique in that it focuses on the rapid integration of targeting performance analysis with structural & packaging analysis, which is especially challenging for new vehicle and mission designs. This paper will detail the guidance development and trajectory design process for a lunar return mission, selected to stress the vehicle designs and encourage future scalability. For the five G&C configurations considered, the Fully Numerical Predictor-Corrector Entry Guidance (FNPEG) was selected for configurations requiring bank angle guidance and FNPEG with Uncoupled Range Control (URC) was developed for configurations requiring angle of attack and sideslip angle guidance. Successful G&C configurations are defined as those that can deliver payloads to the intended descent and landing initiation point, while abiding by trajectory constraints for nominal and dispersed trajectories.

Johnson, Breanna J.↗
NASA NTRS2020

Pterodactyl: Development and Comparison of Control Architectures for a Mechanically Deployed Entry Vehicle

The Pterodactyl project, seeks to advance the current state-of-the-art for entry vehicles by developing novel guidance and control technologies for Deployable Entry Vehicles (DEVs) that can be applied to various entry vehicle configurations. This paper details the efforts on the NASA-funded Pterodactyl project to investigate and implement multiple control techniques for an asymmetric mechanical DEV. We design multiple control architectures for a Pterodactyl Baseline Vehicle (PBV) and evaluate their performance in achieving varying guidance commands during entry. The control architectures studied are (i) propulsive control systems such as reaction control systems and (ii) non-propulsive control systems such as aerodynamic control surfaces and internal moving masses. For each system, state-feedback integral controllers based on linear quadratic regulator (LQR) optimal control methods are designed to track guidance commands of either (i) bank angle or (ii) angle of attack and sideslip angle as determined by the desired guidance trajectory. All control systems are compared for a lunar return reference mission and by providing a comparative analysis of these systems, configurations, and performance, the efforts detailed in this paper and the Pterodactyl project as a whole will help entry vehicle system designers determine suitable control architectures for integration with DEVs and other entry vehicle types.

Okolo, Wendy A.↗
NASA NTRS2020

Pterodactyl: The Development and Performance of Guidance Algorithms for a Mechanically Deployed Entry Vehicle

Pterodactyl is a NASA Space Technology Mission Directorate (STMD) project focused on developing a design capabilityfor optimal, scalable, Guidance and Control (G&C) solutions that enable precision targeting for Deployable Entry Vehicles(DEVs). This feasibility study is unique in that it focuses on the rapid integration of targeting performance analysis withstructural &packaging analysis, which is especially challenging for new vehicle and mission designs. This paper will detailthe guidance development and trajectory design process for a lunar return mission, selected to stress the vehicle designsand encourage future scalability. For the five G&C configurations considered, the Fully Numerical Predictor-CorrectorEntry Guidance (FNPEG) was selected for configurations requiring bank angle guidance and FNPEG with Uncoupled

Johnson, Breanna↗
NASA NTRS2020

Pterodactyl: Control Architectures Development for Integrated Control Design of a Mechanically Deployed Entry Vehicle

The need to return high mass payloads is driving the development of a new class of vehicles, Deployable Entry Vehicles (DEV) for which feasible and optimized control architectures have not been developed. The Pterodactyl project, seeks to advance the current state-of-the-art for entry vehicles by developing a design, test, and build capability for DEVs that can be applied to various entry vehicle configurations. This paper details the efforts on the NASA-funded Pterodactyl project to investigate multiple control techniques for the Lifting Nano-ADEPT (LNA) DEV. We design and implement multiple control architectures on the LNA and evaluate their performance in achieving varying guidance commands during entry.First we present an overview of DEVs and the Lifting Nano-ADEPT (LNA), along with the physical LNA configuration that influences the different control designs. Existing state-of-the-art for entry vehicle control is primarily propulsive as reaction control systems (RCS) are widely employed. In this work, we analyze the feasibility of using both propulsive control systems such as RCS to generate moments, and non-propulsive control systems such as aerodynamic control surfaces and internal moving mass actuations to shift the LNA center of gravity and generate moments. For these diverse control systems, we design different multi-input multi-output (MIMO) state-feedback integral controllers based on linear quadratic regulator (LQR) optimal control methods. The control variables calculated by the controllers vary, depending on the control system being utilized and the outputs to track for the controller are either the (i) bank angle or the (ii) angle of attack and sideslip angle as determined by the desired guidance trajectory. The LQR control design technique allows the relative allocation of the control variables through the choice of the weighting matrices in the cost index. Thus, it is easy to (i) specify which and how much of a control variable to use, and (ii) utilize one control design for different control architectures by simply modifying the choice of the weighting matrices.By providing a comparative analysis of multiple control systems, configurations, and performance, this paper and the Pterodactyl project as a whole will help entry vehicle system designers and control systems engineers determine suitable control architectures for integration with DEVs and other entry vehicle types.

Okolo, Wendy A.↗
NASA NTRS2020

Deployable Entry Vehicles for Future Science and Exploration Missions

Deployable Entry Vehicle (DEV) technology has made significant advances over the last decade with ground test development campaigns and flight test demonstrations. DEVs offer benefits over traditional rigid entry vehicles including lower volume and mass, while enabling larger payload delivery and greater landing access. A crucial mission benefit is the DEV capability to transform from a compactly stowed configuration within the launch vehicle to a high drag area entry system for delivery of landers, rovers, aerial platforms, and orbiters (via aerocapture). These benefits span the range of mission classes from Small Satellite (smallsat) to human-class exploration systems. This paper will describe DEV technology development status, highlight mission concepts, and recommend future investments.

Alan Cassell↗
NASA NTRSDate not supplied

Multi-Fidelity Heating Prediction of Adaptable, Deployable Entry Placement Technology Vehicles

The objective of this work was to investigate a multi-fidelity modeling approach to accurately and efficiently predict the laminar and turbulent convective heating on adaptable, deployable entry placement technology vehicles in Mars entry. A previously developed co-Kriging based multi-fidelity modeling approach was used to model the laminar and turbulent convective heat fluxes at several surface locations along the vehicle, including the rib sections. The laminar convective heat flux multi-fidelity model was found to have a mean convective heat rate error of approximately 3% when compared to high-fidelity CFD simulations. The turbulent convective heat flux multi-fidelity model was found to have a mean convective heat rate error of approximately 8% when compared to high-fidelity CFD simulations. Compared to a single fidelity model, the multi-fidelity model required approximately one-third the number of high-fidelity model evaluations to obtain the same accuracy level. The computational cost of evaluating the multi-fidelity model was approximately five orders of magnitude less than one high-fidelity model simulation.

Mario Santos↗
NASA NTRS2004

Deployment process, mechanization, and testing for the Mars Exploration Rovers

NASA’s Mar Exploration Rover (MER) robotic prospectors were produced in an environment of unusually challenging schedule, volume, and mass restrictions. The technical challenges pushed the system’s design towards extensive integration of function, which resulted in complex system engineering issues. One example of the system’s integrated complexity can be found in the deployment process for the rover. Part of this process, rover “standup”, is outlined in this paper. Particular attention is given to the Rover Lift Mechanism’s (RLM) role and its design. Analysis methods are presented and compared to test results. It is shown that because prudent design principles were followed, a robust mechanism was created that minimized the duration of integration and test, and enabled recovery without perturbing related systems when reasonably foreseeable problems did occur. Examples of avoidable, unnecessary difficulty are also presented.

Iskenderian, Ted C.↗
NASA NTRS2018

Probabilistic Guidance of a Swarm Deployed from the Back Shell of the Mars Spacecraft

This paper presents a probabilistic guidance algorithm for a swarm of assets deployed from the back shell of the Mars spacecraft. Such a swarm could provide valuable science data, with large spatiotemporal variation, from the Martian surface. Our probabilistic swarm guidance algorithm maximizes the coverage area of the swarm while uniformly distributing the assets on the Martian surface and guaranteeing strong connectivity of the swarm’s communication network topology. Numerical simulations demonstrate the effectiveness and versatility of our probabilistic swarm guidance algorithm.

Hadaegh, Fred↗