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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2020

Solar Observation in X and Ka Bands Using DSA 3 Deep Space Station

In recent years, two deep space stations have been installed in Argentina, DSA 3 of the European Space Agency and CLTC-CONAE-NEUQUEN of China Launch and Tracking Control General. Ten percent of the operating time of these stations is available for the use of the Argentine scientific community through the Announcement of Opportunity published by the National Commission for Space Activities. In this work, some first observational tests of the solar disk have been carried out in the working bands of the DSA 3 station with the aim of measuring the capabilities of the instruments installed for this type of experiment and the developing of tools for pointing the antenna and the processing of received data. All this experience will be used to make a new observation with similar characteristics during the solar eclipse of December 14, 2020.

Kuiper, Tom↗
NASA NTRS1986

DSA's subcarrier demodulation losses

The degradation in bit error rate performance due to imperfect subcarrier tracking by the Demodulation Synchronization Assembly (DSA) is investigated. Results apply to any type of digital loop and received signal dynamics. A type four loop causes the least amount of loss, because it tracks phase jerk with zero steady-state error. However, when frequency rate and frequency acceleration are as large as in the extended Magellan mission, it will be necessary to decrease the loop update time in order to minimize the losses.

Simon, M.↗
NASA NTRS2020

Distributed Spacecraft Autonomy (DSA): Development of Swarm Autonomy Capability and Scalability for Spacecraft

The Distributed Spacecraft Autonomy project is developing a suite of software tools that enable an operator to command and receive data from a swarm as a single entity, enable a swarm to autonomously coordinate its actions via distributed decision making and reactive closed-loop control, and model swarm behavior in the presence of anomalies or failures. Our use case is the mapping of the electron density of the ionosphere using radio tomography by coordinating the selection of appropriate GPS channels, and by recording Total Electron Count (TEC)measurements. DSA will be demonstrated on board the NASA Ames Starling mission a swarm of four small, LEO spacecraft, scheduled to launch in 2021. We will also perform a ground demonstration with simulated and hardware-in-the-loop elements, to validate the tools for controlling swarms of up to 100 assets.The capability to communicate autonomously between the swarm satellites is demonstrated via a sophisticated simulation architecture. Historical Plasma sphere TEC data obtained via dual-band Novatel GPS Receivers are utilized as a representative input data set for the swarm. The representative TEC data and GPS satellite observability information is fed to the autonomous software package in place of a true real-time ground data collection process. The swarm satellites actively share status updates amongst one another and utilize multi-agent decision making to optimally identify regions of interest in the TEC distribution. The software,aware of the bandwidth limitations of the swarm satellites, prioritizes explorative measurements,which define the range of observability for the satellites, as well as exploitative measurements,which focus on maximizing the observance potential of regions with prolonged, elevated TEC density. The science of this study can ultimately be used to determine the dynamics and coupling of Earth's magnetosphere, ionosphere, and atmosphere and their response to solar and terrestrial inputs. The findings can be applied to the imaging of critical, transient phenomena in the magnetosphere in later missions. Meanwhile, the swarm autonomy capabilities have far reaching potential in future satellite missions.As an experimental demonstration of the autonomous capabilities of the network, a message is first printed within a core Flight Executive (cFE) application. Two cFE applications that communicate with one another within the same core Flight System (cFS) are shown.Communication between mission applications on the internal cFE bus is extended to utilize Data Distribution Service (DDS) for vehicle-to-vehicle networking. The DDS middle ware provides reliable delivery, routing, and topic subscription features over User Data gram Protocol (UDP).Leveraging Linux containerization, a networked set of satellite instances are generated by script to simulate swarm behavior. Swarm commanding and synchronization through the network is demonstrated under various topologies and data-loss conditions. Finally, autonomous swarms calability from 2 satellites to 100 satellites is shown.

Fugate, Jason↗
NASA NTRSDate not supplied

The Distributed Spacecraft Autonomy (DSA)

NASA’s Distributed Spacecraft Autonomy (DSA) Project developed and demonstrated software to enhance multi-spacecraft mission adaptability, efficiently allocate tasks between spacecraft using ad-hoc networking, and enable human-swarm commanding of Distributed Space Missions.

Autonomy Distributed Space Missions↗
NASA NTRS1985

Performance of the Dsa's Subcarrier Demodulation Digital Loop

The subcarrier demodulation digital loop is part of the baseband assembly. The subcarrier demodulator is a fourth-order Costas-type loop corresponding to a type 2 analog loop in terms of steady state response. The expected value and the variance of the error signal are determined as functions of the input SNR. A Nyquist sampling rate of the input signal is assumed. From the integro-difference equations a mixed s/z domain block diagram is obtained. From the loop's transfer function a set of gains for the loop filter is obtained. Also, a set of state equations is presented for future reference. Finally, the noise-equivalent bandwidths are calculated for normalized computation times of 0, 0.25 and 0.5. The subcarrier demodulator analyzed tracks a parabolic phase input with finite steady state error. Since at each update instant the loop gains are adjusted to compensate for the variations in SNR of the input signal, the noise-equivalent bandwidth is maintained constant.

Simon, M. K.↗
NASA NTRSDate not supplied

Advancing Autonomy in Distributed Space Systems: Insights From on-Orbit Testing with the Starling 1.0 Mission

Autonomous decision-making is crucial for enhancing mission effectiveness in Distributed Space Systems (DSS), particularly in multi-spacecraft operations where communication constraints and mission complexity pose challenges. The Distributed Spacecraft Autonomy (DSA) team at NASA’s Ames Research Center is advancing autonomy in DSS through five key technical areas: distributed resource and task management, reactive operations, system modeling and simulation, human-swarm interaction, and ad hoc network communications. The DSA experiment onboard the Starling 1.0 Mission showcases collaborative resource allocation for multi-point science data collection with four small spacecraft. Autonomy in decision-making is highlighted as a crucial factor for multi-spacecraft missions, enabling spacecraft to operate independently, reducing reliance on ground control. This capability is particularly significant for future deep-space missions, where communication delays and limited data transmission capacity make traditional command and control approaches impractical. This demonstration focuses on a GPS Channel Selection Experiment, leveraging emergent capabilities like "shared sampling" and "simultaneous sampling" to optimize channel selection across the spacecraft swarm. The experiment aims to capture ionospheric phenomena such as the Equatorial Ionization Anomaly and Polar Patches. The DSA system's autonomous reconfiguration ability is showcased, emphasizing its adaptability to natural phenomena without significant integration efforts. The GPS Channel Selection Experiment utilizes a dual-band GPS receiver to estimate plasma density in the ionosphere. Explorative and exploitative channel selections are employed based on the nature of observed phenomena. The performance of DSA algorithms is evaluated in terms of optimal channel allocations and responsiveness to changes in observed features. The DSA Flight Software utilizes the Core Flight System (cFS) framework, ensuring compatibility with the Starling 1.0 flight mission software. DSA showcases results from RTI’s Connext DDS Micro communication middleware, enabling message routing over the Ad-Hoc Network of Starling 1.0. This paper provides a comprehensive overview of the DSA experiment's initial results, emphasizing the advancements in autonomy for Distributed Space Systems and the successful collaboration with the Starling 1.0 mission.

Caleb Ashmore Adams↗
NASA NTRS1989

On equivalence of discrete-discrete and continuum-discrete design sensitivity analysis

Developments in design sensitivity analysis (DSA) method have been made using two fundamentally different approaches as shown. In the first approach, a discretized structural finite element model is used to carry out DSA. There are three different methods in the discrete DSA approach: finite difference, semi-analytical, and analytical methods. The finite difference method is a popular one due to its simplicity, but a serious shortcoming of the method is the uncertainty in the choice of a perturbation step size of design variables. In the semi-analytical method, the derivatives of stiffness matrix is computed by finite differences, whereas in the analytical method, the derivatives are obtained analytically. For the shape design variable, computation of analytical derivative of stiffness matrix is quite costly. Because of this, the semi-analytical method is a popular choice in discrete shape DSA approach. However, recently, Barthelemy and Haftka presented that the semi-analytical method can have serious accuracy problems for shape design variables in structures modeled by beam, plate, truss, frame, and solid elements. They found that accuracy problems occur even for a simple cantilever beam. In the second approach, a continuum model of the structure is used to carry out DSA.

Choi, Kyung K.↗
NASA NTRS1995

Temperature Dependent Cyclic Deformation Mechanisms in Haynes 188 Superalloy

The cyclic deformation behavior of a wrought cobalt-base superalloy, Haynes 188, has been investigated over a range of temperatures between 25 and 1000 C under isothermal and in-phase thermomechanical fatigue (TMF) conditions. Constant mechanical strain rates (epsilon-dot) of 10(exp -3)/s and 10(exp -4)/s were examined with a fully reversed strain range of 0.8%. Particular attention was given to the effects of dynamic strain aging (DSA) on the stress-strain response and low cycle fatigue life. A correlation between cyclic deformation behavior and microstructural substructure was made through detailed transmission electron microscopy. Although DSA was found to occur over a wide temperature range between approximately 300 and 750 C the microstructural characteristics and the deformation mechanisms responsible for DSA varied considerably and were dependent upon temperature. In general, the operation of DSA processes led to a maximum of the cyclic stress amplitude at 650 C and was accompanied by pronounced planar slip, relatively high dislocation density, and the generation of stacking faults. DSA was evidenced through a combination of phenomena, including serrated yielding, an inverse dependence of the maximum cyclic hardening with epsilon-dot, and an instantaneous inverse epsilon-dot sensitivity verified by specialized epsilon-dot -change tests. The TMF cyclic hardening behavior of the alloy appeared to be dictated by the substructural changes occuring at the maximum temperature in the TMF cycle.

Rao, K. Bhanu Sankara↗
NASA NTRSDate not supplied

Design and Testing of Autonomous Distributed Space Systems

Distributed Space Systems (DSS) are an emerging class of mission designs that enable new scientific and commercial opportunities. In order to enable those new opportunities, these systems will need to have significantly expanded autonomous capabilities compared to their single-spacecraft predecessors. In this paper, we present Distributed Spacecraft Autonomy (DSA) project, a payload on NASA's Starling spacecraft experiment. We first describe a step-by-step process for characterizing what features are needed in an autonomous DSS, and show how this process applied to DSA. We then describe the Starling mission, a four-spacecraft swarm hosting multiple DSS payloads. We then describe DSA, which will mature in-space networking and autonomous planning technologies to measure topside ionosophere features using data from the Starling spacecraft's GPS receivers. We describe how DSA will coordinate observations of GPS satellites using Starling's underlying communications infrastructure combined with novel DSS technology. The flight validation of DSS technology will provide mature technology to enable future DSS missions.

Nicholas Cramer↗
NASA NTRS2023

An Overview of Distributed Spacecraft Autonomy at NASA Ames

Autonomous decision-making significantly increases mission effectiveness by mitigating the effects of communication constraints, like latency and bandwidth, and mission complexity on multi-spacecraft operations. To advance the state of the art in autonomous Distributed Space Systems (DSS), the Distributed Spacecraft Autonomy (DSA) team at NASA's Ames Research Center is developing within five relevant technical areas: distributed resource and task management, reactive operations, system modeling and simulation, human-swarm interaction, and ad hoc network communications. DSA is maturing these technologies - critical for future large autonomous DSS - from concept to launch via simulation studies and orbital deployments. A 100-node heterogenous Processor-in-the-Loop (PiL) testbed aids distributed autonomy capability development and verification of multi-spacecraft missions. The DSA software payload deployed to the D-Orbit SCV-004 spacecraft demonstrates multi-agent reconfigurability and reliability as part of an ESA-sponsored in-orbit technology demonstration. Finally, DSA's primary flight mission showcases collaborative resource allocation for multipoint science data collection with four small spacecraft as a payload on NASA's Starling 1.0 satellites.

Caleb Ashmore Adams↗
NASA NTRS2004

New Generation Power System for Space Applications

The Deep Space Avionics (DSA) Project is developing a new generation of power system building blocks. Using application specific integrated circuits (ASICs) and power switching modules a scalable power system can be constructed for use on multiple deep space missions including future missions to Mars, comets, Jupiter and its moons. The key developments of the DSA power system effort are five power ASICs and a mod ule for power switching. These components enable a modular and scalab le design approach, which can result in a wide variety of power syste m architectures to meet diverse mission requirements and environments . Each component is radiation hardened to one megarad) total dose. The power switching module can be used for power distribution to regular spacecraft loads, to propulsion valves and actuation of pyrotechnic devices. The number of switching elements per load, pyrotechnic firin gs and valve drivers can be scaled depending on mission needs. Teleme try data is available from the switch module via an I2C data bus. The DSA power system components enable power management and distribution for a variety of power buses and power system architectures employing different types of energy storage and power sources. This paper will describe each power ASIC#s key performance characteristics as well a s recent prototype test results. The power switching module test results will be discussed and will demonstrate its versatility as a multip urpose switch. Finally, the combination of these components will illu strate some of the possible power system architectures achievable fro m small single string systems to large fully redundant systems.

power switching↗
NASA NTRS1991

Transient thermoelasticity and other body force effects in boundary element shape sensitivity analysis

Structural shape design sensitivity analysis (DSA) is presented for objects subjected to gravity, centrifugal, and general thermal loading. DSA employs implicit differentiation of the governing boundary integral equations. Both a surface integral and a particular integral approach are discussed for computation of these effects in response analysis and sensitivity analysis. It is shown that the particular integral approach is capable of computing the sensitivities of objects subjected to nonharmonic temperature distributions. Attention is also given to several techniques for the modeling of temperature distributions in the DSA process. In particular, an approach that eliminates the need for the incorporation of thermal response analysis and sensitivity analysis is described in the overall shape optimization process. A sharp corner formulation is also presented that can account for the jump in the surface traction components at a sharp corner in an interzone boundary.

Kane, James H.↗
NASA NTRS1993

Geometrically nonlinear design sensitivity analysis on parallel-vector high-performance computers

Parallel-vector solution strategies for generation and assembly of element matrices, solution of the resulted system of linear equations, calculations of the unbalanced loads, displacements, stresses, and design sensitivity analysis (DSA) are all incorporated into the Newton Raphson (NR) procedure for nonlinear finite element analysis and DSA. Numerical results are included to show the performance of the proposed method for structural analysis and DSA in a parallel-vector computer environment.

Baddourah, Majdi A.↗