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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Space Station Freedom electrical performance model

The baseline Space Station Freedom electric power system (EPS) employs photovoltaic (PV) arrays and nickel hydrogen (NiH2) batteries to supply power to housekeeping and user electrical loads via a direct current (dc) distribution system. The EPS was originally designed for an operating life of 30 years through orbital replacement of components. As the design and development of the EPS continues, accurate EPS performance predictions are needed to assess design options, operating scenarios, and resource allocations. To meet these needs, NASA Lewis Research Center (LeRC) has, over a 10 year period, developed SPACE (Station Power Analysis for Capability Evaluation), a computer code designed to predict EPS performance. This paper describes SPACE, its functionality, and its capabilities.

Hojnicki, Jeffrey S.↗
NASA NTRS2011

Current Status of the Nitrogen Oxygen Recharge System

This paper presents an overview of the Nitrogen Oxygen Recharge System (NORS) to date and the current development status of the system. NORS is an element of the International Space Station (ISS) Environmental Control and Life Support Systems (ECLSS) used to resupply the ISS with Nitrogen and Oxygen following the impending retirement of the Space Shuttle. The paper will discuss why NASA is developing NORS, including a summary of other concepts considered, and other related concepts currently being developed by NASA. The current system architecture will be described, along with a summary of the current design of the NORS. The overall programmatic schedule of the NORS in the context of the upcoming shuttle retirement and future launch vehicle development will also be presented. Finally, the paper will examine the significant technical challenges encountered during the requirements and preliminary design phase of NORS development. A key challenge to the development of NORS is the international shipment - and associated regulations - of pressurized Oxygen, which is necessary due to the use of launch vehicles based in Japan and French Guiana to send NORS gasses to the ISS. The storage and use of relatively large quantities of high pressure (41,000 kPa) Oxygen and Nitrogen within the ISS, which is unprecedented both on the ISS and other space vehicles, has had a significant impact on the design and architecture of the system. The high pressure of the system also poses unique thermal considerations, which has led to the development of a heater system for thermal conditioning of high pressure gas to avoid thermal impacts on downstream hardware. The on-orbit envelope allocated to the NORS has changed (gotten smaller) and has impacted both the design and architecture of the system. Finally, the balance of safety considerations associated with these high pressure gasses, particularly high pressure Oxygen, with the functionality of the system has profoundly impacted the form of the system and will be discussed.

Dick, Brandon↗
NASA NTRS2013

Risk-Constrained Dynamic Programming for Optimal Mars Entry, Descent, and Landing

A chance-constrained dynamic programming algorithm was developed that is capable of making optimal sequential decisions within a user-specified risk bound. This work handles stochastic uncertainties over multiple stages in the CEMAT (Combined EDL-Mobility Analyses Tool) framework. It was demonstrated by a simulation of Mars entry, descent, and landing (EDL) using real landscape data obtained from the Mars Reconnaissance Orbiter. Although standard dynamic programming (DP) provides a general framework for optimal sequential decisionmaking under uncertainty, it typically achieves risk aversion by imposing an arbitrary penalty on failure states. Such a penalty-based approach cannot explicitly bound the probability of mission failure. A key idea behind the new approach is called risk allocation, which decomposes a joint chance constraint into a set of individual chance constraints and distributes risk over them. The joint chance constraint was reformulated into a constraint on an expectation over a sum of an indicator function, which can be incorporated into the cost function by dualizing the optimization problem. As a result, the chance-constraint optimization problem can be turned into an unconstrained optimization over a Lagrangian, which can be solved efficiently using a standard DP approach.

Ono, Masahiro↗
DOE OSTI2025

Reproductive and leaf litterfall fluxes in forest ecosystem sites globally (1950-2022)

Forest allocation of net primary productivity (NPP) to reproduction is poorly quantified globally, despite its critical role in forest regeneration and a well-supported trade-off with allocation to growth. Although field measurements of total NPP are rare, our work finds that a proxy for reproductive carbon allocation constructed from leaf (L) and reproductive (R) litterfall fluxes, R/(R+L), is strongly correlated with R/NPP, facilitating analysis across a wide range of sites where biometric estimates of NPP are not available (R² = 0.85; Hanbury-Brown et al., 2022, Ward et al., in prep). To investigate relationships between ecosystem-scale reproductive allocation (RA) and climate, soil fertility, and stand age gradients, we conducted a literature search and synthesized 824 observations of annual average leaf and reproductive litterfall fluxes across forest sites globally. The zip file includes 1) a folder Data/ containing the litterfall data ("GlobalForestRA_data.csv") and metadata ("GlobalForestRA_metadata.doc") files. The data file includes geographic coordinates, long-term mean annual temperature and precipitation (1970-2000, extracted from WorldClim2.1), leaf and reproductive litterfall fluxes, sampling interval and protocols, forest characteristics (dominant leaf morphology, information pertaining to forest age and successional stage, and disturbance history) and soil properties (% sand, %silt, %clay, total phosphorus (P), nitrogen (N), cation exchange capacity (CEC) and pH) extracted from SoilGrids250 and from on-site measurements, where available. The metadata file contains information about each variable reported in the data file, including data sources, processing methods, and all references. The Data folder contains two additional files used to create Figure 1; these are described in greater detail in the README.2) R scripts GloalForestRA_analysis.r and GlobalForestRA_SI.r and a folder /Functions used to produce results, figures, and tables in the manuscript Ward et al. (in press)3) a README file describing how the data and R scripts can be used to reproduce statistical results, figures, and tables found in the manuscript. Ward et al. (in press)This repository can also be found at: https://github.com/r-ward/Global_Analysis_ForestRA.Ward, R.E., Zhang-Zheng, H. Aernethy, K., Adu-Bredu, S., Arroyo, L., Bailey, A. et al. (in press). Forest age rivals climate to explain reproductive allocation patterns in forest ecosystems globally. Ecology Letters. Hanbury-Brown, A.R., Ward, R.E. & Kueppers, L.M. (2022). Forest regeneration within Earth system models: current process representations and ways forward. New Phytol., 235, 20–40.Ward et al. (2025), Forest age rivals climate to explain reproductive allocation patterns in forest ecosystems globally, in prep.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Multilevel Monte Carlo Estimators For Derivative-Free Optimization Under Uncertainty

Optimization is a key tool for scientific and engineering applications; however, in the presence of models affected by uncertainty, the optimization formulation needs to be extended to consider statistics of the quantity of interest. Optimization under uncertainty (OUU) deals with this endeavor and requires uncertainty quantification analyses at several design locations; i.e., its overall computational cost is proportional to the cost of performing a forward uncertainty analysis at each design location. An OUU workflow has two main components: an inner loop strategy for the computation of statistics of the quantity of interest, and an outer loop optimization strategy tasked with finding the optimal design, given a merit function based on the inner loop statistics. Here, in this work, we propose to alleviate the cost of the inner loop uncertainty analysis by leveraging the so-called multilevel Monte Carlo (MLMC) method, which is able to allocate resources over multiple models with varying accuracy and cost. The resource allocation problem in MLMC is formulated by minimizing the computational cost given a target variance for the estimator. We consider MLMC estimators for statistics usually employed in OUU workflows and solve the corresponding allocation problem. For the outer loop, we consider a derivative-free optimization strategy implemented in the SNOWPAC library; our novel strategy is implemented and released in the Dakota software toolkit. We discuss several numerical test cases to showcase the features and performance of our approach with respect to its Monte Carlo single fidelity counterpart.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2014

Low-Cost, Class D Testing of Spacecraft Photovoltaic Systems Can Reduce Risk

The end-to-end verification of a spacecraft photovoltaic power generation system requires light! Specifically, the standard practice for doing so is the Large Area Pulsed Solar Simulation (LAPSS). A LAPSS test can characterize a photovoltaic system's efficiency via its response to rapidly applied impulses of simulated sunlight. However, a Class D program on a constrained budget and schedule may not have the resources to ship an entire satellite for a LAPSS test alone. Such was the case with the Lunar Atmospheric and Dust Environment Explorer (LADEE) program, which was also averse to the risk of hardware damage during shipment. When the Electrical Power System (EPS) team was denied a spacecraft-level LAPSS test, the lack of an end-to-end power generation test elevated to a project-level technical risk. The team pulled together very limited resources to not only eliminate the risk, but build a process to monitor the health of the system through mission operations. We discuss a process for performing a low-cost, end-to-end test of the LADEE photovoltaic system. The approach combines system-level functional test, panel-level performance results, and periodic inspection (and repair) up until launch. Following launch, mission operations tools are utilized to assess system performance based on a scant amount of data. The process starts in manufacturing at the subcontractor. The panel manufacturer provides functional test and LAPSS data on each individual panel. We apply an initial assumption that the per-panel performance is sufficient to meet the power generation requirements. The manufacturer's data is also carried as the performance allocation for each panel during EPS system modeling and initial mission operations. During integration and test, a high-power, professional theater lamp system provides simulated sunlight to each panel on the spacecraft, thereby permitting a true end-to-end system test. A passing test results in a step response to nearly full-rated current at the appropriate solar array switch in the power system. A metal-halide bulb, infrared imagers, and onboard spacecraft measurements are utilized to minimize risk of thermal damage during test. Data is provided to support test results for both passing and marginal panels. Prior to encapsulation in the launch vehicle, each panel is inspected for damage by the panel manufacturer. Cracked cells or other damage is amended on-site. Because the photovoltaic test system is inexpensive and portable, each repaired panel can be re-verified immediately. Post-launch, the photovoltaic system is again characterized for per-panel deviations from the manufacturer's performance test. This proved especially tricky as the LADEE spacecraft performs only one current measurement on the entire array. The algorithm for Matlab tools to assess panel performance based on spacecraft attitude is discussed. While not as precise and comprehensive as LAPSS, the LADEE approach leverages minimal resources into an ongoing assessment program that can be applied through numerous stages of the mission. The project takes a true Class D approach in assessing the technical value of a spacecraft level performance test versus the programmatic risk of shipping the spacecraft to another facility. The resources required are a fraction of that for a LAPSS test, and is easy to repeat. Further, the test equipment can be handed down to future projects without building an on-site facility.

photovoltaic↗
NASA NTRS2008

Spaceborne Processor Array

A Spaceborne Processor Array in Multifunctional Structure (SPAMS) can lower the total mass of the electronic and structural overhead of spacecraft, resulting in reduced launch costs, while increasing the science return through dynamic onboard computing. SPAMS integrates the multifunctional structure (MFS) and the Gilgamesh Memory, Intelligence, and Network Device (MIND) multi-core in-memory computer architecture into a single-system super-architecture. This transforms every inch of a spacecraft into a sharable, interconnected, smart computing element to increase computing performance while simultaneously reducing mass. The MIND in-memory architecture provides a foundation for high-performance, low-power, and fault-tolerant computing. The MIND chip has an internal structure that includes memory, processing, and communication functionality. The Gilgamesh is a scalable system comprising multiple MIND chips interconnected to operate as a single, tightly coupled, parallel computer. The array of MIND components shares a global, virtual name space for program variables and tasks that are allocated at run time to the distributed physical memory and processing resources. Individual processor- memory nodes can be activated or powered down at run time to provide active power management and to configure around faults. A SPAMS system is comprised of a distributed Gilgamesh array built into MFS, interfaces into instrument and communication subsystems, a mass storage interface, and a radiation-hardened flight computer.

Chow, Edward T.↗
DOE OSTI2021

Theoretical evidence that root penetration ability interacts with soil compaction regimes to affect nitrate capture

Abstract Background and Aims Although root penetration of strong soils has been intensively studied at the scale of individual root axes, interactions between soil physical properties and soil foraging by whole plants are less clear. Here we investigate how variation in the penetration ability of distinct root classes and bulk density profiles common to real-world soils interact to affect soil foraging strategies. Methods We utilize the functional–structural plant model ‘OpenSimRoot’ to simulate the growth of maize (Zea mays) root systems with variable penetration ability of axial and lateral roots in soils with (1) uniform bulk density, (2) plow pans and (3) increasing bulk density with depth. We also modify the availability and leaching of nitrate to uncover reciprocal interactions between these factors and the capture of mobile resources. Key Results Soils with plow pans and bulk density gradients affected overall size, distribution and carbon costs of the root system. Soils with high bulk density at depth impeded rooting depth and reduced leaching of nitrate, thereby improving the coincidence of nitrogen and root length. While increasing penetration ability of either axial or lateral root classes produced root systems of comparable net length, improved penetration of axial roots increased allocation of root length in deeper soil, thereby amplifying N acquisition and shoot biomass. Although enhanced penetration ability of both root classes was associated with greater root system carbon costs, the benefit to plant fitness from improved soil exploration and resource capture offset these. Conclusions While lateral roots comprise the bulk of root length, axial roots function as a scaffold determining the distribution of these laterals. In soils with high soil strength and leaching, root systems with enhanced penetration ability of axial roots have greater distribution of root length at depth, thereby improving capture of mobile resources.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Carbon-phosphorus cycle models overestimate CO 2 enrichment response in a mature Eucalyptus forest

The importance of phosphorus (P) in regulating ecosystem responses to climate change has fostered P-cycle implementation in land surface models, but their CO 2 effects predictions have not been evaluated against measurements. Here, we perform a data-driven model evaluation where simulations of eight widely used P-enabled models were confronted with observations from a long-term free-air CO 2 enrichment experiment in a mature, P-limited Eucalyptus forest. We show that most models predicted the correct sign and magnitude of the CO 2 effect on ecosystem carbon (C) sequestration, but they generally overestimated the effects on plant C uptake and growth. We identify leaf-to-canopy scaling of photosynthesis, plant tissue stoichiometry, plant belowground C allocation, and the subsequent consequences for plant-microbial interaction as key areas in which models of ecosystem C-P interaction can be improved. Together, this data-model intercomparison reveals data-driven insights into the performance and functionality of P-enabled models and adds to the existing evidence that the global CO 2 -driven carbon sink is overestimated by models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Modeling Mycorrhizal Carbon Costs in Temperate Forests: The Impacts of Functional Diversity and Global Change Factors

Mycorrhizal fungi form symbiotic relationships with most plant species, facilitating nutrient acquisition while consuming a significant fraction of the plant's photosynthetic carbon (C), which we define as the mycorrhizal C cost. Drivers of the mycorrhizal C cost, which is crucial for predicting environmental impacts on plant productivity, remain under-explored and difficult to quantify. Ecosystem models that incorporate mycorrhizae can offer insights into mycorrhizal C cost dynamics, but their predictions have rarely been validated against empirical data. Here, in this study, we used the Myco-CORPSE model, which explicitly simulates mycorrhizal processes alongside soil carbon and nitrogen cycling, to investigate the drivers of mycorrhizal C cost in temperate forests. Applying this model to over 1,800 forest inventory plots across the eastern United States, we found that the simulations matched published data, showing higher C allocation to ectomycorrhizal (ECM) fungi (16.0% of net primary production (NPP)) compared to arbuscular mycorrhizal (AM) fungi (5.8% of NPP). Further analysis showed that mixed forests, co-dominated by both AM and ECM trees, allocated less C to mycorrhizal fungi compared to forests dominated by either AM or ECM fungi alone, due to complementary nutrient acquisition strategies. Elevated Nitrogen (N) deposition and higher temperatures reduce mycorrhizal C costs, favoring AM strategies. Conversely, elevated CO 2 (eCO 2 ) increased plant N demand and mycorrhizal C costs, favoring ECM strategies that access organic N sources. These findings underscore the critical role of mycorrhizal functional diversity in plant nutrient acquisition and C dynamics, providing new insights into how mycorrhizal symbioses respond to global change.

Shao, Siya [Dartmouth College, Hanover, NH (United↗
NASA NTRS2022

A Generalized Approach to Aircraft Trajectory Prediction via Supervised Deep Learning

As research advances diverse forms and missions of aircraft, the National Airspace System (NAS) will become increasingly crowded, limiting current communications resources to accommodate aviation operations. Ongoing research proposes a paradigm of airspace communications, such that resources are autonomously and dynamically allocated via intelligent agents; this allocation requires accurate representations of the NAS, including the predicted positions of aircraft. State-of-the-art research emphasizes the importance of a hybrid-recurrent framework for trajectory prediction and compares the impact of commonly considered weather data on prediction accuracy. However, current research has been limited in its scope of efforts, frequently utilizing a unique flight route, architecture, set of weather data, and date range. This article considers the challenges of generalizing hybrid-recurrent predictive models for flight trajectories. Results illustrate an increase in error variance when identical models are trained over a generalized set of flights; this may be mitigated with careful tuning of hyperparameters, both in the network structure and optimization algorithms. Even so, an irreducible vertical error was identified, resulting from the complex takeoff and landing procedures which can not be correlated to functions of weather or additional assumptions of aircraft behavior. Finally, the use of a test route indicates that generalized models still do not possess sufficient knowledge for general aircraft predictions, with mean error increases ranging from 70-500%. These results illustrate the need for continued efforts on improving model versatility, as well as potential limitations for spectrum allocation near airports and other centers.

Nathan Schimpf↗
DOE OSTI2024

Patterning of multicomponent elastic shells by gaussian curvature

Recent findings suggest that shell protein distribution and the morphology of bacterial microcompartments regulate the chemical fluxes facilitating reactions which dictate their biological function. Here, we explore how the morphology and component patterning are coupled through the competition of mean and gaussian bending energies in multicomponent elastic shells that form three-component irregular polyhedra. We observe two softer components with lower bending rigidities allocated on the edges and vertices while the harder component occupies the faces. When subjected to a nonzero interfacial line tension, the two softer components further separate and pattern into subdomains that are mediated by the gaussian curvature. We find that this degree of fractionation is maximized when there is a weaker line tension and when the ratio of bending rigidities between the two softer domains ≈2. Our results reveal a patterning mechanism in multicomponent shells that can capture the observed morphologies of bacterial microcompartments, and moreover, can be realized in synthetic vesicles.

Monte Carlo methods↗
NASA NTRS2009

Flightspeed Integral Image Analysis Toolkit

The Flightspeed Integral Image Analysis Toolkit (FIIAT) is a C library that provides image analysis functions in a single, portable package. It provides basic low-level filtering, texture analysis, and subwindow descriptor for applications dealing with image interpretation and object recognition. Designed with spaceflight in mind, it addresses: Ease of integration (minimal external dependencies) Fast, real-time operation using integer arithmetic where possible (useful for platforms lacking a dedicated floatingpoint processor) Written entirely in C (easily modified) Mostly static memory allocation 8-bit image data The basic goal of the FIIAT library is to compute meaningful numerical descriptors for images or rectangular image regions. These n-vectors can then be used directly for novelty detection or pattern recognition, or as a feature space for higher-level pattern recognition tasks. The library provides routines for leveraging training data to derive descriptors that are most useful for a specific data set. Its runtime algorithms exploit a structure known as the "integral image." This is a caching method that permits fast summation of values within rectangular regions of an image. This integral frame facilitates a wide range of fast image-processing functions. This toolkit has applicability to a wide range of autonomous image analysis tasks in the space-flight domain, including novelty detection, object and scene classification, target detection for autonomous instrument placement, and science analysis of geomorphology. It makes real-time texture and pattern recognition possible for platforms with severe computational restraints. The software provides an order of magnitude speed increase over alternative software libraries currently in use by the research community. FIIAT can commercially support intelligent video cameras used in intelligent surveillance. It is also useful for object recognition by robots or other autonomous vehicles

Thompson, David R.↗
DOE OSTI2021

On Anomaly Detection for Transactive Energy Systems with Competitive Market

Two anomaly-detection criteria are proposed for transactive energy systems with competitive markets. Participants of transactive energy systems seek an optimal power allocation through hybrid economic-control methods to facilitate the integration of various types of distributed energy resources to power distribution systems. In transactive energy systems, every participant is assumed to be a rational entity, and consumers have diminishing marginal utility and suppliers have increasing marginal cost. With the first proposed anomaly-detection criterion, the monotonicity of marginal cost and marginal utility are examined. The impact of line flow constraints is also taken into consideration. Then, the second anomaly-detection criterion is proposed for TESs with marginal cost and marginal utility which change faster than a certain rate. The second criterion is more accurate than the first one for TES with marginal cost and marginal utility which change faster than a certain rate, but it requires the knowledge of that rate. Neither criteria requires more data than those necessary to find the optimal power allocation and the market-clear price in a transactive energy system. Therefore, the proposed criteria do not disclose any more data than necessary. As the monotonicity of marginal cost and marginal utility in a TES with competitive markets results in convex objective functions in an optimization problem and strongly convex ones when marginal cost and marginal utility changes faster than a certain rate, the two detection criteria are also applicable to anomaly detection of general convex optimization problems. Simulations are carried out to show the efficacy of the proposed criteria to detect anomalies caused by cyberattacks.

Wang, Peng↗
NASA NTRS2019

Interference Mitigation Using Cyclic Autocorrelation and Multi-Objective Optimization

Radio frequency interference on space-to-ground communications links can degrade performance and disrupt the transfer of critical data. These interference events become increasingly likely as more users enter the spectrum, due in part to shared spectrum allocations and scheduling conflicts. If this interference could be detected and mitigated by an automated system, then link performance and reliability in these scenarios could be improved. This report describes the implementation and evaluation of an automated interference mitigation system that provides this functionality. The system uses Cyclic Autocorrelation (CAC) signal processing techniques to monitor the spectrum and detect interfering signals, and it applies a multi-objective optimization approach to mitigate interference by changing link parameters to continuously optimize the link. The implementation was evaluated to characterize its signal detection capabilities for various link qualities and to compare its link management performance to Adaptive Coding and Modulation (ACM) and Constant Coding and Modulation (CCM) when in the presence of randomized interference. In the latter evaluation, the interference mitigation system achieved the highest average throughput in each tested scenario. With these results, the proposed solution provides the groundwork for further automated link management capabilities and continued investigation into interference mitigation approaches.

Interference mitigation↗
DOE OSTI2025

SECURED: Simulator-Enhanced Control and Understanding of Reactor systems for cyber-Event Defense

The study discusses a learning approach for analyzing cyber-events in reactor systems using integrated hardware and personal computer simulator models. Key points include the rise in cyber-attacks and their sophistication in industrial control systems (ICS), the necessity for awareness, understanding, resource allocation, and preparation to combat these threats, and the digital transformation of old and new nuclear plants, increasing their exposure to cyber threats. It highlights the cyber vulnerabilities of advanced reactor systems, which rely on digital instrumentation and control for operations and safety functions, making them susceptible to cyber-attacks. The approach involves demonstrating reactor system plant ICS cyber-attacks under various operational conditions utilizing tools like simulator models and hardware-based kits. A strategic solution approach tailored to critical infrastructure is emphasized, along with community engagement for public and government support, adopting effective learning approaches, and the preparation for anticipated future challenges. The presentation concludes with a call to action to address challenges, leverage opportunities, and advance through lesson learning in cybersecurity for nuclear energy systems.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2006

CCSDS Time-Critical Onboard Networking Service

The Consultative Committee for Space Data Systems (CCSDS) is developing recommendations for communication services onboard spacecraft. Today many different communication buses are used on spacecraft requiring software with the same basic functionality to be rewritten for each type of bus. This impacts on the application software resulting in custom software for almost every new mission. The Spacecraft Onboard Interface Services (SOIS) working group aims to provide a consistent interface to various onboard buses and sub-networks, enabling a common interface to the application software. The eventual goal is reusable software that can be easily ported to new missions and run on a range of onboard buses without substantial modification. The system engineer will then be able to select a bus based on its performance, power, etc and be confident that a particular choice of bus will not place excessive demands on software development. This paper describes the SOIS Intra-Networking Service which is designed to enable data transfer and multiplexing of a variety of internetworking protocols with a range of quality of service support, over underlying heterogeneous data links. The Intra-network service interface provides users with a common Quality of Service interface when transporting data across a variety of underlying data links. Supported Quality of Service (QoS) elements include: Priority, Resource Reservation and Retry/Redundancy. These three QoS elements combine and map into four TCONS services for onboard data communications: Best Effort, Assured, Reserved, and Guaranteed. Data to be transported is passed to the Intra-network service with a requested QoS. The requested QoS includes the type of service, priority and where appropriate, a channel identifier. The data is de-multiplexed, prioritized, and the required resources for transport are allocated. The data is then passed to the appropriate data link for transfer across the bus. The SOIS supported data links may inherently provide the quality of service support requested by the intra-network layer. In the case where the data link does not have the required level of support, the missing functionality is added by SOIS. As a result of this architecture, re-usable software applications can be designed and used across missions thereby promoting common mission operations. In addition, the protocol multiplexing function enables the blending of multiple onboard networks. This paper starts by giving an overview of the SOIS architecture in section 11, illustrating where the TCONS services fit into the overall architecture. It then describes the quality of service approach adopted, in section III. The prototyping efforts that have been going on are introduced in section JY. Finally, in section V the current status of the CCSDS recommendations is summarized.

Parkes, Steve↗
NASA NTRS1979

Work management plan for data systems and analysis directorate

A contract with the Data Systems and Analysis Directorate contains a specified level of resources related to a specific set of work in support of three divisions within the Data Systems and Analysis Directorate. The divisions are Institutional Data Systems Division, Ground Data Systems Division, and Mission Planning and Analysis Division. The Statement of work defines at a functional requirements level the type of support to be provided to the three divisions. The contract provides for further technical direction to the contractor through issuance of Job Orders. The Job order is the prime method of further defining the work to be done, allocating a portion of the total resources in the contract to the defined tasks, and further delegating technical responsibility.

Nichols, L. R.↗