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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
DOE OSTI2024

Fully quantum algorithm for mesoscale fluid simulations with application to partial differential equations

Fluid flow simulations marshal our most powerful computational resources. In many cases, even this is not enough. Quantum computers provide an opportunity to speed up traditional algorithms for flow simulations. We show that lattice-based mesoscale numerical methods can be executed as efficient quantum algorithms due to their statistical features. This approach revises a quantum algorithm for lattice gas automata to reduce classical computations and state preparation at every time step. For this, the algorithm approximates the qubit relative phases and subtracts them at the end of each time step. Phases are evaluated using the iterative phase estimation algorithm and subtracted using single-qubit rotation phase gates. Further, this method optimizes the quantum resource required and makes it more appropriate for near-term quantum hardware. We also demonstrate how the checkerboard deficiency that the D1Q2 scheme presents can be resolved using the D1Q3 scheme. The algorithm is validated by simulating two canonical partial differential equations: the diffusion and Burgers' equations on different quantum simulators. We find good agreement between quantum simulations and classical solutions for the presented algorithm.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2004

Learning to Control Advanced Life Support Systems

Advanced life support systems have many interacting processes and limited resources. Controlling and optimizing advanced life support systems presents unique challenges. In particular, advanced life support systems are nonlinear coupled dynamical systems and it is difficult for humans to take all interactions into account to design an effective control strategy. In this project. we developed several reinforcement learning controllers that actively explore the space of possible control strategies, guided by rewards from a user specified long term objective function. We evaluated these controllers using a discrete event simulation of an advanced life support system. This simulation, called BioSim, designed by Nasa scientists David Kortenkamp and Scott Bell has multiple, interacting life support modules including crew, food production, air revitalization, water recovery, solid waste incineration and power. They are implemented in a consumer/producer relationship in which certain modules produce resources that are consumed by other modules. Stores hold resources between modules. Control of this simulation is via adjusting flows of resources between modules and into/out of stores. We developed adaptive algorithms that control the flow of resources in BioSim. Our learning algorithms discovered several ingenious strategies for maximizing mission length by controlling the air and water recycling systems as well as crop planting schedules. By exploiting non-linearities in the overall system dynamics, the learned controllers easily out- performed controllers written by human experts. In sum, we accomplished three goals. We (1) developed foundations for learning models of coupled dynamical systems by active exploration of the state space, (2) developed and tested algorithms that learn to efficiently control air and water recycling processes as well as crop scheduling in Biosim, and (3) developed an understanding of the role machine learning in designing control systems for advanced life support.

Subramanian, Devika↗
NASA NTRS2015

IAF 15 Draft Paper

With the International Space Station Program transition from assembly to utilization, focus has been placed on the optimization of essential resources. This includes resources both resupplied from the ground and also resources produced by the ISS. In an effort to improve the use of two of these, the ISS Engineering teams, led by the ISS Program Systems Engineering and Integration Office, undertook an effort to modify the techniques use to perform several key on-orbit events. The primary purposes of this endeavor was to make the ISS more efficient in the use of the Russian-supplied fuel for the propulsive attitude control system and also to minimize the impacts to available ISS power due to the positioning of the ISS solar arrays. Because the ISS solar arrays are sensitive to several factors that are present when propulsive attitude control is used, they must be operated in a manner to protect them from damage. This results in periods of time where the arrays must be positioned, rather than autonomously tracking the sun, resulting in negative impacts to power generated by the solar arrays and consumed by both the ISS core systems and payload customers. A reduction in the number and extent of the events each year that require the ISS to use propulsive attitude control simultaneously accomplishes both these goals. Each instance where the ISS solar arrays normal sun tracking mode must be interrupted represent a need for some level of powerdown of equipment. As the magnitude of payload power requirements increases, and the efficiency of the ISS solar arrays decreases, these powerdowns caused by array positioning, will likely become more significant and could begin to negatively impact the payload operations. Through efforts such as this, the total number of events each year that require positioning of the arrays to unfavorable positions for power generation, in order to protect them against other constraints, are reduced. Optimization of propulsive events and transitioning some of them to non-propulsive CMG control significantly reduces propellant usage on the ISS leading to the reduction of the propellant delivery requirement. This results in move available upmass that can be used for delivering critical dry cargo, additional water, air, crew supplies and science experiments.

Menkin, Evgeny↗
DOE OSTI2025

Evaluating opportunity for distributed wind energy in rural and agricultural areas

Wind energy is among the most mature renewable energy technologies, accounting for 11% of the current US electricity generation in 2024, with the lowest average levelized cost. While it is known that substantial opportunity exists for further development, a key question has been where wind energy is best suited compared to other technologies. This study leverages an immense dataset of parcel-resolved technoeconomic potential for the contiguous United States, focusing on distributed wind (DW) energy—a configuration where one or more turbines, typically 30–60 m in height are used to satisfy nearby energy needs. The analysis is conducted at multiple spatial scales and considers land use, crop land, census, and incentive program data to determine the most opportune areas for market development. The results show that rural, agricultural and residential areas are most suited to DW. Connection type (in front of, or behind the meter) and regulations determine the best application, while siting constraints, economics, demand and the wind resource determines the optimal size of turbine.

17 WIND ENERGY↗
DOE OSTI2024

A Measurement-Based Adaptive Voltage Regulation Method Considering Topology Changes

This paper proposes an online adaptive data-driven distributed energy resource (DER) dispatch optimization method for voltage control considering topology changes. By using a local sensitivity factor (LSF)-enabled voltage control, traditional DER control can be reformulated into a linear programming (LP) problem, leading to faster computation speeds. Power injection alteration and topology changes are two common operational changes in the distribution network that can affect the LSF and voltage control performance. To address this issue, a robust estimation method is developed to adjust the sensitivity matrix at each time step for the time-varying power injection changes. When topology changes occur, only the allocated predominant LSF submatrices are updated based on measurement data, allowing for a fast adaptation to the system reconfiguration. Results obtained from a real distribution feeder in Southern California demonstrate its robustness as compared to traditional volt-var control and constant LSF matrix dispatch control methods.

DERs↗
DOE OSTI2025

torc (Torc Workflow Management System) [SWR-24-127]

This software package orchestrates execution of a workflow of jobs on distributed computing resources. It is optimized for use on HPCs with Slurm, but also can be used in the cloud and on local computers. Please refer to the documentation at https://nrel.github.io/torc

Thom, Daniel [National Renewable Energy Laboratory↗
DOE OSTI2025

C4.jl [SWR-25-106]

A proof-of-concept software framework for integrating capacity expansion and production cost optimization with probabilistic resource adequacy assessment and sending feedback signals between the models.

Stephen, Gordon [National Renewable Energy Laborat↗
DOE OSTI2024

Containers on Switches: A Cluster School Experience

Network switches, such as those from Arista and Mellanox, often have underutilized computational resources in the form of built-in processors and memory. By leveraging these untapped resources, we can optimize functionality and efficiency of computational cluster networks. Our research focuses on deploying containers directly onto these switches to execute various auxiliary tasks ranging from metric logging to system-wide management via post-boot configuration. By doing so, we can significantly enchance the capabilities of the cluster without the need for additional dedicated hardware. Our research involved five distinct scenarios where switch utilization could have a profound impact on HPC Clusters: run cloud-init services via link-local connection; configuring a Telegraf container to export metrics; deploying a caching proxy; creating a reconfigurable IPv6 DHCP/DNS provider for VLAN; and implementing a client detection with Magellan discovery. These scenarios were containerized with podman and docker, and tested both physically on the switch virtually on a QEMU VM both running SONiC OS. Testing and findings indicate that network switches can indeed be used for these scenarios. They offer a wide range of possibilities beyond these applications. They run as expected as containers on the switches, and although there were some minor issues, work-arounds were implemented. Overall, this is a positive result that can be further explored with more scenarios.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1990

SURE (Science User Resource Expert): A science planning and scheduling assistant for a resource based environment

SURE (Science User Resource Expert) is one of three components that compose the SURPASS (Science User Resource Planning and Scheduling System). This system is a planning and scheduling tool which supports distributed planning and scheduling, based on resource allocation and optimization. Currently SURE is being used within the SURPASS by the UARS (Upper Atmospheric Research Satellite) SOLSTICE instrument to build a daily science plan and activity schedule and in a prototyping effort with NASA GSFC to demonstrate distributed planning and scheduling for the SOLSTICE II instrument on the EOS platform. For the SOLSTICE application the SURE utilizes a rule-based system. Development of a rule-based program using Ada CLIPS as opposed to using conventional programming, allows for capture of the science planning and scheduling heuristics in rules and provides flexibility in inserting or removing rules as the scientific objectives and mission constraints change. The SURE system's role as a component in the SURPASS, the purpose of the SURE planning and scheduling tool, the SURE knowledge base, and the software architecture of the SURE component are described.

Thalman, Nancy E.↗
NASA NTRS1991

Cargo transfer vehicle RCS propellant contamination issues

The purpose of this report is to address Cargo Transfer Vehicle (CTV) RCS contamination issues and contribute to the resources necessary to optimize the vehicle and propulsion systems required in the CTV of the National Launch System (NLS) Heavy Lift Launch Vehicle (HLLV). This study reviews the thruster-induced contaminants; their transportation from the thrust chamber to the vehicle, payload, and SSF; and the mechanism by which damage is inflicted on their components. The effect of both monopropellant and bipropellant RCS rocket exhaust plumes on a spacecraft and related functional surfaces has been the subject of considerable study over the years. It is recognized that the RCS rocket produces contaminants which can significantly degrade the performance of optical windows, solar cells, thermal-protective coatings, and other external vehicle components. This is particularly true when the rocket is operating in the pulse mode. The exhaust plume impingement pressure and heat-transfer phenomena also complicate the environment to which the vehicle and its functional surfaces are exposed, but are not addressed in this study. Bipropellant contamination presented several modes of damage to incident surfaces, which can pose a long-term deleterious consequence to CTV payloads and the Space Station Freedom (SSF). Monopropellant contamination did not pose any significant long-term issues other than the possibility of aniline deposition. The use of either bipropellant and monopropellant propulsion systems can have a design impact on the CTV propulsion system with respect to maneuvering operations in the proximity of SSF.

Ballard, Richard O.↗
NASA NTRS2003

Ionic signaling in plant gravity and touch responses

Plant roots are optimized to exploit resources from the soil and as each root explores this environment it will encounter a range of biotic and abiotic stimuli to which it must respond. Therefore, each root must possess a sensory array capable of monitoring and integrating these diverse stimuli to direct the appropriate growth response. Touch and gravity represent two of the biophysical stimuli that plants must integrate. As sensing both of these signals requires mechano-transduction of biophysical forces to biochemical signaling events, it is likely that they share signal transduction elements. These common signaling components may allow for cross-talk and so integration of thigmotropic and gravitropic responses. Indeed, signal transduction events in both plant touch and gravity sensing are thought to include Ca(2+)- and pH-dependent events. Additionally, it seems clear that the systems responsible for root touch and gravity response interact to generate an integrated growth response. Thus, primary and lateral roots of Arabidopsis respond to mechanical stimuli by eliciting tropic growth that is likely part of a growth strategy employed by the root to circumvent obstacles in the soil. Also, the mechano-signaling induced by encountering an obstacle apparently down-regulates the graviperception machinery to allow this kind of avoidance response. The challenge for future research will be to define how the cellular signaling events in the root cap facilitate this signal integration and growth regulation. In addition, whether other stimuli are likewise integrated with the graviresponse via signal transduction system cross-talk is an important question that remains to be answered.

Review↗
NASA NTRS2005

Incorporation of a Chemical Equilibrium Equation of State into LOCI-Chem

Renewed interest in development of advanced high-speed transport, reentry vehicles and propulsion systems has led to a resurgence of research into high speed aerodynamics. As this flow regime is typically dominated by hot reacting gaseous flow, efficient models for the characteristic chemical activity are necessary for accurate and cost effective analysis and design of aerodynamic vehicles that transit this regime. The LOCI-Chem code recently developed by Ed Luke at Mississippi State University for NASA/MSFC and used by NASA/MSFC and SSC represents an important step in providing an accurate, efficient computational tool for the simulation of reacting flows through the use of finite-rate kinetics [3]. Finite rate chemistry however, requires the solution of an additional N-1 species mass conservation equations with source terms involving reaction kinetics that are not fully understood. In the equilibrium limit, where the reaction rates approach infinity, these equations become very stiff. Through the use of the assumption of local chemical equilibrium the set of governing equations is reduced back to the usual gas dynamic equations, and thus requires less computation, while still allowing for the inclusion of reacting flow phenomenology. The incorporation of a chemical equilibrium equation of state module into the LOCI-Chem code was the primary objective of the current research. The major goals of the project were: (1) the development of a chemical equilibrium composition solver, and (2) the incorporation of chemical equilibrium solver into LOCI-Chem. Due to time and resource constraints, code optimization was not considered unless it was important to the proper functioning of the code.

Cox, Carey F.↗
NASA NTRS2006

The Development of Jomo Kenyatta International Airport as a Regional Aviation Hub

Air transportation plays an important role in the social and economic development of the global system and the countries that seek to participate in it. As Africa seeks to take its place in the global economy, it is increasingly looking to aviation as the primary means of connecting its people and goods with the world. It has been suggested that Africa as a continent needs to move toward a system of hubs to optimize its scarce resources. Jomo Kenyatta International Airport in Nairobi, Kenya, is one of the airports in the eastern region of Africa that is seeking to fill this role. This paper discusses the prospects for success and the challenges that it will need to overcome, including projections through 2020 for the growth in passenger and cargo traffic.

Irandu, Evaristus M.↗
NASA NTRS2008

Self-Adjusting Hash Tables for Embedded Flight Applications

A common practice in computer science to associate a value with a key is to use a class of algorithms called a hash-table. These algorithms enable rapid storage and retrieval of values based upon a key. This approach assumes that many keys will need to be stored immediately. A new set of hash-table algorithms optimally uses system resources to ideally represent keys and values in memory such that the information can be stored and retrieved with a minimal amount of time and space. These hash-tables support the efficient addition of new entries. Also, for large data sets, the look-up time for large data-set searches is independent of the number of items stored, i.e., O(1), provided that the chance of collision is low.

James, Mark↗
NASA NTRS2020

What Can We Learn from One Billion Ground System Log Messages?

Shortage of log-based data in a ground system they have traditionally been the under achievers in a satellite ground system. This is due to several factors: Once log messages scroll out of view on the TTC event console window they are soon forgotten. Application and system log files are scattered across directories within a system, across a multitude of servers, and across one or more databases making access cumbersome. Typical tools to perform log file content searching are generally crude and typically only employed as part of trouble-shooting exercises.As we move towards satellite constellations and fleets and add even more status information, the number of messages keeps growing. One mission now estimates that they could generate 3,000,000 messages per day 1 billion per year - for the life of their mission. What to do with those 1 billion messages? That is the challenge. With the recent technological advances in the management of large data sets, text-based processing, and data analytics, there are now capabilities that we can provide to the ground system engineers and satellite operators to address what we postulate are missed opportunities. Advanced real-time log analysis can allow us to be less reactionary in favor of being more proactive. Analytics goals include the ability to: Identify root cause of unexpected events, failures or error conditions enabled by correlating disparate data. Detect security breaches attempts before they are successful. Help admins ensure IT resources continue running optimally. Identify trends and patterns that may indicate impending failures or error conditions for valuable assets before they happen. Compare satellites in a fleet or constellation in terms of number of alarms, number of command sent to them, etc.. Answer questions like "Are the operations support needs increasing over the past year?" or "Have we seen this combination of alarm conditions before?" But really, once the tools are readily available the users will start realizing what can be done with their new powers. In this presentation we will show the results of analyzing millions of actual mission operations log messages, how the results can be displayed to the user, and how new products now available as open source can be applied to the challenges of large scale time-tagged text-based mission operations messages. Flight operations team members believe that this is a powerful new option for how they assess overall system and space asset health. Technical descriptions of the design, tools, and storage will be provided. One billion messages? Bring'em on!

Orsborne, Sharon↗
NASA NTRSDate not supplied

Quantifying the Sensitivity of Condition Incidence Parameters in the Evidence Library

One approach to quantifying spaceflight risk at NASA makes use event driven probabilistic techniques. The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) is such a tool that estimates medical risk metrics via simulation and enables optimization of medical resources subject to mission constraints [1]. Previous analyses have informed medical set composition, exercise countermeasures, and water intake, where each analysis quantifies the risk associated with proposed variations in system design. As future mission profiles extend beyond Low-Earth Orbit (LEO) and lengthen in duration, understanding these risks and contributing factors is critical. MEDPRAT employs Monte Carlo sampling techniques to simulate missions and track the occurrence of medical events. These events follow fault-tree-like progressions through levels of severity and mitigation via medical treatment to many possible outcomes and these are reported throughout the mission. Making this possible, are the medical databases that contain evidence gathered by the Human Research Program (HRP). Quantifying the impact of uncertainty or variability in the input data is an important step in evaluating the credibility of modeling and simulation results. In this work, we investigate the sensitivity of medical risk metrics with respect to the condition incidence parameters within the Evidence Library (EL) [2] as the medical database input for MEDPRAT. The medical conditions, contained in the EL, are equipped with incidence rates that describe the likelihood that the condition will occur. These incidence rates reflect historical spaceflight data or when appropriate, terrestrial data. In this presentation, we will explore how uncertainty in these rates propagate to the medical risk described by MEDPRAT. These results identify the conditions and parameters with the largest contribution to medical risks.

Ian Lim↗
DOE OSTI2025

Optimal Network Reconfiguration and Scheduling With Hardware-in-the-Loop Validation for Improved Microgrid Resilience

With the increased occurrence of various major extreme weather events, power outages and prompt power system restorations have recently drawn more attention to the resilience and recovery of power systems. From the perspective of a more resilient power delivery at the distribution grid, system restoration using network topology reconfiguration together with optimal scheduling of distributed energy resources are adopted in this paper. The proposed optimization model aims at minimizing the total load shedding cost and other operational costs, in which linearized topological constraints borrowed from graph theory and linearized DistFlow models are respectively used to maintain the radial network topology and power flow balance after system contingencies. To demonstrate the applicability of the proposed strategy, a real-world case study of a networked three-microgrid system in Adjuntas, Puerto Rico, is used with the consideration of different independent/interconnected microgrid scenarios, contingencies, and fairness settings. Furthermore, hardware-in-the-loop testing is conducted for the same three-microgrid network, where the closely matched results with the simulated ones have validated the effectiveness of the proposed restoration strategy, which is now ready to move one step forward towards field deployment. Finally, to test the proposed restoration strategy in a larger networked system, the modified IEEE-33 bus test distribution system is considered, and the results show a more resilient power delivery for critical loads under three and four line outages.

24 POWER TRANSMISSION AND DISTRIBUTION↗