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Results for “Reliability allocation”

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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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

O/S analysis of conceptual space vehicles

The application of recently developed computer models in determining operational capabilities and support requirements during the conceptual design of proposed space systems is discussed. The models used are the reliability and maintainability (R&M) model, the maintenance simulation model, and the operations and support (O&S) cost model. In the process of applying these models, the R&M and O&S cost models were updated. The more significant enhancements include (1) improved R&M equations for the tank subsystems, (2) the ability to allocate schedule maintenance by subsystem, (3) redefined spares calculations, (4) computing a weighted average of the working days and mission days per month, (5) the use of a position manning factor, and (6) the incorporation into the O&S model of new formulas for computing depot and organizational recurring and nonrecurring training costs and documentation costs, and depot support equipment costs. The case study used is based upon a winged, single-stage, vertical-takeoff vehicle (SSV) designed to deliver to the Space Station Freedom (SSF) a 25,000 lb payload including passengers without a crew.

Ebeling, Charles E.↗
NASA NTRS2003

Generalized Symbolic Execution for Model Checking and Testing

Modern software systems, which often are concurrent and manipulate complex data structures must be extremely reliable. We present a novel framework based on symbolic execution, for automated checking of such systems. We provide a two-fold generalization of traditional symbolic execution based approaches: one, we define a program instrumentation, which enables standard model checkers to perform symbolic execution; two, we give a novel symbolic execution algorithm that handles dynamically allocated structures (e.g., lists and trees), method preconditions (e.g., acyclicity of lists), data (e.g., integers and strings) and concurrency. The program instrumentation enables a model checker to automatically explore program heap configurations (using a systematic treatment of aliasing) and manipulate logical formulae on program data values (using a decision procedure). We illustrate two applications of our framework: checking correctness of multi-threaded programs that take inputs from unbounded domains with complex structure and generation of non-isomorphic test inputs that satisfy a testing criterion. Our implementation for Java uses the Java PathFinder model checker.

Khurshid, Sarfraz↗
NASA NTRS2022

Regenerative Life Support Systems for Exploration Habitats: Unique Capabilities and Challenges to Enable Long-Duration-Mission Habitats Beyond Low Earth Orbit

The Artemis I launch of NASA’s Space Launch System and Orion crew vehicle will mark a major milestone in the agency’s efforts to return humans to the Moon. Work is underway on the Human Landing System that will carry the next astronauts to the lunar surface, and the lunar orbiting Gateway that will host science and serve as a platform to support sustained human presence on the Moon and ultimately crewed missions to Mars. Two decades of continuous human presence on the International Space Station has provided a wealth of experience operating, upgrading, and demonstrating advanced Regenerative Environmental Control and Life Support Systems (Regen ECLSS). However, habitats that enable sustained lunar surface presence and transit to Mars will encounter many unique conditions and challenges. System characteristics including reliability, maintainability, mass, and power become significantly more critical. Operating environments associated with lower total pressure, low gravity, contingency protocols, and extensive un-crewed and dormant periods impose additional functionality requirements and alter the performance of certain critical systems. Integration and combined operations with other elements such as orbiting outposts, logistics suppliers, and mobility platforms impact capability and interface requirements. Limits on allocated water and oxygen consumable mass influence the need for higher levels of water and oxygen recovery from waste products. Impacts and challenges these unique exploration circumstances impose on the suite of Regen ECLSS systems are explored and discussed herein.

David F Howard↗
NASA NTRS1989

Implementation of GAMMON - An efficient load balancing strategy for a local computer system

GAMMON (Global Allocation from Maximum to Minimum in cONstant time), an efficient load-balancing algorithm, is described. GAMMON uses the available broadcast capability of multiaccess networks to implement an efficient search technique for finding hosts with maximal and minimal loads. The search technique has an average overhead which is independent of the number of participating stations. The transition from the theoretical concept to a practical, reliable, and efficient implementation is described.

Baumgartner, Katherine M.↗
NASA NTRS2011

Comparison Modeling of System Reliability for Future NASA Projects

A National Aeronautics and Space Administration (NASA) supported Reliability, Maintainability, and Availability (RMA) analysis team developed a unique RMA analysis methodology using cut set and importance measure analysis in order to comparison model proposed avionics computing architectures. In this paper we will present this efficient application of the RMA analysis methodology for importance measures that includes Reliability Block Diagram (RED) Analysis, Comparison modeling, Cut Set Analysis, and Importance Measure Analysis. We will also demonstrate that integrating RMA early in the system design process as a key to success by providing a fundamental decision metric supporting design selection. The RMA analysis methodology presented in this paper and applied to the avionics architectures enhances the usual way of predicting the need for redundancy based on failure rates or subject matter expert opinion. Using the REDs and the minimal cut sets, along with the Fussell-Vesely (FV) factors, importance measures are calculated for each functional element in the architectures. This paper presents an application of the FV importance measures and presents an improved methodology for using importance measures in success space (instead of failure space) to compare architectures. These importance measures are used to determine which functional element would be most likely to cause a system failure, thus, quickly identifying the path to increase the overall system reliability by either procuring more reliable functional elements or adding redundancy. This application of the RMA analysis methodology, using RBD analysis, cut set analysis, and the importance measure analysis, allows the avionics design team to better understand and compare the vulnerabilities in each of the architectures, enabling them to address the deficiencies in the design architectures more efficiently, while balancing the need to design for optimum weight and space allocations.

Gillespie, Amanda M.↗
DOE OSTI2025

Comprehensive assessment of deep reinforcement learning approaches for economic dispatch in nuclear-driven microgrids

As the electrical grid integrates more variable renewable energy sources such as wind and solar, the demand for distributed and flexible systems to address this increased variability becomes critical. Nuclear-driven microgrids provide a promising solution by offering stable generation to complement intermittent renewables, ensuring grid reliability and operating efficiency. This paper proposes a recurrent deep reinforcement learning framework for optimal economic dispatch in a nuclear-powered microgrid integrating renewable energy sources, small modular reactors, battery storage systems, and balance-of-plant dynamics. A three-agent control architecture is developed, where demand and renewable energy agents act as forecasters, and a reinforcement learning-based dispatch agent performs real-time energy allocation. A nonlinear programming formulation is first used to generate an optimal baseline for benchmarking. The proposed dispatch controller, based on Proximal Policy Optimization enhanced with Long Short-Term Memory networks, exploits temporal correlations in system dynamics by taking advantage of the time series used as inputs to improve policy robustness under uncertainty. Comparative analysis against established deep reinforcement learning methods, including Proximal Policy Optimization with a feedforward architecture, Soft Actor-Critic, and Twin Delayed Deep Deterministic Policy Gradient, demonstrates superior performance. Numerical results indicate that the proposed controller achieves a 0.39% cost reduction relative to the nonlinear programming benchmark and outperforms other learning-based methods by generating additional revenue of up to 0.35%. All reinforcement learning controllers compute dispatch actions in less than 0.3 s, resulting in a computational speedup of more than three orders of magnitude over the nonlinear programming baseline. The findings of this paper highlight their applicability for real-time operation and control in nuclear-integrated microgrids under volatile operating conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1981

Study of Thermal Control Systems for orbiting power systems

Thermal control system designs were evaluated for the 25 kW power system. Factors considered include long operating life, high reliability, and meteoroid hazards to the space radiator. Based on a cost advantage, the bumpered pumped fluid radiator is recommended for the initial 25 kW power system and intermediate versions up to 50 kW. For advanced power systems with heat rejection rates above 50 kW the lower weight of the advanced heat pipe radiator offsets the higher cost and this design is recommended. The power system payloads heat rejection allocations studies show that a centralized heat rejection system is the most weight and cost effective approach. The thermal interface between the power system and the payloads was addressed and a concept for a contact heat exchanger that eliminates fluid transfer between the power system and the payloads was developed. Finally, a preliminary design of the thermal control system, with emphasis on the radiator and radiator deployment mechanism, is presented.

Howell, H. R.↗
NASA NTRS2010

Centralized Alert-Processing and Asset Planning for Sensorwebs

A software program provides a Sensorweb architecture for alert-processing, event detection, asset allocation and planning, and visualization. It automatically tasks and re-tasks various types of assets such as satellites and robotic vehicles in response to alerts (fire, weather) extracted from various data sources, including low-level Webcam data. JPL has adapted cons iderable Sensorweb infrastructure that had been previously applied to NASA Earth Science applications. This NASA Earth Science Sensorweb has been in operational use since 2003, and has proven reliability of the Sensorweb technologies for robust event detection and autonomous response using space and ground assets. Unique features of the software include flexibility to a range of detection and tasking methods including those that require aggregation of data over spatial and temporal ranges, generality of the response structure to represent and implement a range of response campaigns, and the ability to respond rapidly.

Castano, Rebecca↗
NASA NTRS2016

Satellite Communications for Unmanned Aircraft C2 Links: C-Band, Ku-Band and Ka-Band

Unmanned aircraft (UA) that require access to controlled (or non-segregated) airspace require a highly reliable and robust command and control (C2) link, operating over protected aviation spectrum. While operating within radio line-of-sight (LOS) UA can make use of air-to-ground C2 links to terrestrial stations. When operating beyond LOS (BLOS) where a group of networked terrestrial stations does not exist to provide effective BLOS coverage, a satellite communications link is required. Protected aviation spectrum for satellite C2 links has only recently been allocated in bands where operational satellites exist. A previously existing C-Band allocation covers a bands where there are currently no operational satellites. The new allocations, within the Fixed Satellite Service bands at Ku and Ka-Bands will not be finalized until 2023 due to the need for the development of standards and technical decisions on the operation of UA satellite C2 links within these bands. This paper provides an overview of BLOS satellite C2 links, some of the conditions which will need to be met for the operation of such links, and a look at some aspects of spectrum sharing which may constrain these operations.

radiofrequency spectrum↗
DOE OSTI2024

Distributed Energy Resource Interconnection Roadmap

Adopting strategic reforms to DER interconnection can help reduce interconnection delays, fairly allocate costs, improve transparency and equity, and support efficient and strategic investment in distribution and sub-transmission grids that can accommodate a rapidly evolving energy landscape. The Interconnection Innovation e-Xchange envisions this roadmap and its transmission system companion volume as collaborative resources to facilitate continued stakeholder discussions, problem-solving, and innovation as the U.S. works together to enable simpler, faster, and fairer interconnection of clean energy resources all while enhancing the reliability, resiliency, and security of our electric grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1984

Aerospace Safety Advisory Panel

An assessment of NASA's safety performance for 1983 affirms that NASA Headquarters and Center management teams continue to hold the safety of manned flight to be their prime concern, and that essential effort and resources are allocated for maintaining safety in all of the development and operational programs. Those conclusions most worthy of NASA management concentration are given along with recommendations for action concerning; product quality and utility; space shuttle main engine; landing gear; logistics and management; orbiter structural loads, landing speed, and pitch control; the shuttle processing contractor; and the safety of flight operations. It appears that much needs to be done before the Space Transportation System can achieve the reliability necessary for safe, high rate, low cost operations.

Source record↗
NASA NTRS2010

Impact of Conflict Avoidance Responsibility Allocation on Pilot Workload in a Distributed Air Traffic Management System

Pilot workload was examined during simulated flights requiring flight deck-based merging and spacing while avoiding weather. Pilots used flight deck tools to avoid convective weather and space behind a lead aircraft during an arrival into Louisville International airport. Three conflict avoidance management concepts were studied: pilot, controller or automation primarily responsible. A modified Air Traffic Workload Input Technique (ATWIT) metric showed highest workload during the approach phase of flight and lowest during the en-route phase of flight (before deviating for weather). In general, the modified ATWIT was shown to be a valid and reliable workload measure, providing more detailed information than post-run subjective workload metrics. The trend across multiple workload metrics revealed lowest workload when pilots had both conflict alerting and responsibility of the three concepts, while all objective and subjective measures showed highest workload when pilots had no conflict alerting or responsibility. This suggests that pilot workload was not tied primarily to responsibility for resolving conflicts, but to gaining and/or maintaining situation awareness when conflict alerting is unavailable.

Ligda, Sarah V.↗
NASA NTRSDate not supplied

Problem Complexity and LLM: H-M Team Reliability in Challenging Environments

In traditional human-machine operations, the functional decomposition of actions and responsibilities among various agents is assigned a priori. For instance, in current air traffic operations, although assisted by software, human pilots have the ultimate control of aircraft. Multiagent human-machine and machine-machine systems will face problems of varying and potentially unpredicted complexity in future challenging scenarios of planetary, en route, and orbital activities. Hence, it is important to enable dynamic transfer of decision-making to appropriate team members, human or machine, depending on which agent is best equipped to solve that specific problem on a time budget. In this paper, we consider aspects of problem-solving and its modeling that affect the outcomes of decision-making as a function of solution quality and the likelihood of solving the problem on a required time budget. We focus on Large Language Models (LLM) as potential machine teammates and conclude that practical, predictive modeling of their performance, at the current stage of their development, is infeasible. Simple examples help us illustrate that current LLM will require fundamental advancements to provide reliable support in team decision-making, especially in safety-critical and time-critical domains. The study is not meant to diminish the value of the remarkable capabilities of LLM, but rather to gain a better understanding of the technology’s appropriate use and the needed additions.

function allocation↗
NASA NTRS2013

Real-Time Optimization for use in a Control Allocation System to Recover from Pilot Induced Oscillations

Integration of the Control Allocation technique to recover from Pilot Induced Oscillations (CAPIO) System into the control system of a Short Takeoff and Landing Mobility Concept Vehicle simulation presents a challenge because the CAPIO formulation requires that constrained optimization problems be solved at the controller operating frequency. We present a solution that utilizes a modified version of the well-known L-BFGS-B solver. Despite the iterative nature of the solver, the method is seen to converge in real time with sufficient reliability to support three weeks of piloted runs at the NASA Ames Vertical Motion Simulator (VMS) facility. The results of the optimization are seen to be excellent in the vast majority of real-time frames. Deficiencies in the quality of the results in some frames are shown to be improvable with simple termination criteria adjustments, though more real-time optimization iterations would be required.

optimal control↗
NASA NTRS2014

Use of DES Modeling for Determining Launch Availability for SLS

The National Aeronautics and Space Administration (NASA) is developing new capabilities for human and scientific exploration beyond Earth's orbit. This effort includes the Space Shuttle derived Space Launch System (SLS), the Multi-Purpose Crew Vehicle (MPCV) "Orion", and the Ground Systems Development and Operations (GSDO). There are several requirements and Technical Performance Measures (TPMs) that have been levied by the Exploration Systems Development (ESD) upon the SLS, MPCV, and GSDO Programs including an integrated Launch Availability (LA) TPM. The LA TPM is used to drive into the SLS, Orion and GSDO designs a high confidence of successfully launching exploration missions that have narrow Earth departure windows. The LA TPM takes into consideration the reliability of the overall system (SLS, Orion and GSDO), natural environments, likelihood of a failure, and the time required to recover from an anomaly. A challenge with the LA TPM is the interrelationships between SLS, Orion, GSDO and the natural environments during launch countdown and launch delays that makes it impossible to develop an analytical solution for calculating the integrated launch probability. This paper provides an overview of how Discrete Event Simulation (DES) modeling was used to develop the LA TPM, how it was allocated down to the individual programs, and how the LA analysis is being used to inform and drive the SLS, Orion, and GSDO designs to ensure adequate launch availability for future human exploration.

Watson, Mike↗
NASA NTRS2014

Use of DES Modeling for Determining Launch Availability for SLS

The National Aeronautics and Space Administration (NASA) is developing new capabilities for human and scientific exploration beyond Earth's orbit. This effort includes the Space Shuttle derived Space Launch System (SLS), the Orion Multi-Purpose Crew Vehicle (MPCV), and the Ground Systems Development and Operations (GSDO). There are several requirements and Technical Performance Measures (TPMs) that have been levied by the Exploration Systems Development (ESD) upon the SLS, Orion, and GSDO Programs including an integrated Launch Availability (LA) TPM. The LA TPM is used to drive into the SLS, Orion and GSDO designs a high confidence of successfully launching exploration missions that have narrow Earth departure windows. The LA TPM takes into consideration the reliability of the overall system (SLS, Orion and GSDO), natural environments, likelihood of a failure, and the time required to recover from an anomaly. A challenge with the LA TPM is the interrelationships between SLS, Orion, GSDO and the natural environments during launch countdown and launch delays that makes it impossible to develop an analytical solution for calculating the integrated launch probability. This paper provides an overview of how Discrete Event Simulation (DES) modeling was used to develop the LA TPM, how it was allocated down to the individual programs, and how the LA analysis is being used to inform and drive the SLS, Orion, and GSDO designs to ensure adequate launch availability for future human exploration.

Staton, Eric↗
DOE OSTI2025

Assessing the Impact of Lubrication on Efficiency and Life Cycle Economics of the US Wind Turbine Fleet: Cooperative Research and Development (Final Report)

As with any mechanical system, lubrication plays a key role in the performance of wind turbines used to generate electricity. The lubricant design offers a way to optimize the competing requirements of efficiency, component reliability, and maintenance strategy. This project will estimate the impact of improved lubrication on the levelized cost of energy of the US wind turbine fleet as a means of identifying opportunities for disruptive innovation or system-level optimization. The models developed will provide a clear understanding of the benefits and potential for advanced lubrication of wind turbines. The project will enable identification of high value targets for wind turbine component suppliers and a roadmap that highlights where the greatest return on technology investment can be achieved. This will promote efficient resource allocation in areas of new technology development.

17 WIND ENERGY↗
DOE OSTI2025

VA EDH Advanced Software Pipeline Framework Report: Enhancing Automation and Scalability

The VA Environmental Determinants of Health (EDH) Advanced Software Pipeline Framework is designed to enhance the efficiency, scalability, and security of geospatial data processing workflows. This framework integrates modern data orchestration and containerization technologies, including Prefect for workflow automation, Docker for containerization, and PostgreSQL/PostGIS for geospatial data storage and analysis. It ensures standardized, reproducible, and automated data processing, supporting VA objectives related to substance use risk assessment and recovery research. The pipeline addresses key scalability and performance challenges through horizontal and vertical scaling, high-performance computing (HPC) integration, parallel processing, task caching, and dynamic resource allocation. These optimizations improve throughput and reduce latency, allowing the system to efficiently manage large and complex datasets. Additionally, security and compliance measures—such as data encryption (SSL), Role-Based Access Control (RBAC), and adherence to GDPR and HIPAA standards—safeguard sensitive information throughout data transmission and storage. A key implementation of this framework includes the automation of shelter list geolocation workflows, ensuring that up-to-date data is readily available for VA decision-making. Lessons learned from this project include the transition from in-memory processing to incremental storage writes, improving resource management and reliability. Future enhancements aim to expand automation, integrate AI-driven anomaly detection, and incorporate high-performance computing resources. This framework provides a scalable, secure, and adaptable solution for managing geospatial datasets, reinforcing the VA’s ability to support clinical and strategic initiatives through data-driven decision-making.

97 MATHEMATICS AND COMPUTING↗