SEARCH · Search NASA

Results for “self-recovery”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

8 records

All sources NASA NTRS DOE OSTI

NASA NTRS1992

Micro-rollback and self-recovery synthesis

A new approach to high level synthesis with micro-rollback and self-recovery method is presented. The objective of this approach is to generate a reliable system from the behavioral descriptions. The approach is formulated as a rollback point insertion problem based on the probability function of being inserted rollback points after the given CDFG is scheduled. This function allows us not only to search the problem space efficiently but also to avoid the exhaustive search.

Jeon, Byung Wook↗

NASA NTRS2004

Self-Recovery Experiments in Extreme Environments Using a Field Programmable Transistor Array

Temperature and radiation tolerant electronics, as well as long life survivability are key capabilities required for future NASA missions. Current approaches to electronics for extreme environments focus on component level robustness and hardening. However, current technology can only ensure very limited lifetime in extreme environments. This paper describes novel experiments that allow adaptive in-situ circuit redesign/reconfiguration during operation in extreme temperature and radiation environments. This technology would complement material/device advancements and increase the mission capability to survive harsh environments. The approach is demonstrated on a mixed-signal programmable chip (FPTA-2), which recovers functionality for temperatures until 28 C and with total radiation dose up to 250kRad.

space vehicle electronics↗

DOE OSTI2023

A constitutive model for elastomers tailored by ionic bonds and entanglements

Over the past decade or two, the concept has emerged of using multiple types of weak interactions simultaneously to enhance the mechanical properties of elastomers. These weak interactions include physical entanglements, hydrogen bonds, metal-coordination bonds, dynamic covalent bonds, and ionic bonds. The combination of entanglements and ionic bonding has been minimally explored and is particularly exciting because of the broad application space for polyelectrolytes. In this work, a constitutive model framework is developed to describe the response of elastomers with both ionic bonds and entanglements. Here we formulate a micromechanical model that couples together chain stretching, ionic bond slipping, and entanglement evolution. The ionic bonds provide toughness by enabling plastic deformation in comparison to covalently crosslinked material and add strength compared to a linear polymer. Evolution of the entanglement density is taken as a key mechanism that can govern stiffness, toughness, and self-recovery in elastomers. The model is used to match bulk polyelectrolytes with different fractions of ionic components under a variety of loading histories. The variations in material parameters are then used to help understand the relative importance of different governing mechanisms in the bulk polymers. We show that the theoretical framework can explain our experimental uniaxial tensile experimental results for polyelectrolytes. This model can help to design better material with high stiffness and toughness. We expect that our model can be extended to explain the mechanical behavior of other polyelectrolytes and other soft materials with a wide range of dynamic bonds.

42 ENGINEERING↗

DOE OSTI2023

Reinforcement Learning for Intentional Islanding in Resilient Power Transmission Systems

Intentional islanding is the process of identifying and deliberately decomposing the transmission network to form self-sustained islands from an endangered network during disruptions to improve resilience and security. Most existing intentional islanding models are offline resilience decision tools and hence do not provide outage responses in a timely manner. In this paper, a reinforcement learning (RL) based model for intentional islanding is developed, which offers real-time switching control, online deployability, and adaptability to varying system conditions. The intentional islanding process is formulated as a Markov decision process, where the optimal transmission switching policy is learned using the RL approach. The control policy is learned over an environment that encompasses a Power System Simulator for Engineering (PSS/E) model of the transmission network, facilitated by an interface to the standard openAI Gym framework. The proposed RL-based methodology aims to form stable and self-sustainable islands by ensuring voltage stability while reducing the power mismatch in the formed islands. A proximal policy optimization algorithm is designed, which is suitable for controlling the on/off status of the switches with multi-layer perceptron as value and actor networks. The effectiveness of the proposed framework in the self-recovery of the grid by island formation is applied on the modified IEEE 39-bus test network and validated by dynamic simulations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1997

A High Temperature Vapor Phase Lubrication Study Utilizing a Thioether Liquid Lubricant

Much of the experimental work on vapor phase lubrication has employed certain organo phosphorous compounds as the vapor phase lubricant. Graham and Klaus, for instance, used tricresyl phosphate (TCP) and tributyl phosphate to vapor phase lubricate a four-ball wear tester using M50 steel balls at 370 C. Makki and Graham were able to vapor phase lubricate a reciprocating pin on plate tribometer using 1018 steel at 280 C with TCP vapor. Although a few organo phosphorous compounds, such as TCP, have been successfully used as vapor phase lubricants in many laboratory experiments, many problems remain unsolved. Two areas of concern relate to the 'durability' of phosphate deposited films and to the ability of the lubricating system to "self-recover" when vapor phase lubricated with an organo phosphorous compound. Durability refers to the ability of the deposited film to provide effective lubrication, for a period of time, after the vapor flow to the lubricating surfaces has been interrupted. Vapor phase lubrication tests, conducted at Cleveland State University with their high temperature tribometer, revealed that when TCP vapor flow to the lubricating surfaces was interrupted the frictional coefficient of the system rapidly increased from a value less than 0.1 to a value of 0.3 which was selected as our failure point. Self-recovery means the ability of the vapor phase lubricant to reduce the frictional coefficient of the lubricating system back down to value less than 0.1 after startup of the interrupted vapor flow. Lubrication tests conducted at Cleveland State University revealed that the high temperature tribometer could not self-recover after startup of the interrupted TCP vapor flow.

Morales, Wilfredo↗

NASA NTRSDate not supplied

Development and Validation of a High-Vacuum Thermal Conductivity Testbed for Aerospace Interface Materials

Spacecraft thermal margins depend on the temperature penalty of installed interfaces, yet catalog conductivity omits bondline thickness, mating surfaces, preload, and environment. The Testbed for Advanced Interface Materials in Vacuum (TAIMV) addresses this engineering-data gap by converting ambient/vacuum temperature fields from a four-coupon stack into quantities usable in spacecraft thermal models. Its 17-node steady-state model resolves axial conduction, parasitic fixture paths, grease-filled contact, radiation, and ambient convection. Four monolithic checks gave axial heat-rate ratios of 0.90–1.02, and Braycote calibration self-recovery gave 2.20% casewise mean absolute percentage error (MAPE) and 2.85% maximum difference. With transferable fixture terms frozen, Krytox LVP tested cross-material transfer against a manufacturer-derived external relation. The six Krytox cases gave 2.28% MAPE, 5.10% maximum difference, and full-field residual root-mean-square values of 0.553 °C ambient and 1.306 °C vacuum. Installed-joint resistance spanned 6.39–7.15 × 10⁻⁴ m²·K/W for Braycote and 4.09–4.49 × 10⁻⁴ m²·K/W for Krytox, corresponding to 2.33–6.66 K per modeled interface over the tested heat-flux range. TAIMV therefore supplies directly usable installed-joint resistance and conductance, plus apparent installed conductivity and explicitly model-conditioned grease conductivity/contact terms.

heat transfer↗

NASA NTRS2006

Temperature-Adaptive Circuits on Reconfigurable Analog Arrays

Demonstration of a self-reconfigurable Integrated Circuit (IC) that would operate under extreme temperature (-180 C and 120 C) and radiation (300krad), without the protection of thermal controls and radiation shields. Self-Reconfigurable Electronics platform: a) Evolutionary Processor (EP) to run reconfiguration mechanism; b) Reconfigurable chip (FPGA, FPAA, etc).

self-recovery↗

NASA NTRS2006

Functional Recovery of Analog Circuits at Extreme Temperatures

This paper describes a new reconfigurable analog array (RAA) architecture and integrated circuit (IC) used to map analog circuits that can adapt to extreme temperatures under programmable control. Algorithm-driven adaptation takes place on the RAA IC. The algorithms are implemented in a separate Field Programmable Gate Array (FPGA) IC, co-located with the RAA in the extreme temperature environment. The experiments demonstrate circuit adaptation over a wide temperature range, from extremely low temperature of -180 C to high 120 C.

self-recovery↗