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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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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Information adaptive system of NEEDS

The NASA End-to-End Data System (NEEDS) program was initiated by NASA to improve significantly the state of the art in acquisition, processing, and distribution of space-acquired data for the mid-1980s and beyond. The information adaptive system (IAS) is a program element under NEEDS Phase II which addresses sensor specific processing on board the spacecraft. The IAS program is a logical first step toward smart sensors, and IAS developments - particularly the system components and key technology improvements - are applicable to future smart efforts. The paper describes the design goals and functional elements of the IAS. In addition, the schedule for IAS development and demonstration is discussed.

Howle, W. M., Jr.↗
NASA NTRS2017

Carbon Nanofiber Electrode Array for Neurochemical Monitoring

A sensor platform based on vertically aligned carbon nanofibers (CNFs) has been developed. Their inherent nanometer scale, high conductivity, wide potential window, good biocompatibility and well-defined surface chemistry make them ideal candidates as biosensor electrodes. Here, we report using vertically aligned CNF as neurotransmitter recording electrodes for application in a smart deep brain stimulation (DBS) device. Our approach combines a multiplexed CNF electrode chip, developed at NASA Ames Research Center, with the Wireless Instantaneous Neurotransmitter Concentration Sensor (WINCS) system, developed at the Mayo Clinic. Preliminary results indicate that the CNF nanoelectrode arrays are easily integrated with WINCS for neurotransmitter detection in a multiplexed array format. In the future, combining CNF based stimulating and recording electrodes with WINCS may lay the foundation for an implantable smart therapeutic system that utilizes neurochemical feedback control while likely resulting in increased DBS application in various neuropsychiatric disorders. In total, our goal is to take advantage of the nanostructure of CNF arrays for biosensing studies requiring ultrahigh sensitivity, high-degree of miniaturization, and selective biofunctionalization.

Koehne, Jessica E.↗
DOE OSTI2024

SMART – A Comprehensive Research and Development Program to Demonstrate Application of Machine Learning for Supporting CCS Deployment

The objective of the US Department of Energy’s SMART Initiative, i.e., Science-informed Machine Learning (ML) for Accelerating Real-Time Decisions in Subsurface Applications, is to showcase how the utilization of ML can significantly improve efficiency and effectiveness of field-scale commercial carbon storage operations. This paper will present the results from the current phase of SMART (field deployment) for demonstrating the applicability of ML-based tools and workflows for: (a) virtual learning during the pre-injection permitting phase, (b) advanced storage reservoir imaging to better characterize fractures and faults, and (c) dynamic storage reservoir modelling and optimization to inform operational decision making and visualization of system evolution.

Siriwardane, Hema↗
DOE OSTI2021

Method for sealing a void in a well using a smart gel sealant

Embodiments of the disclosure include swellable smart gel sealants. In certain embodiments, the smart gel sealants reversibly swell when exposed to a certain trigger, such as temperature or pH. In specific embodiments, the smart gel is disposed within voids in a well and triggered to swell in order to seal the voids. One application of the smart gel sealant is to seal the casing of a well against the leakage of gas, such as CO2.

Goodman, Harvey Edwin↗
DOE OSTI2022

Method for sealing a void in a well using smart gels

Embodiments of the disclosure include swellable smart gel sealants and methods of using smart gel sealants. In certain embodiments, the smart gel sealants reversibly swell when exposed to a certain trigger, such as temperature or pH. In specific embodiments, the smart gel is disposed within voids in a well and triggered to swell in order to seal the voids. One application of the smart gel sealant is to seal the casing of a well against the leakage of gas, such as H2S.

Roback, Robert Clifford↗
NASA NTRS2000

Smart Microsystems with Photonic Element and Their Applications to Aerospace Platforms

The need to make manufacturing, operation, and support of airborne vehicles safer and more efficient forces engineers and scientists to look for lighter, cheaper, more reliable technologies. Light weight, immunity to EMI, fire safety, high bandwidth, and high signal fidelity have already made photonics in general and fiber optics in particular an extremely attractive medium for communication purposes. With the fiber optics serving as a central nervous system of the vehicle, generation, detection, and processing of the signal occurs at the peripherals that include smart structures and devices. Due to their interdisciplinary nature, photonic technologies cover such diverse areas as optical sensors and actuators, embedded and distributed sensors, sensing schemes and architectures, harnesses and connectors, signal processing and algorithms. The paper includes a brief description of work in the photonic area that is going on at NASA, especially at the Glenn Research Center (GRC).

Adamovsky, G.↗
NASA NTRS2003

Methods for Determining the Level of Autonomy to Design into a Human Spaceflight Vehicle: A Function Specific Approach

The next-generation human spaceflight vehicle is in a unique position to realize the benefits of more than thirty years of technological advancements since the Space Shuttle was designed. Computer enhancements, the emergence of highly reliable decision-making algorithms, and an emphasis on efficiency make an increased use of autonomous systems highly likely. NASA is in a position to take advantage of these advances and apply them to the human spaceflight environment. One of the key paradigm shifts will be the shift, where appropriate, of monitoring, option development, decision-making, and execution responsibility from humans to an Autonomous Flight Management (AFM) system. As an effort to reduce risk for development of an AFM system, NASA engineers are developing a prototype to prove the utility of previously untested autonomy concepts. This prototype, called SMART (Spacecraft Mission Assessment and Replanning Tool), is a functionally decomposed flight management system with an appropriate level of autonomy for each of its functions. As the development of SMART began, the most important and most often asked question was, How autonomous should an AFM system be? A thorough study of the literature through 2002 surrounding autonomous systems has not yielded a standard method for designing a level of autonomy into either a crewed vehicle or an uncrewed vehicle. The current focus in the literature on defining autonomy is centered on developing IQ tests for built systems. The literature that was analyzed assumes that the goal of all systems is to strive for complete autonomy from human intervention, rather than identifying how autonomous each function within the system should have been. In contrast, the SMART team developed a method for determining the appropriate level of autonomy to be designed into each function within a system. This paper summarizes the development of the Level of Autonomy Assessment Tool and its application to the SMART project.

AFM (AUTONOMOUS FLIGHT MANAGEMENT)↗
DOE OSTI2024

SMART – A Comprehensive Research and Development Program to Demonstrate Application of Machine Learning for Supporting CCS Deployment

Presentation material for a paper presented at the GHGT-17 conference, Calgary, Canada, October 20-24, 2024. The objective of the US Department of Energy’s SMART Initiative, i.e., Science-informed Machine Learning (ML) for Accelerating Real-Time Decisions in Subsurface Applications, is to showcase how the utilization of ML can significantly improve efficiency and effectiveness of field-scale commercial carbon storage operations. This paper will present the results from the current phase of SMART (field deployment) for demonstrating the applicability of ML-based tools and workflows for: (a) virtual learning during the pre-injection permitting phase, (b) advanced storage reservoir imaging to better characterize fractures and faults, and (c) dynamic storage reservoir modelling and optimization to inform operational decision making and visualization of system evolution.

CO2 geologic storage↗
DOE OSTI2021

Resilient Information Architecture Platform for Smart Grid (RIAPS)

A number of emerging trends will substantially alter the operation and control of the electric grid over the next several decades. These trends include ensuring resiliency under severe weather events, increasing integration of renewable electricity generation, supporting changing electricity demand patterns, and the improving cost effectiveness of distributed energy resources. To address these challenges, the future “Smart Grid” management will need to transition from centralized to coordinated distributed control paradigm. Reliable operation of the Smart Grid depends on distributed intelligence realized through software applications that run on distributed computing devices attached to the power system to collect data and collaboratively manage resources. However, much of the existing software for Smart Grid-enabled devices is either proprietary or developed with custom solutions, which limits interoperability among the heterogeneous devices and hinders the ability to manage system-level reliability, security, and resiliency requirements. Additionally, this approach makes Smart Grid applications hard to maintain, evolve, verify, and replace; resulting in high development and deployment costs. Further development of the Smart Grid requires a reusable software base-layer to move from hard-coded functionality to a plug-and-play architecture capable of managing system-level objectives and constraints in addition to providing consistent common services across heterogeneous devices and applications. Vanderbilt University, in collaboration with North Carolina State University and Washington State University has developed a foundation ‘software platform’ for developing and deploying robust, reliable, effective and secure software applications for the Smart Grid. The Resilient Information Architecture Platform for the Smart Grid (RIAPS) provides core services for building effective and powerful smart grid applications. It offers unique services for real-time data dissemination, fault tolerance, and coordination across apps distributed over the network.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2009

Proof Compression and the Mobius PCC Architecture for Embedded Devices

The EU Mobius project has been concerned with the security of Java applications, and of mobile devices such as smart phones that execute such applications. In this talk, I'll give a brief overview of the results obtained on on-device checking of various security-related program properties. I'll then describe in more detail how the concept of certified abstract interpretation and abstraction-carrying code can be applied to polyhedral-based analysis of Java byte code in order to verify properties pertaining to the usage of resources of a down-loaded application. Particular emphasis has been on finding ways of reducing the size of the certificates that accompany a piece of code.

Jensen, Thomas↗
NASA NTRS2005

Deformation Measurements of Smart Aerodynamic Surfaces

Video Model Deformation (VMD) and Projection Moire Interferometry (PMI) were used to acquire wind tunnel model deformation measurements of the Northrop Grumman-built Smart Wing tested in the NASA Langley Transonic Dynamics Tunnel. The F18-E/F planform Smart Wing was outfitted with embedded shape memory alloys to actuate a seamless trailing edge aileron and flap, and an embedded torque tube to generate wing twist. The VMD system was used to obtain highly accurate deformation measurements at three spanwise locations along the main body of the wing, and at spanwise locations on the flap and aileron. The PMI system was used to obtain full-field wing shape and deformation measurements over the entire wing lower surface. Although less accurate than the VMD system, the PMI system revealed deformations occurring between VMD target rows indistinguishable by VMD. This paper presents the VMD and PMI techniques and discusses their application in the Smart Wing test.

Fleming, Gary A.↗
DOE OSTI2020

Autonomously Responsive Membranes for Chemical Warfare Protection

Stimuli-responsive materials offer new opportunities to resolve long-standing material challenges and are rapidly gaining pivotal roles in diverse applications. For example, smart protective garments that rapidly transport water vapor and autonomously block chemical threats are expected to enable an effective new paradigm of adaptive personal protection. However, the incorporation of these seemingly incompatible properties into a single responsive system remains elusive. Herein, a bistable membrane that can rapidly, selectively, and reversibly transition from a highly breathable state in a safe environment to a chemically protective state when exposed to organophosphate threats such as sarin is demonstrated. Dynamic response to chemical stimuli is achieved through the physical collapse of an ultrathin copolymer layer on the membrane surface, which efficiently gates transport through membrane pores composed of single-walled carbon nanotubes (SWNTs). The adoption of nanometer-wide SWNTs for ultrafast moisture conduction enables a simultaneous boost in size-sieving selectivity and water-vapor permeability by decreasing nanotube diameter, thereby overcoming the breathability/protection trade-off that limits conventional membrane materials. Adaptive multifunctional membranes based on this platform greatly extend the active use of a protective garment and present exciting opportunities in many other areas including separation processes, sensing, and smart delivery.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Autonomous Changes in Polymer Materials Driven by Chemical Fuels

Time-dependent properties in polymer materials can be achieved through coupling to out-of-equilibrium chemical fuel reactions that mimic biological processes. Through transient changes in bonding in polymers, transient gelation, changes in mechanical stiffness, swelling, self-healing, or self-assembly can be achieved. Recent advances in these categories are discussed. These out-of-equilibrium behaviors enable applications ranging from smart adhesives to actuators for soft robotics. However, challenges remain, including waste accumulation, bio-compatibility, and achieving functionally useful performance. Addressing these issues is essential for advancing the practical use of chemically driven polymer materials and unlocking their full potential for future technologies.

36 MATERIALS SCIENCE↗