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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Optimal sensor network design for multi-scale, time-varying differential algebraic equation systems: Application to an entrained-flow gasifier refractory brick

An algorithm for optimal sensor network design for multi-scale, time-varying differential algebraic equation systems with non-separable dynamics is presented. As the process is time-varying, an integral normalized posterior error covariance of a multi-scale filter is minimized to obtain the optimal sensor locations. For reducing the computational cost, an adaptive sampling rate approach is considered for the slowly-varying variables. The algorithm is applied to a smart refractory brick with embedded sensors as part of an entrained-flow gasifier. Thermistors and interdigital capacitors are considered as candidate measurement technologies for estimating temperature and slag penetration profile along the gasifier wall. Finally, when the optimal set of sensors obtained from the algorithm is used for estimating temperature and slag penetration profiles in a multi-scale Kalman filter framework, satisfactory estimates are obtained despite high measurement noise and model mismatch.

42 ENGINEERING↗
NASA NTRS1994

Discrete-Layer Piezoelectric Plate and Shell Models for Active Tip-Clearance Control

The objectives of this work were to develop computational tools for the analysis of active-sensory composite structures with added or embedded piezoelectric layers. The targeted application for this class of smart composite laminates and the analytical development is the accomplishment of active tip-clearance control in turbomachinery components. Two distinct theories and analytical models were developed and explored under this contract: (1) a discrete-layer plate theory and corresponding computational models, and (2) a three dimensional general discrete-layer element generated in curvilinear coordinates for modeling laminated composite piezoelectric shells. Both models were developed from the complete electromechanical constitutive relations of piezoelectric materials, and incorporate both displacements and potentials as state variables. This report describes the development and results of these models. The discrete-layer theories imply that the displacement field and electrostatic potential through-the-thickness of the laminate are described over an individual layer rather than as a smeared function over the thickness of the entire plate or shell thickness. This is especially crucial for composites with embedded piezoelectric layers, as the actuating and sensing elements within these layers are poorly represented by effective or smeared properties. Linear Lagrange interpolation polynomials were used to describe the through-thickness laminate behavior. Both analytic and finite element approximations were used in the plane or surface of the structure. In this context, theoretical developments are presented for the discrete-layer plate theory, the discrete-layer shell theory, and the formulation of an exact solution for simply-supported piezoelectric plates. Finally, evaluations and results from a number of separate examples are presented for the static and dynamic analysis of the plate geometry. Comparisons between the different approaches are provided when possible, and initial conclusions regarding the accuracy and limitations of these models are given.

Heyliger, P. R.↗
NASA NTRS2022

Radiation Tolerance and Mitigation for Neuromorphic Processors

Neuromorphic processors are designed to execute Deep Neural Networks (DNNs) at very high speed using only a fraction of the electrical power needed to run a DNN on a traditional CPU or GPU. This unique capability makes Neuromorphic processors a prime candidate for space systems, where advanced computational tasks like image analysis, depth map reconstruction, or rover control need to be executed in a power-starved environment. In contrast to the growing number of applications of Neuromorphic processors in smart phones, the automotive and robotics domain, the space environment is unforgiving because of extreme temperatures and high levels of radiation. Any space system, operating beyond LEO requires computing hardware that is resilient against radiation effects. However, Neuromorphic processors have not yet been designed or tested for their radiation tolerance. In this report, we consider traditional methods of detection of radiation events and mitigation via redundancy and gauge their effectiveness on DNNs. In contrast to traditional flight software, however, neural networks represent a statistical algorithm, which might affect its resilience against radiation events. We will focus on the analysis of the tolerance of DNNs with respect to radiation events and discuss techniques to detect radiation hits using on-chip triple modular redundancy (TMR) on an Intel Loihi neuromorphic processor and to mitigate radiation damage. We describe an architecture for on-chip TMR for the Intel Loihi and present results of initial experiments.

Neural Networks↗
DOE OSTI2024

A Perspective on Scalable AI on High-Performance Computing and Leadership Class Supercomputing Facilities [Industrial and Governmental Activities]

Many scientific applications that support the mission of the US Department of Energy (US-DoE) require modeling complex engineering and/or physical systems. Here, examples of such complex systems arise from: (a) materials science to develop new compounds with exceptional mechanical and thermodynamical properties (e.g., resistance to mechanical stresses and high temperatures), (b) structural and nuclear engineering to model the temporal evolution of the structural damage of concrete shields exposed to continuous neutron and gamma radiations emitted by the nuclear reactor core, (c) urban sciences (e.g., transportation and smart buildings), and (d) power grid systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

SmartFuse: Reconfigurable Smart Switches to Accelerate Fused Collectives in HPC Applications

Communication switches have sometimes been augmented to process collectives (e.g., the IBM BlueGene project and the Mellanox SHArP switch). In this work, we find that there is a great acceleration opportunity through the further augmentation of switches to accelerate more complex functions that combine communication with computation. We consider three types of such functions. The first is fully-fused collectives built by fusing multiple existing collectives like Allreduce with Alltoall. The second is semi-fused collectives built by combining a collective with another computation. The third we refer to as higher-order collectives built by combining multiple computations and communications, such as to perform matrix-matrix multiply (PGEMM). In this work, we propose a framework called SmartFuse to accelerate fused collective functions. The core of SmartFuse is a reconfigurable smart switch to support these operations. The semi/fully fused collectives are implemented with a CGRAlike architecture, while higher-order collectives are implemented with a more specialized computational unit that can also schedule communication. Supporting our framework is software to evaluate and translate relevant parts of the input program, compile them into a control data flow graph, and then map this graph to the switch hardware. The proposed framework, once deployed, has the strong potential to accelerate existing HPC applications transparently by encapsulation within an MPI implementation. Experimental results show that this approach improves the performance of the PGEMM kernel, MINIFE, and AMG by, on average, 94%, 15%, and 13%, respectively.

Haghi, Pouya↗
DOE OSTI2019

Solar-Forecast GridAPPS-D Application [SWR-18-36]

Persistent model serves as the baseline in the intra-hour forecasting of solar radiation due to the extensive computing efforts from the numerical weather prediction (NWP) models and the lack of surface observations in cloud as well as other atmospheric properties. The smart persistent model actively updates the extraterrestrial solar radiation with time and is an important improvement from the persistent model while the cloud conditions are assumed unchanged by giving constant clear-sky indexes. We developed a Physics-based Smart Persistent model for Intra-hour solar forecasting (PSPI) to further improve the accuracy of the smart persistent model. We used a cloud retrieval technique developed by Xie and Liu (2013) to estimate cloudy fraction and cloud albedo using surface-based observations of solar radiation. The solar radiation in future time steps is accurately given by actively computing individual cloud albedo related to the future solar position. Our evaluation studies indicated that the PSPI model significantly increased the accuracy in the short-term forecast of solar radiation, especially in thin cloud conditions or those covered by broken clouds.

Xie, Yu↗
DOE OSTI2024

Privacy by Design in Distributed Edge Systems: Innovating Secure Workflows for Smart Cities

The proliferation of distributed edge systems, such as those in smart cities, healthcare, and industrial IoT, offers unprecedented opportunities for data processing closer to its source, thereby reducing latency and enhancing efficiency. However, these systems also present significant privacy challenges due to the handling of sensitive data from multiple sources. This article explores the critical need for designing privacy-preserving workflows in distributed edge systems to ensure data security while maximizing the potential of edge computing. By examining the challenges, technological advancements, and potential of privacy-by-design approaches, we highlight the importance of integrating advanced privacy-preserving techniques like federated learning, differential privacy, homomorphic encryption, secure multi-party computation, and zero-knowledge proofs. These innovations are crucial for enhancing data security, regulatory compliance, and public trust in smart city applications, ultimately leading to safer and more efficient urban environments.

Kotevska, Olivera↗
NASA NTRS1993

Quantification of uncertainties in the performance of smart composite structures

A composite wing with spars, bulkheads, and built-in control devices is evaluated using a method for the probabilistic assessment of smart composite structures. Structural responses (such as change in angle of attack, vertical displacements, and stresses in regular plies with traditional materials and in control plies with mixed traditional and actuation materials) are probabilistically assessed to quantify their respective scatter. Probabilistic sensitivity factors are computed to identify those parameters that have a significant influence on a specific structural response. Results show that the uncertainties in the responses of smart composite structures can be quantified. Responses such as structural deformation, ply stresses, frequencies, and buckling loads in the presence of defects can be reliably controlled to satisfy specified design requirements.

Shiao, Michael C.↗
NASA NTRS1987

Computer hardware and software for robotic control

The KSC has implemented an integrated system that coordinates state-of-the-art robotic subsystems. It is a sensor based real-time robotic control system performing operations beyond the capability of an off-the-shelf robot. The integrated system provides real-time closed loop adaptive path control of position and orientation of all six axes of a large robot; enables the implementation of a highly configurable, expandable testbed for sensor system development; and makes several smart distributed control subsystems (robot arm controller, process controller, graphics display, and vision tracking) appear as intelligent peripherals to a supervisory computer coordinating the overall systems.

Davis, Virgil Leon↗
DOE OSTI2019

REALIZATION OF A AUTOMATED T-WAY COMBINATORIAL TESTING APPROACH FOR A SOFTWARE BASED EMBEDDED DIGITAL DEVICE

Under the Department of Energy’s Light Water Reactor Sustainability Program, within the Plant Modernization research pathway, the Digital I&C Qualification Project is identifying new methods that would be beneficial in qualifying digital I&C systems and devices for safety-related usage. One such method that would be useful in qualifying field components such as sensors and actuators is the concept of testability. The Nuclear Regulatory Commission (NRC) considers testability to be one of two design attributes sufficient to eliminate consideration of software-based or software logic-based common cause failure (the other being diversity). The NRC defines acceptable “testability” as follows: Testability – A system is sufficiently simple such that every possible combination of inputs and every possible sequence of device states are tested and all outputs are verified for every case (100% tested). [NUREG 0800, Chapter 7, Branch Technical Position (BTP) 7-19] This qualification method has never proven to be practical in view of the very large number of combinations of inputs and sequences of device states for a typical I&C device. However, many of these combinations are not unique in the sense that they represent the same state space or in that that they represent state space that would not affect the critical design basis functions of the device. Therefore, the state space of interest might possibly be reduced to a manageable dimension through such analysis. This project will focus on a representative I&C device similar in design, function, and complexity to the types of devices that would likely be deployed in nuclear power plants as digital or software based sensors and actuators (e.g. Smart Sensors). Analysis will be conducted to determine the feasibility of testing this device in a manner consistent with the NRC definition. This report describes the development of test process for Bounded Exhaustive Testing with respect to Combinatorial Test (CT) methods. The report describes the candidate Device Under Test SW – the VCU smart sensor, conceptual experimental methods for stated test objectives, description of the process, tools, resources, and computing. This information will be used to fully develop a detailed test plan (based on statistical measure needs) and test environment for conducting an I&C device testability demonstration study. The future planed experimental study of this project is to demonstrate digital qualification via Bounded Exhaustive Testability with respect to Common Cause Failure.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Measuring Cities with Software-Defined Sensors

The Chicago Array of Things (AoT) project, funded by the US National Science Foundation, created an experimental, urban-scale measurement capability to support diverse scientific studies. Initially conceived as a traditional sensor network, collaborations with many science communities guided the project to design a system that is remotely programmable to implement Artificial Intelligence (AI) within the devices-at the “edge” of the network-as a means for measuring urban factors that heretofore had only been possible with human observers, such as human behavior including social interaction. The concept of “software-defined sensors” emerged from these design discussions, opening new possibilities, such as stronger privacy protections and autonomous, adaptive measurements triggered by events or conditions. We provide examples of current and planned social and behavioral science investigations uniquely enabled by software-defined sensors as part of the SAGE project, an expanded follow-on effort that includes AoT.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2007

An IEEE 1451.1 Architecture for ISHM Applications

The IEEE 1451.1 Standard for a Smart Transducer Interface defines a common network information model for connecting and managing smart elements in control and data acquisition networks using network-capable application processors (NCAPs). The Standard is a network-neutral design model that is easily ported across operating systems and physical networks for implementing complex acquisition and control applications by simply plugging in the appropriate network level drivers. To simplify configuration and tracking of transducer and actuator details, the family of 1451 standards defines a Transducer Electronic Data Sheet (TEDS) that is associated with each physical element. The TEDS contains all of the pertinent information about the physical operations of a transducer (such as operating regions, calibration tables, and manufacturer information), which the NCAP uses to configure the system to support a specific transducer. The Integrated Systems Health Management (ISHM) group at NASA's John C. Stennis Space Center (SSC) has been developing an ISHM architecture that utilizes IEEE 1451.1 as the primary configuration and data acquisition mechanism for managing and collecting information from a network of distributed intelligent sensing elements. This work has involved collaboration with other NASA centers, universities and aerospace industries to develop IEEE 1451.1 compliant sensors and interfaces tailored to support health assessment of complex systems. This paper and presentation describe the development and implementation of an interface for the configuration, management and communication of data, information and knowledge generated by a distributed system of IEEE 1451.1 intelligent elements monitoring a rocket engine test system. In this context, an intelligent element is defined as one incorporating support for the IEEE 1451.x standards and additional ISHM functions. Our implementation supports real-time collection of both measurement data (raw ADC counts and converted engineering units) and health statistics produced by each intelligent element. The handling of configuration, calibration and health information is automated by using the TEDS in combination with other electronic data sheets extensions to convey health parameters. By integrating the IEEE 1451.1 Standard for a Smart Transducer Interface with ISHM technologies, each element within a complex system becomes a highly flexible computation engine capable of self-validation and performing other measures of the quality of information it is producing.

Morris, Jon A.↗
NASA NTRS2010

Statistical Attitude Determination

All spacecraft require attitude determination at some level of accuracy. This can be a very coarse requirement of tens of degrees, in order to point solar arrays at the sun, or a very fine requirement in the milliarcsecond range, as required by Hubble Space Telescope. A toolbox of attitude determination methods, applicable across this wide range, has been developed over the years. There have been many advances in the thirty years since the publication of Reference, but the fundamentals remain the same. One significant change is that onboard attitude determination has largely superseded ground-based attitude determination, due to the greatly increased power of onboard computers. The availability of relatively inexpensive radiation-hardened microprocessors has led to the development of "smart" sensors, with autonomous star trackers being the first spacecraft application. Another new development is attitude determination using interferometry of radio signals from the Global Positioning System (GPS) constellation. This article reviews both the classic material and these newer developments at approximately the level of, with emphasis on. methods suitable for use onboard a spacecraft. We discuss both "single frame" methods that are based on measurements taken at a single point in time, and sequential methods that use information about spacecraft dynamics to combine the information from a time series of measurements.

Markley, F. Landis↗
DOE OSTI2023

Smart Pixels: towards on-sensor inference of charged particle track parameters and uncertainties

The combinatorics of track seeding has long been a computational bottleneck for triggering and offline computing in High Energy Physics (HEP), and remains so for the HL-LHC. Next-generation pixel sensors will be sufficiently fine-grained to determine angular information of the charged particle passing through from pixel-cluster properties. This detector technology immediately improves the situation for offline tracking, but any major improvements in physics reach are unrealized since they are dominated by lowest-level hardware trigger acceptance. We will demonstrate track angle and hit position prediction, including errors, using a mixture density network within a single layer of silicon as well as the progress towards and status of implementing the neural network in hardware on both FPGAs and ASICs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Smart Pixels: towards on-sensor inference of charged particle track parameters and uncertainties

The combinatorics of track seeding has long been a computational bottleneck for triggering and offline computing in High Energy Physics (HEP), and remains so for the HL-LHC. Next-generation pixel sensors will be sufficiently fine-grained to determine angular information of the charged particle passing through from pixel-cluster properties. This detector technology immediately improves the situation for offline tracking, but any major improvements in physics reach are unrealized since they are dominated by lowest-level hardware trigger acceptance. We will demonstrate track angle and hit position prediction, including errors, using a mixture density network within a single layer of silicon as well as the progress towards and status of implementing the neural network in hardware on both FPGAs and ASICs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

A VSM-Based DER Dispatch MINLP for Volt-VAR Control in Unbalanced Power Distribution Systems

This paper presents an optimal dispatch algorithm to coordinate customer-owned controllable loads and smart solar inverters with utility-owned voltage regulators and capacitors to meet voltage control objectives. The optimization problem is formulated as a mixed-integer nonlinear programming (MINLP) problem. A voltage sensitivity matrix (VSM) is used to linearize the effect of control actions on the voltage at customer nodes when solving the MINLP. The VSM is recalculated at each time step to improve the computational accuracy. Both discrete switching actions of the capacitor and VRs and the continuous adjustment of real and reactive power from load and smart inverters are considered in the MINLP volt-var problem formulation. The objective function minimizes the cost of all control actions and the magnitude of voltage fluctuations from the previous time period. Constraints ensure that the voltage at each node is maintained within ANSI limits and the feeder power factor is controlled within the desired range. The algorithm is tested using an actual 3-phase unbalanced distribution feeder model. Simulation results demonstrate that the proposed algorithm is computationally feasible on real circuits and improves voltage control while minimizing operational costs.

McEntee, Catie↗