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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A comparative study on deep learning models for condition monitoring of advanced reactor piping systems

Advanced nuclear reactors offer innovative applications due to their portability, reliability, resiliency, and high capacity factors. To operate them on a wider scale, reducing maintenance life-cycle costs while ensuring their integrity is essential. Autonomous operations in advanced nuclear reactors using augmented Digital Twin (DT) technology can serve as a cost-effective solution by increasing awareness about the system’s health. A key component of nuclear DT frameworks is the condition monitoring of safety systems, such as piping-equipment systems, which involves acquiring and monitoring the plant’s sensor data. Here, this research proposes a condition monitoring methodology utilizing deep learning algorithms, such as multilayer perceptions (MLP) and convolutional neural networks (CNNs), to detect degradation and its severity in nuclear piping-equipment systems. Sensor signals are processed to obtain the power spectral density and the Short-Time Fourier transform, and feature extraction methodologies are proposed to develop degradation-sensitive data repositories. The performance of MLP, one-dimensional (1D) CNN, and 2D CNN within the proposed condition monitoring framework is compared using a finite element model of a 3D piping system subjected to seismic loads as the application case study. Various approaches, such as dropout, k-Fold validation, regularization, and early stopping of training the network, are investigated to avoid overfitting the models to the input sensor data. The predictive capability and computational capacity of the deep learning algorithms are also compared to detect degradation in the Z-pipe system of the Experimental Breeder Reactor II (EBRII). The Z-pipe system is subjected to harmonic excitations that represent normal operating loads, such as pump-induced vibrations. The findings of the study indicate that the proposed artificial intelligence (AI)-driven condition monitoring framework demonstrates superior prediction accuracies with a 2D CNN, whereas the MLP exhibits higher computational efficiency.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Distributed deep learning training using silicon photonic switched architectures

The scaling trends of deep learning models and distributed training workloads are challenging network capacities in today’s datacenters and high-performance computing (HPC) systems. We propose a system architecture that leverages silicon photonic (SiP) switch-enabled server regrouping using bandwidth steering to tackle the challenges and accelerate distributed deep learning training. In addition, our proposed system architecture utilizes a highly integrated operating system-based SiP switch control scheme to reduce implementation complexity. To demonstrate the feasibility of our proposal, we built an experimental testbed with a SiP switch-enabled reconfigurable fat tree topology and evaluated the network performance of distributed ring all-reduce and parameter server workloads. The experimental results show up to 3.6× improvements over the static non-reconfigurable fat tree. Our large-scale simulation results show that server regrouping can deliver up to 2.3× flow throughput improvement for a 2× tapered fat tree and a further 11% improvement when higher-layer bandwidth steering is employed. The collective results show the potential of integrating SiP switches into datacenters and HPC systems to accelerate distributed deep learning training.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

A Tailored Convolutional Neural Network for Nonlinear Manifold Learning of Computational Physics Data Using Unstructured Spatial Discretizations

In this work, we propose a nonlinear manifold learning technique based on deep convolutional autoencoders that is appropriate for model order reduction of physical systems in complex geometries. Convolutional neural networks have proven to be highly advantageous for compressing data arising from systems demonstrating a slow-decaying Kolmogorov n-width. However, these networks are restricted to data on structured meshes. Unstructured meshes are often required for performing analyses of real systems with complex geometry. Our custom graph convolution operators based on the available differential operators for a given spatial discretization effectively extend the application space of deep convolutional autoencoders to systems with arbitrarily complex geometry that are typically discretized using unstructured meshes. We propose sets of convolution operators based on the spatial derivative operators for the underlying spatial discretization, making the method particularly well suited to data arising from the solution of partial differential equations. We demonstrate the method using examples from heat transfer and fluid mechanics and show better than an order of magnitude improvement in accuracy over linear methods.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2006

The Deep Space Network Array

This document is a viewgraph presentation that reviews the costs, and technological processing required to replace the current network of Deep Space Antennas. The concept of using an array for space communications is much less of a concern than the cost of implementing and operating such an array. Within the cost question, the cost uncertainty of the front-end components (repeated n-times) is of most importance. The activities at JPL have focused on both these aspects of the cost. A breadboard array of three antennas at JPL has been the vehicle to perform many investigations into the development of the new DSN. Several pictures of the antennas at JPL are shown.

Deep Space Network (DSN)↗
DOE OSTI2019

SDN-NGenIA, a Software Defined Next Generation Integrated Architecture for HEP and Data Intensive Science

This project aims to enable the LHC and other leading programs in high energy physics and other global science domains funded by the DOE to operate with a new level of efficiency and control, through the development of a Next Generation Integrated Architecture (NGenIA) based on intelligent software defined network (SDN)-driven network systems coupled to high throughput applications. While the initial focus is on the challenging LHC use case, the systems and products being developed are general, and apply to many fields of data intensive science ranging from astrophysical sky surveys to bioinformatics and earth observation, as well as other organizations facing the challenges of extracting knowledge from distributed multi-petabyte data stores. A central concept in this development program is a new paradigm ‘consistent network operations’ among widely distributed computing and storage facilities, where stable high throughput flows, at set rates, cross load-balanced network paths, up to flexible high water marks that are adjusted in real time to accommodate other network traffic. The large smooth flows are launched and managed by SDN services that act in concert with the experiments’ site-resident data distribution and management systems, to meet the expanding needs of the science programs. The technical goals include the construction of autonomous, intelligent site-resident services that interact dynamically with network-resident services, and with the science programs’ principal data distribution and management tools, to request or command network resources in support of high throughput petascale to exascale workflow Specific work items include: 1. Developing compact Data Transfer Nodes (DTNs) with auto-tuning functions that support data transfer rates in the 100 Gbps to the 1 Tbps range when used with high throughput data transfer applications 2. Deep site orchestration among virtualized clusters, storage subsystems and subnets to successfully coschedule CPU, storage and network resources 3. Science-program designed site architectures, operational modes, and policy and resource usage priorities, adjudicated across multiple network domains and virtual organizations, using the orchestration functions and methods 4. Seamlessly extending end-to-end operation across both extra-site and intra-site boundaries through the use of Open vSwitch (OVS), FireQoS + next generation Science DMZs 5. Novel methods of system integration that enable granular control of extreme scale long distance transfers through flow matching of scattered source-destination address pairs to multi-domain dynamic circuits 6. Funneling massive sets of streams to DTNs at the site edge hosting petascale buffer pools configured for flows of 100 Gbps and up, exploiting state of the art data transfers 7. Adaptive scheduling based on pervasive end-to-end monitoring, including DTN or compute-node resident agents providing comprehensive end-system profiling 8. Developing unsupervised and supervised machine learning and modeling methods to optimize the workflow involving terabyte to multi-petabyte datasets.

47 OTHER INSTRUMENTATION↗
NASA NTRS1991

Challenges for deep space communications in the 1990s

The discussion of NASA's Deep Space Network (DSN) examines the evolving character of aerospace missions and the corresponding changes in the DSN architecture. Deep space missions are reviewed, and it is noted that the two 34-m and the 70-m antenna subnets of the DSN are heavily loaded and more use is expected. High operational workload and the challenge of network cross-support are the design drivers for a flexible DSN architecture configuration. Incorporated in the design are antenna arraying for aperture augmentation, beam-waveguide antennas for frequency agility, and connectivity with non-DSN sites for cross-support. Compatibility between spacecraft and ground-facility designs is important for establishing common international standards of communication and data-system specification.

Dumas, Larry N.↗
DOE OSTI2023

Physics-informed neural network with transfer learning (TL-PINN) based on domain similarity measure for prediction of nuclear reactor transients

Nuclear reactor safety and efficiency can be enhanced through the development of accurate and fast methods for prediction of reactor transient (RT) states. Physics informed neural networks (PINNs) leverage deep learning methods to provide an alternative approach to RT modeling. Applications of PINNs in monitoring of RTs for operator support requires near real-time model performance. However, as with all machine learning models, development of a PINN involves time-consuming model training. Here, we show that a transfer learning (TL-PINN) approach achieves significant performance gain, as measured by reduction of the number of iterations for model training. Using point kinetic equations (PKEs) model with six neutron precursor groups, constructed with experimental parameters of the Purdue University Reactor One (PUR-1) research reactor, we generated different RTs with experimentally relevant range of variables. The RTs were characterized using Hausdorff and Fréchet distance. We have demonstrated that pre-training TL-PINN on one RT results in up to two orders of magnitude acceleration in prediction of a different RT. The mean error for conventional PINN and TL-PINN models prediction of neutron densities is smaller than 1%. We have developed a correlation between TL-PINN performance acceleration and similarity measure of RTs, which can be used as a guide for application of TL-PINNs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1973

The deep space network, volume 14

DSN progress during Jan. and Feb. 1973 is reported. Areas of accomplishment include: flight project support, TDA research and technology, network engineering, hardware and software implementation, and operations.

Source record↗
NASA NTRS1983

The Telecommunications and Data Acquisition Report

Archival reports on developments in programs managed by JPL's office of Telecommunications and Data Acquisition (TDA) are presented. In space communications, radio navigation, radio science, and ground-based radio astronomy, it reports on activities of the Deep Space Network (DSN) and its associated Ground Communications Facility (GCF) in planning, in supporting research and technology, in implementation, and in operations.

E. C. Posner↗
NASA NTRS1983

The Telecommunications and Data Acquisition Report

This publication reports on developments in programs managed by JPL's office of Telecommunications and Data Acquisition (TDA). In space communications, radio navigation, radio science, and ground based radio astronomy, it reports on activities of the Deep Space Network (DSN) and its associated Ground Communications Facility (GCF) in planning, in supporting research and technology, in implementation and in operations. In geodynamics, the publication reports on the application of radio interferometry at microwave frequencies for geodynamic measurements. This publication also reports on implementation and operations for searching the microwave spectrum.

Posner, E. C.↗
NASA NTRS1985

The Telecommunications and Data Acquisition Report

Deep Space Network (DSN) progress in flight project support, tracking and data acquisition research and technology, network engineering, hardware and software implementation, and operation is discussed. In addition, developments in Earth-based radio technology as applied to geodynamics, astrophysics and the radio search for extraterrestrial intelligence are reported.

Posner, E. C.↗
NASA NTRS1986

The Telecommunications and Data Acquisition Report

This quarterly publication (July-Sept. 1986) provides archival reports on developments in programs managed by JPL's Office of Telecommunications and Data Acquisition (TDA). In space communications, radio navigation, radio science, and ground-based radio astronomy, it reports on activities of the Deep Space Network (DSN) and its associated Ground Communications Facility (GCF) in planning, in supporting research and technology, in implementation, and in operations. This work is performed for NASA's Office of Space Tracking and Data Systems (OSTDS). In geodynamics, the publication reports on the application of radio interferometry at microwave frequencies for geodynamic measurements. In the search for extraterrestrial intelligence (SETI), it reports on implementation and operations for searching the microwave spectrum. The latter two programs are performed for NASA's Office of Space Science and Applications (OSSA).

Posner, E. C.↗
NASA NTRS1987

The Telecommunications and Data Acquisition Report

This quarterly publication (July-September 1987) provides archival reports on developments in programs managed by JPL's Office of Telecommunications and Data Acquisition (TDA). In space communications, radio navigation, radio science, and ground-based radio astronomy, it reports on activities of the Deep Space Network (DSN) and its associated Ground Communications Facility (GCF) in planning, in supporting research and technology, in implementation, and in operations. This work is performed for NASA's Office of Space Tracking and Data Systems (OSTDS). In geodynamics, the publication reports on the application of radio interferometry at microwave frequencies for geodynamic measurements. In the Search for Extraterrestrial Intelligence (SETI), it reports on implementation and operations for searching the microwave spectrum. The latter two programs are performed for NASA's Office of Space Science and Applications (OSSA).

Posner, E. C.↗
NASA NTRS2008

The NASA Phoenix 2007 Mars Lander Thruster Calibration Estimator: Design and Validation

The NASA Phoenix 2007 Mars Lander mission, launched in August 2007 on its mission to land near the north pole of Mars in May 2008, had a driving need for entry-corridor delivery precision, which parlayed into stringent requirements on deep space navigation accuracy. This, in turn, necessitated in-cruise calibration of the three-axis thrust force vectors produced by each of the vehicle's four reactioncontrol system (RCS) thrusters during frequent daily low-catalyst-bed-temperature firings done to maintain the 3-axis attitude deadbands. A novel recursive sigmapoint consider-covariance filter was designed, validated and ultimately utilized extensively during flight operations, to estimate the RCS force vectors, per individual thruster. The estimate was achieved through ground-based processing of Deep Space Network (DSN) and telemetered gyroscope data from the spacecraft's inertial measurement unit (IMU), using a novel sigma-point consider filter (SPCF) formulation. During early-cruise active calibration, the spacecraft was flown in attitudes chosen, using this filter, to maximize observability of all thruster axes, to an extent constrained by vehicle thermal and communication considerations. The design of the Phoenix thruster calibration filter, and its validation through processing of archived Mars Odyssey thruster calibration radiometric data, and simulated sets of data, are discussed in this paper. The paper concludes with the formulation of the thruster calibration campaign and a summary of the thruster calibration campaign results. The SPCF algorithm is summarized in the Appendix.

sigma-point filter↗
NASA NTRS2014

Design Concepts for a Small Space-Based GEO Relay Satellite for Missions Between Low Earth and near Earth Orbits

The main purpose of the Small Space-Based Geosynchronous Earth orbiting (GEO) satellite is to provide a space link to the user mission spacecraft for relaying data through ground networks to user Mission Control Centers. The Small Space Based Satellite (SSBS) will provide services comparable to those of a NASA Tracking Data Relay Satellite (TDRS) for the same type of links. The SSBS services will keep the user burden the same or lower than for TDRS and will support the same or higher data rates than those currently supported by TDRS. At present, TDRSS provides links and coverage below GEO; however, SSBS links and coverage capability to above GEO missions are being considered for the future, especially for Human Space Flight Missions (HSF). There is also a rising need for the capability to support high data rate links (exceeding 1 Gbps) for imaging applications. The communication payload on the SSBS will provide S/Ka-band single access links to the mission and a Ku-band link to the ground, with an optical communication payload as an option. To design the communication payload, various link budgets were analyzed and many possible operational scenarios examined. To reduce user burden, using a larger-sized antenna than is currently in use by TDRS was considered. Because of the SSBS design size, it was found that a SpaceX Falcon 9 rocket could deliver three SSBSs to GEO. This will greatly reduce the launch costs per satellite. Using electric propulsion was also evaluated versus using chemical propulsion; the power system size and time to orbit for various power systems were also considered. This paper will describe how the SSBS will meet future service requirements, concept of operations, and the design to meet NASA users' needs for below and above GEO missions. These users' needs not only address the observational mission requirements but also possible HSF missions to the year 2030. We will provide the trade-off analysis of the communication payload design in terms of the number of links looking above and below GEO; the detailed design of a GEO SSBS spacecraft bus and its accommodation of the communication payload, and a summary of the trade study that resulted in the selection of the Falcon 9 launch vehicle to deploy the SSBS and its impact on cost reductions per satellite. ======================================================================== Several initiatives have taken place within NASA1 and international space agencies2 to create a human exploration strategy for expanding human presence into the solar system; these initiatives have been driven by multiple factors to benefit Earth. Of the many elements in the strategy one stands out: to send robotic and human missions to destinations beyond Low Earth Orbit (LEO), including cis-lunar space, Near-Earth Asteroids (NEAs), the Moon, and Mars and its moons.3, 4 The time frame for human exploration to various destinations, based on the public information available,1,4 is shown in Figure 1. Advance planning is needed to define how future space communications services will be provided in the new budget environment to meet future space communications needs. The spacecraft for these missions can be dispersed anywhere from below LEO to beyond GEO, and to various destinations within the solar system. NASA's Space Communications and Navigation (SCaN) program office provides communication and tracking services to space missions during launch, in-orbit testing, and operation phases. Currently, SCaN's space networking relay satellites mainly provide services to users below GEO, at Near Earth Orbit (NEO), below LEO, and in deep space. The potential exists for using a space-based relay satellite, located in the vicinity of various solar system destinations, to provide communication space links to missions both below and above its orbit. Such relays can meet the needs of human exploration missions for maximum connectivity to Earth locations and for reduced latency. In the past, several studies assessed the ability of satellite-based relays working above GEO in conjunction with Earth ground stations. Many of these focused on the trade between space relay and direct-to-Earth station links5,6,7. Several others focused on top-level architecture based on relays at various destinations8,9,10,11,12. Much has changed in terms of microwave and optical technology since the publication of the referenced papers; Ka-band communication systems are being deployed, optical communication is being demonstrated, and spacecraft buses are becoming increasingly more functional and operational. A design concept study was undertaken to access the potential for deploying a Small Space-Based Satellite (SSBS) relay capable of serving missions between LEO and NEO. The needs of future human exploration missions were analyzed, and a notional relay-based architecture concept was generated as shown in Fig. 1. Relay satellites in Earth through cis-Lunar orbits are normally located in stable orbits requiring low fuel consumption. Relay satellites for Mars orbit are normally selected based on the mission requirement and projected fuel consumption. Relay satellites have extreme commonalities of functions between them, differing only in the redundancy and frequencies used; therefore, the relay satellite in GEO was selected for further analysis since it will be the first step in achieving a relay-based architecture for human exploration missions (see Fig.Figure 2). The mission design methodology developed by the Collaborative Modeling for Parametric Assessment of Space Systems (COMPASS) team13 was used to produce the satellite relay design and to perform various design trades. At the start of the activity, the team was provided with the detailed concept of the notional architecture and the system and communication payload drivers.

Relay Satellites↗
DOE OSTI2022

Reconfigurable Intelligent Surfaces in Action for Nonterrestrial Networks

Next-generation communication technology will be made possible by cooperation between terrestrial networks with nonterrestrial networks (NTNs) composed of high-altitude platform stations (HAPSs) and satellites. Further, as humanity embarks on the long road to establish new habitats on other planets, the cooperation between NTNs and deep-space networks (DSNs) will be necessary. In this regard, we propose the use of reconfigurable intelligent surfaces (RISs) to improve coordination between these networks given that RISs perfectly match the size, weight, and power (SWaP) restrictions of operating in space. Here, a comprehensive framework of RIS-assisted nonterrestrial and interplanetary communications is presented that pinpoints challenges, use cases, and open issues. Furthermore, the performance of RIS-assisted NTNs under environmental effects, such as solar scintillation and satellite drag, is discussed in light of simulation results.

42 ENGINEERING↗
DOE OSTI2020

Vehicle to Grid Frequency Regulation Capacity Optimal Scheduling for Battery Swapping Station Using Deep Q-Network

Battery swapping stations (BSSs) are ideal candidates for fast frequency regulation services (FFRS) due to their large battery stock capacity. In addition, BSSs can precharge batteries for customers and the batteries that are not in charging can provide a stable regulation capacity to the market. However, uncertainties, such as ACE signals and the EV per-hour visit counts, introduce stochastic nonlinear dynamics into the operation of a BSS-based FFRS. Currently, there is no quantification method to ensure its optimal economical operation. To close this gap, in this article, we propose a novel deep Q-learning-based FFRS capacity dynamic scheduling strategy. This method can autonomously schedule the hourly regulation capacity in real time to maximize the BSSx0027;s revenue for providing FFRS. Case studies using real-world data verify the efficacy of the proposed work.

25 ENERGY STORAGE↗
NASA NTRSDate not supplied

Optimizing Altitude Sampling and Sensitivity with the Goldstone Orbital Debris Radar

The NASA Orbital Debris Program Office (ODPO) has used the Goldstone Orbital Debris Radar (Goldstone) since 1993 to characterize orbital debris (OD) in low Earth orbit too small to be tracked by the U.S. Space Surveillance Network. Operated by NASA’s Jet Propulsion Laboratory, Goldstone can measure OD as small as 3 mm at 1000 km altitude and lower. Goldstone is a bistatic radar that for 25 years used Deep Space Station (DSS)-14 as a transmitter and DSS-15 as a receiver. In early 2018, DSS-15 was decommissioned and replaced with DSS-25 (and occasionally DSS-26) of the Deep Space Network Apollo Cluster. The increased baseline between DSS-14 and DSS-25 significantly reduced the instantaneous altitude coverage of the bistatic beam overlap. Initial measurements in 2018 were focused around 800 km, which has approximately the highest flux of sub-centimeter debris. In 2019, DSS-14 was offline for maintenance, and the ODPO designed an annual survey observation plan to efficiently sample altitudes from 700 km to 1000 km, since many NASA satellites fly in this range. This paper discusses the observation plan, including the development of the pointings, a refinement of the altitudes of interest, and an analysis of the effects of random pointing errors on beam overlap. Additionally, results from measurements taken in 2020 and 2021 are presented, showing that not only is the observation plan effective at sampling 700 km to 1000 km altitude, but it is also producing the most sensitive terrestrial radar measurements at these altitudes to date.

James Murray↗