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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Scalable parallel communications

Coarse-grain parallelism in networking (that is, the use of multiple protocol processors running replicated software sending over several physical channels) can be used to provide gigabit communications for a single application. Since parallel network performance is highly dependent on real issues such as hardware properties (e.g., memory speeds and cache hit rates), operating system overhead (e.g., interrupt handling), and protocol performance (e.g., effect of timeouts), we have performed detailed simulations studies of both a bus-based multiprocessor workstation node (based on the Sun Galaxy MP multiprocessor) and a distributed-memory parallel computer node (based on the Touchstone DELTA) to evaluate the behavior of coarse-grain parallelism. Our results indicate: (1) coarse-grain parallelism can deliver multiple 100 Mbps with currently available hardware platforms and existing networking protocols (such as Transmission Control Protocol/Internet Protocol (TCP/IP) and parallel Fiber Distributed Data Interface (FDDI) rings); (2) scale-up is near linear in n, the number of protocol processors, and channels (for small n and up to a few hundred Mbps); and (3) since these results are based on existing hardware without specialized devices (except perhaps for some simple modifications of the FDDI boards), this is a low cost solution to providing multiple 100 Mbps on current machines. In addition, from both the performance analysis and the properties of these architectures, we conclude: (1) multiple processors providing identical services and the use of space division multiplexing for the physical channels can provide better reliability than monolithic approaches (it also provides graceful degradation and low-cost load balancing); (2) coarse-grain parallelism supports running several transport protocols in parallel to provide different types of service (for example, one TCP handles small messages for many users, other TCP's running in parallel provide high bandwidth service to a single application); and (3) coarse grain parallelism will be able to incorporate many future improvements from related work (e.g., reduced data movement, fast TCP, fine-grain parallelism) also with near linear speed-ups.

Maly, K.↗
NASA NTRS2009

A Belief-Based Model of Air Traffic Controllers Performing Separation Assurance

A model of an air traffic controller performing a separation assurance task was produced. The model was designed to be simple to use and deploy in a simulator, but still provide realistic behavior. The model is based upon an evaluation of the safety function of the controller for separation assurance, and utilizes fast and frugal heuristics and belief networks to establish a knowledge set for the controller model. Based on this knowledge set, the controller acts to keep aircraft separated. Validation results are provided to demonstrate the model s performance.

Landry, S.J.↗
DOE OSTI2021

Augmented signal processing in Liquid Argon Time Projection Chambers with a deep neural network

The Liquid Argon Time Projection Chamber (LArTPC) is an advanced neutrino detector technology widely used in recent and upcoming accelerator neutrino experiments. It features a low energy threshold and high spatial resolution that allow for comprehensive reconstruction of event topologies. In current-generation LArTPCs, the recorded data consist of digitized waveforms on wires produced by induced signal on wires of drifting ionization electrons, which can also be viewed as two-dimensional (2D) (time versus wire) projection images of charged-particle trajectories. For such an imaging detector, one critical step is the signal processing that reconstructs the original charge projections from the recorded 2D images. For the first time, we introduce a deep neural network in LArTPC signal processing to improve the signal region of interest detection. By combining domain knowledge (e.g., matching information from multiple wire planes) and deep learning, this method shows significant improvements over traditional methods. This work details the method, software tools, and performance evaluated with realistic detector simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Compliant Intramedullary Stems for Joint Reconstruction

The longevity of current joint replacements is limited by aseptic loosening, which is the primary cause of non-infectious failure for hip, knee, and ankle arthroplasty. Aseptic loosening is typically caused either by osteolysis from particulate wear, or by high shear stresses at the bone-implant interface from over-constraint. Our objective was to demonstrate feasibility of a compliant intramedullary stem that eliminates over-constraint without generating particulate wear. The compliant stem is built around a compliant mechanism that permits rotation about a single axis. We first established several models to understand the relationship between mechanism geometry and implant performance under a given angular displacement and compressive load. We then used a neural network to identify a design space of geometries that would support an expected 100-year fatigue life inside the body. We additively manufactured one representative mechanism for each of three anatomic locations, and evaluated these prototypes on a KR-210 robot. The neural network predicts maximum stress and torsional stiffness with 2.69% and 4.08% error respectively, relative to finite element analysis data. We identified feasible design spaces for all three of the anatomic locations. Simulated peak stresses for the three stem prototypes were below the fatigue limit. Benchtop performance of all three prototypes was within design specifications. Our results demonstrate the feasibility of designing patient- and joint-specific compliant stems that address the root causes of aseptic loosening. Guided by these results, we expect the use of compliant intramedullary stems in joint reconstruction technology to increase implant lifetime.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Time series of methane fluxes measured by eddy-covariance require gap-filling to estimate annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for methane, with regards both to the best model algorithms and predictors. In this study, we address the need for standardization by synthesizing results of gap-filling methods applied at 17 wetland sites spanning boreal to tropical regions including all major wetlands classes and two rice paddies. We introduce new procedures for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with robust uncertainty estimates. We tested a conventional method (marginal distribution sampling) and four machine learning algorithms - penalized linear regression, artificial neural networks, random forests, and boosted decision trees - and four predictor sets, including temporal, meteorological, ecosystem carbon and energy flux, and soil predictors. We find that the conventional method can achieve similar median performance to the machine learning models but is worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. Finally, we gap-fill and provide summary evaluation metrics for all 81 sites in the FLUXNET-CH4 community dataset and publicly release the python code for model development, evaluation, and uncertainty estimation.

42 ENGINEERING↗
DOE OSTI2021

Enabling Realistic Communications Evaluations for ADMS

Increasing penetration levels of inverter-based distributed energy resources (DERs) in distribution systems are creating challenges in system operation. Currently, wired or proprietary wireless communications are used by advanced distribution management systems (ADMS) to detect the state of the system and control the DERs for optimal operation. Wireless communications are an alternative solution that can enable connectivity between the dispersed assets used in distribution system applications. As demand for the seamless integration of distributed energy resources (DERs) continues to increase, proper networking and communications systems are becoming important to support the DER infrastructure. This report summarizes validation of a private wireless LTE network in a laboratory environment. The purpose of this work is to 1) demonstrate the effectiveness of private wireless LTE communication for grid applications and 2) provide a means of evaluating latency and overall performance of wireless communication in grid applications. First, private wireless LTE communication was validated in a direct transfer trip relaying scenario as an example of one-way communications using grid equipment. This study provided a baseline understanding of the variation in latency for seven different kinds of wireless scenarios shown in Figure A below. As expected, weak (attenuated) wireless signal-based communication yielded the widest ranges in latency. When higher priority was set for the trip signal communication, this resulted in lower latency in communication timing. In the final phase of this project, the private wireless LTE network was validated using two-way communications in an advanced distribution management system (ADMS) testbed which was developed in the ESIF at NREL. The purpose of this was to study the impact of wireless communication on grid performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Universal Solvent Viscosity Reduction via Hydrogen Bonding Disruptors

Liquid Ion Solutions LLC (DBA RoCo Global) in partnership with Carnegie Mellon University and Carbon Capture Scientific LLC, has performed lab-scale development and evaluation of novel additives that lower the viscosity of water-lean amine solvents for post-combustion carbon dioxide capture. This project focuses on developing additives that minimize the formation of long-range electrostatic and hydrogen bonding (HB) networks, decreasing the solvent viscosity, improving diffusion, and improving the process economics. The project objectives included: 1) performing computer simulation to understand the molecular interactions of the additive molecules in water-lean CO 2 capture solvents, 2) design and synthesis of HB disruptors additives, 3) performance testing with additive molecules on model amine solvents, and 4) demonstration of the effectiveness of the optimized additives in the presence of synthetic flue gas. To meet the abovementioned objectives, the project team utilized a holistic approach that combines molecular simulation, experimental testing, and economic analysis studies. The project team developed ab initio molecular model and then perform computer simulation to develop relationship between hydrogen bonding, viscosity, and performed quantitative analysis of additive on the viscosity of the solvent. The team completed computational comparative study on a range of organic functional groups such as ethers, esters, cyclic carbonates, alkanes, and ammonium salts for their effect on viscosity gaining key insights into molecular interactions and the impact of various functional groups and molecular shapes on viscosity. Assisted with molecular simulation insights, the project team conducted additive synthesis and testing, including a proof-of-concept study, additive screening, optimization, and synthetic flue gas testing. The experimental proof-of-concept study proved that the hydrogen bonding acceptors result in significant decrease of viscosities. Detailed additive screening (exploring various functionalities and molecular structures) has been performed. Several promising additives showed excellent reduction in viscosity (30-41%) at 5% additive loading, and over 50% viscosity reduction at 10% additive loading for the model solvents. The team also performed complex screening studies on additive loadings and mixing effect among additives using the design of experiments. Based on multiple screening experiments, one additive-solvent candidate was down-selected for synthetic flue gas testing. A 100-hour continuous absorption/desorption study was conducted under simulated flue gas using a lab-scale continuous capture and separation system. No degradation (for both solvent and additive) was observed based on the GC results of the solvent samples collected from the continuous study. The team conducted preliminary engineering analyses and cost-benefit analyses to quantify the potential economic benefits of the additive approach for solvent viscosity reduction. Based on the experimental data, CO 2 capture cost savings from the capital and operating cost savings are estimated at $\$$4.7/tonne and $\$$0.3/tonne CO 2 captured, respectively. Considering the additive cost, the net benefit is estimated to be between $\$$4.32~$\$$4.86/tonne CO 2 captured.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2020

Using an Advanced Distribution Management System Test Bed to Evaluate the Impact of Model Quality on Volt/VAR Optimization: Preprint

In this paper, we present a test bed for evaluating existing and future advanced distribution management system (ADMS) applications in a realistic laboratory setting, including other utility management systems and field equipment. We present an example of using it to evaluate the impact of the ADMS network model quality on a Volt/VAR optimization (VVO) application. The test bed integrates a commercial ADMS with a real-time simulation model of a utility distribution feeder. Representative power and controller hardware are integrated through hardware-in-the-loop (HIL) techniques. The performance of the ADMS VVO application is also evaluated for different levels of measurement density. Initial results indicate that a higher model quality achieves the highest possible energy savings while avoiding voltage violations, whereas a lower model quality results in increased energy savings but at the expense of more voltage violations.

ADMS↗
DOE OSTI2022

A Two-Level Model Predictive Control-Based Approach for Building Energy Management including Photovoltaics, Energy Storage, Solar Forecasting and Building Loads

This paper uses a two-level model predictive control-based approach for the coordinated control and energy management of an integrated system that includes photovoltaic (PV) generation, energy storage, and building loads. Novel features of the proposed local controller include (1) the ability to simultaneously manage building loads and energy storage to achieve different operational objectives such as energy efficiency, economic cost efficiency, demand response and grid optimization through the design of specific power trajectory tracking performance functionals, (2) an energy trim function that minimizes the impact of solar forecasting errors on system performance, and (3) the design of a state of charge controller that uses day-ahead forecast of solar power and building loads to intialize energy storage at the start of each day. The local controller is tested in simulation using an exemplary system with PV generation, energy storage and dispatchable building loads. Two sample days with different PV forecasts and multiple case scenarios are considered, and the performance of the algorithm in managing the real and reactive net building load trajectories and the ramp rate of PV injections into the utility network are evaluated. The simulations are based on actual forecasted and measured PV data, and the results show that the local controller meets the tracking requirements for real and reactive power within the operating constraints of the building.

14 SOLAR ENERGY↗
NASA NTRS1993

Data communication network at the ASRM facility

This report describes the simulation of the overall communication network structure for the Advanced Solid Rocket Motor (ASRM) facility being built at Yellow Creek near Iuka, Mississippi as of today. The report is compiled using information received from NASA/MSFC, LMSC, AAD, and RUST Inc. As per the information gathered, the overall network structure will have one logical FDDI ring acting as a backbone for the whole complex. The buildings will be grouped into two categories viz. manufacturing intensive and manufacturing non-intensive. The manufacturing intensive buildings will be connected via FDDI to the Operational Information System (OIS) in the main computing center in B_1000. The manufacturing non-intensive buildings will be connected by 10BASE-FL to the OIS through the Business Information System (BIS) hub in the main computing center. All the devices inside B_1000 will communicate with the BIS. The workcells will be connected to the Area Supervisory Computers (ASCs) through the nearest manufacturing intensive hub and one of the OIS hubs. Comdisco's Block Oriented Network Simulator (BONeS) has been used to simulate the performance of the network. BONeS models a network topology, traffic, data structures, and protocol functions using a graphical interface. The main aim of the simulations was to evaluate the loading of the OIS, the BIS, and the ASCs, and the network links by the traffic generated by the workstations and workcells throughout the site.

Moorhead, Robert J., II↗
NASA NTRS1993

Space network scheduling benchmark: A proof-of-concept process for technology transfer

This paper describes a detailed proof-of-concept activity to evaluate flexible scheduling technology as implemented in the Request Oriented Scheduling Engine (ROSE) and applied to Space Network (SN) scheduling. The criteria developed for an operational evaluation of a reusable scheduling system is addressed including a methodology to prove that the proposed system performs at least as well as the current system in function and performance. The improvement of the new technology must be demonstrated and evaluated against the cost of making changes. Finally, there is a need to show significant improvement in SN operational procedures. Successful completion of a proof-of-concept would eventually lead to an operational concept and implementation transition plan, which is outside the scope of this paper. However, a high-fidelity benchmark using actual SN scheduling requests has been designed to test the ROSE scheduling tool. The benchmark evaluation methodology, scheduling data, and preliminary results are described.

Moe, Karen↗
NASA NTRS2008

Model-Based Fault Tolerant Control

The Model Based Fault Tolerant Control (MBFTC) task was conducted under the NASA Aviation Safety and Security Program. The goal of MBFTC is to develop and demonstrate real-time strategies to diagnose and accommodate anomalous aircraft engine events such as sensor faults, actuator faults, or turbine gas-path component damage that can lead to in-flight shutdowns, aborted take offs, asymmetric thrust/loss of thrust control, or engine surge/stall events. A suite of model-based fault detection algorithms were developed and evaluated. Based on the performance and maturity of the developed algorithms two approaches were selected for further analysis: (i) multiple-hypothesis testing, and (ii) neural networks; both used residuals from an Extended Kalman Filter to detect the occurrence of the selected faults. A simple fusion algorithm was implemented to combine the results from each algorithm to obtain an overall estimate of the identified fault type and magnitude. The identification of the fault type and magnitude enabled the use of an online fault accommodation strategy to correct for the adverse impact of these faults on engine operability thereby enabling continued engine operation in the presence of these faults. The performance of the fault detection and accommodation algorithm was extensively tested in a simulation environment.

Kumar, Aditya↗
DOE OSTI2023

Performance Evaluation of Gray-box and Machine Learning Models of a Thermal Energy Storage System with Active Insulation

An interior partition wall integrated with active thermal storage and a dynamic insulation system was built and then installed in an office building in Oak Ridge, Tennessee, TN. This smart wall, termed the Empower Wall, was equipped with embedded pipes in the building envelope core component and an additional pipe network enclosing rigid insulation to switch on and off the active insulation dynamically. The performance of the wall's contribution to cooling load reduction under different parameters has been investigated in previous publications. Aiming to be deployed into model predictive control and other optimization methods, simplified and reliable models for the developed wall and the room accommodating it are required. They are needed to characterize the properties and thermal response of both Empower Wall and building envelope, which form an essential component for accurate indoor temperature or cooling/heating demand prediction. In this study, simplified gray-box and regression models as well as machine learning model were developed and the performance of them were compared and analyzed.

Cui, Borui↗
NASA NTRS1998

High End Computer Network Testbedding at NASA Goddard Space Flight Center

The Earth & Space Data Computing (ESDC) Division, at the Goddard Space Flight Center, is involved in development and demonstrating various high end computer networking capabilities. The ESDC has several high end super computers. These are used to run: (1) computer simulation of the climate systems; (2) to support the Earth and Space Sciences (ESS) project; (3) to support the Grand Challenge (GC) Science, which is aimed at understanding the turbulent convection and dynamos in stars. GC research occurs in many sites throughout the country, and this research is enabled by, in part, the multiple high performance network interconnections. The application drivers for High End Computer Networking use distributed supercomputing to support virtual reality applications, such as TerraVision, (i.e., three dimensional browser of remotely accessed data), and Cave Automatic Virtual Environments (CAVE). Workstations can access and display data from multiple CAVE's with video servers, which allows for group/project collaborations using a combination of video, data, voice and shared white boarding. The ESDC is also developing and demonstrating the high degree of interoperability between satellite and terrestrial-based networks. To this end, the ESDC is conducting research and evaluations of new computer networking protocols and related technologies which improve the interoperability of satellite and terrestrial networks. The ESDC is also involved in the Security Proof of Concept Keystone (SPOCK) program sponsored by National Security Agency (NSA). The SPOCK activity provides a forum for government users and security technology providers to share information on security requirements, emerging technologies and new product developments. Also, the ESDC is involved in the Trans-Pacific Digital Library Experiment, which aims to demonstrate and evaluate the use of high performance satellite communications and advanced data communications protocols to enable interactive digital library data access between the U. S. Library of Congress, the National Library of Japan and other digital library sites at 155 MegaBytes Per Second. The ESDC participation in this program is the Trans-Pacific access to GLOBE visualizations in real time. ESDC is participating in the Department of Defense's ATDNet with Multiwavelength Optical Network (MONET) a fully switched Wavelength Division Networking testbed. This presentation is in viewgraph format.

Gary, James Patrick↗
NASA NTRS2011

Analysis of Proximity-1 Space Link Interleaved Time Synchronization (PITS) Protocol

To synchronize clocks between spacecraft in proximity, the Proximity-1 Space Link Interleaved Time Synchronization (PITS) Protocol has been proposed. PITS is based on the NTP Interleaved On-Wire Protocol and is capable of being adapted and integrated into CCSDS Proximity-1 Space Link Protocol with minimal modifications. In this work, we will discuss the correctness and liveness of PITS. Further, we analyze and evaluate the performance of time synchronization latency with various channel error rates in different PITS operational modes.

network time protocol↗
DOE OSTI2024

Multi-Level Structural Damage Characterization Using Sparse Acoustic Sensor Networks and Knowledge Transferred Deep Learning

Standard structural health monitoring techniques face well-known difficulties for comprehensive defect diagnosis in real-world structures that have structural, material, or geometric complexity. This motivates the exploration of machine-learning-based structural health monitoring methods in complex structures. However, creating sufficient training data sets with various defects is an ongoing challenge for data-driven machine (deep) learning algorithms. The ability to transfer the knowledge of a trained neural network from one component to another or to other sections of the same component would drastically reduce the required training data set. Also, it would facilitate computationally inexpensive machine learning based inspection systems. In this work, a machine-learning-based multi-level damage characterization is demonstrated with the ability to transfer trained knowledge within the sparse sensor network. A novel network spatial assistance and an adaptive convolution technique are proposed for efficient knowledge transfer within the deep learning algorithm. Proposed structural health monitoring method is experimentally evaluated on an aluminum plate with artificially induced defects. It was observed that the method improves the performance of knowledge transferred damage characterization by 50% during localization and 24% during severity assessment. Further, experiments using time windows with and without multiple edge reflections are studied. Results reveal that multiply scattered waves contain rich and deterministic defect signatures that can be mined using deep learning neural networks, improving the accuracy of both identification and quantification. In the case of a fixed sensor network, using multiply scattered waves shows 100% prediction accuracy at all levels of damage characterization.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Quantum-Based Molecular Dynamics Simulations Using Tensor Cores

Tensor cores, along with tensor processing units, represent a new form of hardware acceleration specifically designed for deep neural network calculations in artificial intelligence applications. Tensor cores provide extraordinary computational speed and energy efficiency but with the caveat that they were designed for tensor contractions (matrix–matrix multiplications) using only low-precision floating-point operations. Despite this perceived limitation, we demonstrate how tensor cores can be applied with high efficiency to the challenging and numerically sensitive problem of quantum-based Born–Oppenheimer molecular dynamics, which requires highly accurate electronic structure optimizations and conservative force evaluations. The interatomic forces are calculated on-the-fly from an electronic structure that is obtained from a generalized deep neural network, where the computational structure naturally takes advantage of the exceptional processing power of the tensor cores and allows for high performance in excess of 100 Tflops on a single Nvidia A100 GPU. Stable molecular dynamics trajectories are generated using the framework of extended Lagrangian Born–Oppenheimer molecular dynamics, which combines computational efficiency with long-term stability, even when using approximate charge relaxations and force evaluations that are limited in accuracy by the numerically noisy conditions caused by the low-precision tensor core floating-point operations. A canonical ensemble simulation scheme is also presented, where the additional numerical noise in the calculated forces is absorbed into a Langevin-like dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1993

Diversity reception for advanced multi-satellite networks: A CDMA approach

Diversity reception for Synchronous CDMA (S-CDMA) is introduced and analyzed. A Gaussian co-channel synchronous and asynchronous interference approximation is derived to evaluate the effects on the system bit error rate. Numerical results are provided for a simple mobile communication system where the signals transmitted by two distinct satellites in visibility are coherently combined by a three fingers Rake receiver. A second example showing performance of an integrated ground/satellite single frequency network for digital audio broadcasting is presented. Results show the capacity advantage of utilizing S-CDMA in combination with diversity reception.

Colzi, E.↗