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At least 343 records · Page 19

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Optimal Traffic Signal Control Using Priority Metric Based on Real-Time Measured Traffic Information

Optimizing traffic control systems at traffic intersections can reduce network-wide fuel consumption as well as improve traffic flow. While traffic signals have conventionally been controlled based on predetermined schedules, various adaptive control systems have been developed recently using advanced sensors such as cameras, radars, and LiDARs. By utilizing rich traffic information enabled by the advanced sensors, more efficient or optimal traffic signal control is possible in response to varying traffic conditions. This paper proposes an optimal traffic signal control method to minimize network-wide fuel consumption utilizing real-time traffic information provided by advanced sensors. This new method employs a priority metric calculated by a weighted sum of various factors, including the total number of vehicles, total vehicle speed, vehicle waiting time, and road preference. Genetic Algorithm (GA) is used as a global optimization method to determine the optimal weights in the priority metric. In order to evaluate the effectiveness of the proposed method, a traffic simulation model is developed in a high-fidelity traffic simulation environment called SUMO, based on a real-world traffic network. The traffic flow within this model is simulated using actual measured traffic data from the traffic network, enabling a comprehensive assessment of the novel optimal traffic signal control method in realistic conditions. The simulation results show that the proposed priority metric-based real-time traffic signal control algorithm can significantly reduce network-wide fuel consumption compared to the conventional fixed-time control and coordinated actuated control methods that are currently used in the modeled network. Additionally, incorporating truck priority in the priority metric leads to further improvements in fuel consumption reduction.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Real Fuel Modeling for Gasoline Compression Ignition Engine

Increasing regulatory demand for efficiency has led to development of novel combustion modes such as HCCI, GCI and RCCI for gasoline light duty engines. In order to realize HCCI as a compression ignition combustion mode system, in-cylinder compression temperatures must be elevated to reach the autoignition point of the premixed fuel/air mixture. This should be co-optimized with appropriate fuel formulations that can autoignite at such temperatures. CFD combustion modeling is used to model the auto ignition of gasoline fuel under compression ignition conditions. Using the fully detailed fuel mechanism consisting of thousands of components in the CFD simulations is computationally expensive. To overcome this challenge, the real fuel is represented by few major components of create a surrogate fuel mechanism. In this study, 9 variations of gasoline fuel sets were chosen as candidates to run in HCCI combustion mode. A study detailing the development of the gasoline real fuel model was performed and various surrogates for gasoline fuel were investigated. The gasoline real fuel model will be used in subsequent CFD modelling activities for the development of an advanced mixed mode combustion system as part of the Department of Energy funded project DE-EE0008478.

Gasoline Compression Ignition, real fuel modeling,↗

NASA NTRS2001

A New Centimeter-Level Real-Time Global Navigation and Positioning Capability with GPS

NASA/JPL has developed a new, precise, global, GPS-based capability for real-time terrestrial and space platform navigation. It has been demonstrated on Earth's surface and is 10 times more accurate than other real-time GPS-based systems. The new system poses certain advantages for Earth science remote sensing, including: the onboard generation of science data products in real-time, sensor control and reduction of data transmission bandwidth, improved environmental forecasting, autonomous and intelligent platform control, operations cost savings, and technology transfer and commercial partnership opportunities. The system's measurement capabilities and applications, demonstrated orbit accuracies, and precision LEO and spacecraft positioning and timing are highlighted.

real time↗

NASA NTRS2011

Digital Calibration of TR Modules for Real-time Digital Beamforming SweepSAR Architectures

Real-time digital beamforming, combined with lightweight, large aperture reflectors, enable SweepSAR architectures such as that of the proposed DESDynI [Deformation, Ecosystem Structure, and Dynamics of Ice] SAR [Synthetic Aperture Radar] Instrument (or DSI). These new instrument concepts require new methods for calibrating the multiple channels, which must be combined on-board, in real-time. The calibration of current state-of-the-art Electronically Steered Arrays typically involves pre-flight TR (Transmit/Receive) module characterization over temperature, and in-flight correction based on temperature, which ignores the effects of element aging and drifts unrelated to temperature. We are developing new methods for digitally calibrating digital beamforming arrays to reduce development time, risk and cost of precision calibrated TR modules for array architectures by accurately tracking modules' characteristics through closed-loop Digital Calibration, thus tracking systematic changes regardless of temperature. The benefit of this effort is that it would enable a new class of lightweight radar architecture, Digital Beamforming with SweepSAR, providing significantly larger swath coverage than conventional SAR architectures for solid earth and biomass remote sensing, while reducing mission mass and cost. This new instrument concept requires new methods for calibrating the multiple channels, which must be combined on-board, in real-time.

Real-time digital beamforming↗

NASA NTRS2016

Initial Demonstration of the Real-Time Safety Monitoring Framework for the National Airspace System Using Flight Data

As new operational paradigms and additional aircraft are being introduced into the National Airspace System (NAS), maintaining safety in such a rapidly growing environment becomes more challenging. It is therefore desirable to have an automated framework to provide an overview of the current safety of the airspace at different levels of granularity, as well an understanding of how the state of the safety will evolve into the future given the anticipated flight plans, weather forecast, predicted health of assets in the airspace, and so on. Towards this end, as part of our earlier work, we formulated the Real-Time Safety Monitoring (RTSM) framework for monitoring and predicting the state of safety and to predict unsafe events. In our previous work, the RTSM framework was demonstrated in simulation on three different constructed scenarios. In this paper, we further develop the framework and demonstrate it on real flight data from multiple data sources. Specifically, the flight data is obtained through the Shadow Mode Assessment using Realistic Technologies for the National Airspace System (SMART-NAS) Testbed that serves as a central point of collection, integration, and access of information from these different data sources. By testing and evaluating using real-world scenarios, we may accelerate the acceptance of the RTSM framework towards deployment. In this paper we demonstrate the framework's capability to not only estimate the state of safety in the NAS, but predict the time and location of unsafe events such as a loss of separation between two aircraft, or an aircraft encountering convective weather. The experimental results highlight the capability of the approach, and the kind of information that can be provided to operators to improve their situational awareness in the context of safety.

Real-time Safety Monitoring↗

NASA NTRS2018

NASA Provides the Capability to Deliver Near Real-Time JPSS Data to Users in Order to Monitor Time-Sensitive Applications Such as Wildfires, Floods, Volcanic Eruptions, Tropical Cyclones and Extreme Weather Events

NASA's Land, Atmosphere Near real-time Capability for EOS (Earth Observing System) (LANCE https://earthdata.nasa.gov/lance) serves near real time (NRT) data to monitor time sensitive applications such as monitoring wildfires, floods, volcanic eruptions, tropical cyclones and extreme weather events. It currently serves data and imagery from the Visible Infrared Imager Radiometer Suite (VIIRS) and Ozone Mapping and Profiler Suite (OMPS) S NPP (Suomi National Polar-orbiting Partnership) instruments and is in the process of integrating continuity data products from VIIRS and OMPS onboard the Joint Polar Satellite System (JPSS), via the JPSS data Hub, to continue to meet the needs of agencies, scientists and members of the general public. NASA's Earth Science Division (ESD) sponsored the EOSDIS development of LANCE in 2009 to provide a central point of access to high quality NRT data products and imagery for applications users. LANCE makes data available to the public within 3 hours of satellite observation and imagery within 4-5 hours of satellite observation. Full resolution browse imagery from LANCE are provided through the Global Imagery Browse Services (GIBS) which also fuels NASA's Worldview tool so that users can interactively browse near real time data. This data supports time critical applications and allows users to view current natural hazards and events and animate the imagery over time.

Near real time↗

NASA NTRS1997

ARTSN: An Automated Real-Time Spacecraft Navigation System

ARTSN, the Automated Real-Time Spacecraft Navigation system is a real time system for the automated navigation of interplanetary spacecraft. The system processes the real time DSN radio metric data flow and generates updated spacecraft solutions and the associated covariance. ARTSN is designed modularly with the user interface input and output separated from the data analysis modules. Designed for distributed application, the system provided, for the first time, an automated method of processing radio metric navigation data for interplanetary spacecraft.

ARTSN↗

DOE OSTI2021

SO3/H2SO4 continuous real-time sensor demonstration at a power plant

We present results from field testing of a new, innovative sensor developed to measure SO3/H2SO4 continuously and in real time at a coal-fired power plant. The system utilizes the sensitivity, specificity, and real-time capabilities of mid-infrared (Mid-IR) laser-based sensor technology, along with a heated, close-coupled cell mounted directly to a power plant duct. Measurements were made by the laser sensor over a 2-day period and compared to results from the accepted method, EPA 8A, which requires a 30-minute collection, labor intensive processing, and off-site analysis at a lab. In contrast to the condensation method, the laser sensor continuously samples flue gas and reports measurements of the concentration of SO3/H2SO4, SO2 ever second with unattended operation. This initial demonstration proved the sensor concept and paves the way for its use for optimizing sorbent injection used to neutralize SO3/H2SO4. Optimized sorbent injection will enable significant cost savings associated with efforts to mitigate the presence and effects of SO3/H2SO4 such as “Blue Plume”, air heater fouling, and duct corrosion. In particular, the real-time, actionable information will enable better control of additive injection in flex conditions and variable fuels.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2023

2023 Real-time Optimization Workflow Status Update

Nuclear integrated energy systems are composed of a diverse set of energy generation sources and exist in dynamic and competitive electricity markets. With the inclusion of thermal energy storage, nuclear power systems can store heat for future use through various processes, such as water desalination or hydrogen generation. This heat storage can be managed in such a way as to economically optimize its usage. By combining real-time price data from the day-ahead and real-time markets with predictive and intelligent models, the charging and discharging of the thermal energy storage may be determined and optimized. This research details an approach through models and systems for the real-time optimization (RTO) of capacity allocation. Virtual models of the energy system and its physics phenomenon and component interactions provide intelligence to verification and prediction of operations. An optimization framework can use data generated from both a set of physical assets as well as the virtual models to predict future performance and create optimization and control workflows. Data warehouse technologies can be used to combine data across models, optimization workflows, market price data, and sensor data to intuitively store various types of data and provide integrations to physical control systems as well as user visualizations. Put together, these components can create a system for the RTO of nuclear integrated energy systems. Various virtual models and bench-scale physical demonstrations have been successfully performed and verified using this system. Larger scale testbeds that include thermal energy storage systems have been identified as future opportunities. A gap analysis that details the steps necessary to reach a physical demonstration at this scale is provided, along with conclusions on the current effort and future work.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

Real‐Time Optical Process Monitoring for Structure and Property Control of Aerosol Jet Printed Functional Materials

Abstract Aerosol jet printing is a popular digital additive manufacturing method for flexible and hybrid electronics, but it lacks sophisticated real‐time process control schemes that would enable more widespread adoption in manufacturing environments. Here, an optical measurement system is introduced to track the aerosol density upstream of the printhead. The measured optical extinction, combined with the aerosol flow rate, is directly related to deposition rate and accurately predicts functional materials properties such as the electrical resistance of printed graphene films. This real‐time system offers a compelling solution for process drift and batch‐to‐batch variability, rendering it a valuable tool for both real‐time control of aerosol jet printing and fundamental studies of the underlying process science.

Tafoya, Rebecca R.↗

DOE OSTI2020

Data Federation Challenges in Remote Near-Real-Time Fusion Experiment Data Processing

Fusion energy experiments and simulations provide critical information needed to plan future fusion reactors. As next-generation devices like ITER move toward long-pulse experiments, analyses, including AI and ML, should be performed in a wide range of time and computing constraints, from near-real-time constraints, between-shot analysis, and to campaign-wide long-term analysis. However, the data volume, velocity, and variety make it extremely challenging for analyses using only local computational resources. Researchers need the ability to compose and execute workflows spanning edge resources to large-scale high-performance computing facilities.We present Delta, a system to address data analysis challenges, including AI/ML, in fusion science, by leveraging the ADIOS I/O library and middleware, to support executing science workflows over the wide area network for near-real-time streaming. We discuss the data federation challenges in performing remote workflows, focusing on on-going research work in (1) managing, reducing, and streaming data to minimize I/O and data movement overheads, (2) decompressing and reorganizing data for analysis, and (3) executing workflows for automated data analysis. We introduce examples for deep-learning based data analysis for the fusion domain and demonstrate how we use Delta to construct end-to-end workflows for a fusion device in Korea, connecting a remote DOE facility in the USA. The capability demonstrated by this project is the basis for improving the state of the art for near-real-time data federation amongst remote facilities.

Choi, Jong Youl↗

DOE OSTI2021

Collider probes of real triplet scalar dark matter

We study discovery prospects for a real triplet extension of the Standard Model scalar sector at the Large Hadron Collider (LHC) and a possible future 100 TeV $\mathcal{pp}$ collider. We focus on the scenario in which the neutral triplet scalar is stable and contributes to the dark matter relic density. When produced in $\mathcal{pp}$ collisions, the charged triplet scalar decays to the neutral component plus a soft pion or soft lepton pair, yielding a disappearing charged track in the detector. We recast current 13 TeV LHC searches for disappearing tracks, and find that the LHC presently excludes a real triplet scalar lighter than 248 (275) GeV, for a mass splitting of 172 (160) MeV with $\mathcal{L}$ = 36 fb –1 . The reach can extend to 497 (520) GeV with the collection of 3000 fb –1 . We extrapolate the 13 TeV analysis to a prospective 100 TeV pp collider, and find that a ~ 3 TeV triplet scalar could be discoverable with $\mathcal{L}$ = 30 ab –1 , depending on the degree to which pile up effects are under control. We also investigate the dark matter candidate in our model and corresponding present and prospective constraints from dark matter direct detection. We find that currently XENON1T can exclude a real triplet dark matter lighter than ~ 3 TeV for a Higgs portal coupling of order one or larger, and the future XENON20T will cover almost the entire dark matter viable parameter space except for vanishingly small portal coupling.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Real-time evolution of texture and temperature during friction stir processing of a magnesium alloy: An operando neutron diffraction study

The real-time development of texture and the evolution of temperature during friction stir processing (FSP) of a Mg alloy were investigated using an operando neutron diffraction measurement. A novel approach was applied in this study where the real-time, quasi-steady state measurements performed as a function of position during FSP are converted to a Lagrangian dataset that reveals the transient behavior as a function of time. The in-situ FSP was carried out under two different thermo-mechanical processing conditions represented by the Zener-Hollomon parameter, Z. Further, the results show that: (i) a shear texture develops from the initial strong basal texture with the peak temperature reaching about 774 K during a low-Z processing and (ii) a strong off-normal texture develops with a peak temperature of 616 K during a high-Z processing. Moreover, time-temperature-texture diagrams were established to reveal the real-time development of the texture during the processing for both the low Z and high Z processing conditions. The changes in texture will be discussed in terms of plastic deformation mechanisms active during various stages of the FSP under the two different processing conditions.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Multimodal sensor fusion for real-time standoff estimation in directed energy deposition

In Laser Powder-based Direct Energy Deposition (LP-DED) systems, achieving consistency, precision and quality of produced parts requires tight control over printing parameters. One of the critical parameters is the standoff distance. Maintaining an optimal standoff height is crucial for achieving correct laser power density and powder catchment efficiency, as both laser and powder streams are focused at this distance. Here, this study introduces a novel approach using multimodal sensor fusion to predict standoff height in real-time. The proposed system integrates two low-profile, cost-effective sensors: an RGB coaxial camera and a high frequency and high dynamic range microphone. By utilizing a simple fully connected neural network, trained on a limited dataset, data fusion of these sensors allowed for the real-time prediction of the standoff height. The results demonstrate high resolution and accuracy of the predictions across multiple geometries and a wide range of standoff heights. This approach offers a simple, and cost-effective solution for real-time standoff height monitoring and lays the groundwork for future integration into commercial LP-DED systems.

42 ENGINEERING↗

DOE OSTI2024

A semantics-driven framework to enable demand flexibility control applications in real buildings

Decarbonising and digitalising the energy sector requires scalable and interoperable Demand Flexibility (DF) applications. Semantic models are promising technologies for achieving these goals, but existing studies focused on DF applications exhibit limitations. These include dependence on bespoke ontologies, lack of computational methods to generate semantic models, ineffective temporal data management and absence of platforms that use these models to easily develop, configure and deploy controls in real buildings. This paper introduces a semantics-driven framework to enable DF control applications in real buildings. The framework supports the generation of semantic models that adhere to Brick and SAREF while using metadata from Building Information Models (BIM) and Building Automation Systems (BAS). The work also introduces a web platform that leverages these models and an actor and microservices architecture to streamline the development, configuration and deployment of DF controls. The paper demonstrates the framework through a case study, illustrating its ability to integrate diverse data sources, execute DF actuation in a real building, and promote modularity for easy reuse, extension, and customisation of applications. The paper also discusses the alignment between Brick and SAREF, the value of leveraging BIM data sources, and the framework's benefits over existing approaches, demonstrating a 75% reduction in effort for developing, configuring, and deploying building controls.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

A comparative study between real-world and laboratory accelerated aging of Cu/SSZ-13 SCR catalysts

Elucidating aging mechanisms in real-world applications is a critical component for developing and maintaining Cu/SSZ-13 SCR catalysts. To reveal gaps between laboratory accelerated aging and real-world aging, herein we report thorough comparative studies between 6 representative catalysts. Here, we apply a wide range of catalyst characterization methods, including surface area/porosity analysis, X-ray diffraction (XRD), H 2 -temperature programmed reduction, NH3-temperaure programmed desorption, solid-state nuclear magnetic resonance (NMR), in situ X-ray photoelectron (XPS) and electron paramagnetic resonance (EPR) spectroscopies, to gain atomic-level knowledge on Cu transformation under different aging protocols. We then correlate such knowledge to SCR, NH 3 /NO oxidation kinetic behavior of the catalysts. We found that sulfur aging plays the most important role in interpreting catalyst degradation during real-world application, including direct sulfur poisoning of isolated Cu II SCR active species to CuSO 4 -like species, the agglomeration of such species to multinuclear CuSO 4 clusters, and eventually, CuO formation during desulfation treatments. Such chemistries convert SCR active Cu to SCR inert Cu moieties without severely deteriorating catalyst support integrity. These characteristics are partially replicated by hydrothermal aging in the presence of SOx but are poorly mimicked by hydrothermal aging alone.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Imaginary admittance and charge transfer resistance correlate to the physiological status of Shewanella oneidensis cultures in real time

Monitoring microbial activity is essential for industrial and environmental applications to proceed efficiently. To minimize time and labor-intensive monitoring, a new paradigm is required for in-situ, real time analysis. Since bioconversion of organics is accomplished by microorganisms through the oxidation of feedstocks linked to the reduction of electron acceptors, microorganisms can be viewed as electrochemical catalysts. In this respect, cell membranes have an electrical potential, which is analogous to a conventional capacitor and linked dynamically to cellular activity. Here, in this study, we demonstrate the use of electrochemical impedance spectrometry (EIS) and cyclic voltammetry (CV) for monitoring microbial metabolic activity in real time, in-situ. The effect of organic electron donors as a function of concentration to the physiological status of strains of Shewanella oneidensis was determined. In this study, the pyomelanin overproducer (S. oneidensis ΔhmgA) and the pyomelanin deficient mutant (S. oneidensis ΔmelA) were chosen due to different surface electrochemical characteristics along with differences in oxygen utilization efficiency. CV, relative admittance, phase shift and permittivity changed with growth status and correlated with electron flow from organic carbon sources and terminal electron acceptor availability. This work offers a novel and inexpensive approach to real time monitoring with the advantage of abundant data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Lattice Boltzmann simulation of the dissolution of slag in alkaline solution using real-shape particles

Highlights: • A dissolution numerical model was proposed to capture the real dissolution kinetics of slag in alkaline solution. • The log forward dissolution rate of Si was described as a function of NBO/T and solution pH. • A threshold solid volume fraction of 0.688 was found for a voxel in 3D, 63.8% larger than that for a pixel in 2D. • The proposed dissolution numerical model provides a reliable alternative to study the dissolution kinetics of slag. A dissolution numerical model was proposed in this study to capture the real dissolution kinetics of slag in alkaline solution. It consists of three modules, i.e. (i) simulation of the initial particle parking structure of slag in alkaline solution using real-shape particles of slag, (ii) simulation of the chemical reactions between slag and solution based on the transition state theory, and (iii) simulation of the physical transport of aqueous ions using the lattice Boltzmann method. This dissolution numerical model was verified using experimental results, showing reasonable accuracy. After verification, the dissolution numerical model was implemented to study the influences of temperature and particle shape using a proper recipe of slag in alkaline solution. This recipe was designed to avoid solid phase precipitation or gel formation via thermodynamic analysis. The simulation results showed faster dissolution kinetics of slag when using higher temperatures and more irregular particle shapes.

36 MATERIALS SCIENCE↗