Results for “TIME” — Page 2

NASA NTRSDate not supplied

A Discussion of Time Management Concepts and Time Constraint Equations for Multi-Rate Federation Executions

The High Level Architecture (HLA) is a simulation interoperability standard developed by the Simulation Interoperability Standards Organization (SISO) and published as the international standard IEEE 1516-2010 by the Institute for Electrical and Electronics Engineers (IEEE). HLA is a widely used standard for the development and execution of collaborative distributed simulations. HLA provides a number of Management Services to simulation developers: Federation, Declaration, Object, Ownership, Data Distribution, and Time. Of those services, Time Management Services is probably one of the least understood and least used. However, Time Management Services are critical to technical simulations like those created for space systems using the Space Reference Federation Object Model (SpaceFOM). Time Management can be used to insure data coherence and execution repeatability in distributed simulations. When combined with real time execution policies, Time Management is being used to support real time execution of mixed software and hardware in the loop integration, verification, and validation simulations for active space systems development. This paper starts by providing an overview of the HLA Time Management Services. This provides the background to discuss the challenges associated with Time Management and its use, starting with simple common rate frame scheduled simulations, then simple multi-rate simulations, and ending with complex mixed rate simulations. The authors then formulate the significant time constraint relationships between identified frame scheduling parameters. The intent of the paper is to provide a concise discussion of how to use Time Management in both simple cases and in more complex mixed frame rate federation executions.

Simulation Interoperability↗

NASA NTRSDate not supplied

A Discussion of Time Management Concepts and Time Constraint Equations for Multi-Rate Federation Executions

The High Level Architecture (HLA) is a simulation interoperability standard developed by the Simulation Interoperability Standards Organization (SISO) and published as the international standard IEEE 1516-2010 by the Institute for Electrical and Electronics Engineers (IEEE). HLA is a widely used standard for the development and execution of collaborative distributed simulations. HLA provides a number of Management Services to simulation developers: Federation, Declaration, Object, Ownership, Data Distribution, and Time. Of those services, Time Management Services is probably one of the least understood and least used. However, Time Management Services are critical to technical simulations like those created for space systems using the Space Reference Federation Object Model (SpaceFOM). Time Management can be used to insure data coherence and execution repeatability in distributed simulations. When combined with real time execution policies, Time Management is being used to support real time execution of mixed software and hardware in the loop integration, verification, and validation simulations for active space systems development. This paper starts by providing an overview of the HLA Time Management Services. This provides the background to discuss the challenges associated with Time Management and its use, starting with simple common rate frame scheduled simulations, then simple multi-rate simulations, and ending with complex mixed rate simulations. The authors then formulate the significant time constraint relationships between identified frame scheduling parameters. The intent of the paper is to provide a concise discussion of how to use Time Management in both simple cases and in more complex mixed frame rate federation executions.

Simulation Interoperability↗

NASA NTRS2016

Taxi Time Prediction at Charlotte Airport Using Fast-Time Simulation and Machine Learning Techniques

Accurate taxi time prediction is required for enabling efficient runway scheduling that can increase runway throughput and reduce taxi times and fuel consumptions on the airport surface. Currently NASA and American Airlines are jointly developing a decision-support tool called Spot and Runway Departure Advisor (SARDA) that assists airport ramp controllers to make gate pushback decisions and improve the overall efficiency of airport surface traffic. In this presentation, we propose to use Linear Optimized Sequencing (LINOS), a discrete-event fast-time simulation tool, to predict taxi times and provide the estimates to the runway scheduler in real-time airport operations. To assess its prediction accuracy, we also introduce a data-driven analytical method using machine learning techniques. These two taxi time prediction methods are evaluated with actual taxi time data obtained from the SARDA human-in-the-loop (HITL) simulation for Charlotte Douglas International Airport (CLT) using various performance measurement metrics. Based on the taxi time prediction results, we also discuss how the prediction accuracy can be affected by the operational complexity at this airport and how we can improve the fast time simulation model before implementing it with an airport scheduling algorithm in a real-time environment.

airport surface traffic↗

NASA NTRS2019

Prediction of Pushback Times and Ramp Taxi Times for Departures at Charlotte Airport

When optimizing the takeoff sequence and schedule for departures at busy airports, it is important to accurately predict the taxi times from gate to runway because those are used to calculate the earliest possible takeoff times. Several airports like Charlotte Douglas International Airport show relatively long taxi times inside the ramp area with large variations, with respect to the travel times in the airport movement area. Also, the pushback process times have not been accurately modeled so far mainly due to the lack of accurate data. The recent deployment of the integrated arrival, departure, and surface traffic management system at Charlotte airport by NASA enables more accurate flight data in the airport surface operations to be obtained. Taking advantage of this system, actual pushback times and ramp taxi times from historical flight data at this airport are analyzed. Based on the analysis, a simple, data-driven prediction model is introduced for estimating pushback times and ramp transit times of individual departure flights. To evaluate the performance of this prediction model, several machine learning techniques are also applied to the same dataset. The prediction results show that the data-driven prediction model is as good as the machine learning algorithms when comparing various prediction performance metrics.

airport surface operations↗

NASA NTRS2019

Fast-Time Simulation for Evaluating the Impact of Estimated Flight Ready Time Uncertainty on Surface Metering

NASA has been developing and demonstrating new concepts and technologies for Integrated Arrival, Departure, and Surface (IADS) traffic management capabilities under the Airspace Technology Demonstration 2 (ATD-2) project. One of the IADS capabilities in the ATD-2 project is surface metering enabled by a tactical surface scheduler to provide controllers with the pushback advisories for departures at gates. The tactical surface scheduler uses the estimated flight ready times provided by airlines, called Earliest Off-Block Times (EOBTs), as input to calculate the target off-block times for pushback advisories. However, the EOBTs are often inaccurate and deviate from the actual flight ready times, which may reduce the benefits of surface metering. In this paper, a linear regression model is developed to model the EOBT uncertainty distribution over time based on actual EOBT data collected at Charlotte airport. This EOBT model is integrated with a tactical surface scheduler and a fast-time simulation tool. To evaluate the impact of the EOBT accuracy on airport surface operations, fast-time simulations are implemented for selected traffic scenarios under different levels of modelled EOBT accuracy. The simulation results show that the EOBT uncertainty affects several performance metrics related to the surface metering, such as gate hold, taxi time reduction, and target takeoff time predictability, which in turn influences ATD-2's scheduler performance.

tactical surface scheduler↗

NASA NTRS2019

Fast-Time Simulation for Evaluating the Impact of Estimated Flight Ready Time Uncertainty on Surface Metering

NASA has been developing and demonstrating new concepts and technologies for Integrated Arrival, Departure, and Surface (IADS) traffic management capabilities under the Airspace Technology Demonstration 2 (ATD-2) project. One of the IADS capabilities in the ATD-2 project is surface metering enabled by a tactical surface scheduler to provide controllers with the pushback advisories for departures at gates. The tactical surface scheduler uses the estimated flight ready times provided by airlines, called Earliest Off-Block Times (EOBTs), as input to calculate the target off-block times for pushback advisories. However, the EOBTs are often inaccurate and deviate from the actual flight ready times, which may reduce the benefits of surface metering. In this paper, a linear regression model is developed to model the EOBT uncertainty distribution over time based on actual EOBT data collected at Charlotte airport. This EOBT model is integrated with a tactical surface scheduler and a fast-time simulation tool. To evaluate the impact of the EOBT accuracy on airport surface operations, fast-time simulations are implemented for selected traffic scenarios under different levels of modelled EOBT accuracy. The simulation results show that the EOBT uncertainty affects several performance metrics related to the surface metering, such as gate hold, taxi time reduction, and target takeoff time predictability, which in turn influences ATD-2's scheduler performance.

tactical surface scheduler↗

DOE OSTI2024

X-ray Spectral-Timing Pipeline to Investigate an Electron-Scattering Time Delay in Black Hole Accretion Disks [Slides]

The soft lag in black hole X-ray binaries (BHXRBs) refers to the time delay for the soft, thermal disk to respond to hard, variable coronal irradiation. This time lag increases from less than 1 ms to ~10 ms during the hard-to-soft state transition. Interpretations of soft lag trends appeal to changing the light-travel path via an evolving coronal height and/or inner accretion disk radius. Both interpretations neglect a time delay contribution from the reprocessing of irradiation inside the disk, where electron-scattering opacity dominates. A new theory considering a thermalization (electron scattering) time delay in the disk can plausibly produce ~10 ms time delays in the intermediate state. To further investigate the impacts of adding a time delay component from electron scattering in the disk, we are creating a spectral-timing pipeline that can analyze NICER (Neutron Star Interior Composition Explorer) X-ray observations of BHXRBs in outburst. In the near future, we will apply this spectral timing pipeline to develop a reverberation lag model from simulations that include the thermalization time delay from electron scattering in the disk.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1991

Comparison of GLONASS and GPS time transfers between two west European time laboratories and VNIIFTRI

The University of Leeds built a GPS/GLONASS receiver about five years ago and since then has provided continuous information about GLONASS time and its comparison with GPS time. For the last two years VNllFTRl and some other Soviet time laboratories have used Soviet-built GLONASS navigation receivers for time comparisons. Since June 1991, VNIIFTRI has been operating a GPS time receiver on loan from the BIPM. This offered, for the first time, an opportunity for direct comparison of time transfers using GPS and GLONASS. This experiment shows that even with relatively imprecise data recording and processing, in terms of time metrology, GLONASS can provide continental time transfer at a level of several tens of nanoseconds.

P. Daly↗

NASA NTRS2009

Implementation and Comparison of Acoustic Travel-Time Measurement Procedures for the Helioseismic and Magnetic Imager Time-Distance Helioseismology Pipeline

The Helioseismic and Magnetic Imager (HMI) instrument on board the Solar Dynamics Observatory (SDO) satellite is designed to produce high-resolution Doppler velocity maps of oscillations at the solar surface with high temporal cadence. To take advantage of these high-quality oscillation data, a time-distance helioseismology pipeline has been implemented at the Joint Science Operations Center (JSOC) at Stanford University. The aim of this pipeline is to generate maps of acoustic travel times from oscillations on the solar surface, and to infer subsurface 3D flow velocities and sound-speed perturbations. The wave travel times are measured from cross covariances of the observed solar oscillation signals. For implementation into the pipeline we have investigated three different travel-time definitions developed in time-distance helioseismology: a Gabor wavelet fitting (Kosovichev and Duvall, 1997), a minimization relative to a reference cross-covariance function (Gizon and Birch, 2002), and a linearized version of the minimization method (Gizon and Birch, 2004). Using Doppler velocity data from the Michelson Doppler Imager (MDI) instrument on board SOHO, we tested and compared these definitions for the mean and difference travel-time perturbations measured from reciprocal signals. Although all three procedures return similar travel times in a quiet Sun region, the method of Gizon and Birch (2004) gives travel times that are significantly different from the others in a magnetic (active) region. Thus, for the pipeline implementation we chose the procedures of Kosovichev and Duvall (1997) and Gizon and Birch (2002). We investigated the relationships among these three travel-time definitions, their sensitivities to fitting parameters, and estimated the random errors they produce

Couvidat, S.↗

NASA NTRS2015

Taxi Time Prediction at Charlotte Airport Using Fast-Time Simulation and Machine Learning Techniques

Accurate taxi time prediction can be used for more efficient runway scheduling to increase runway throughput and reduce taxi times and fuel consumptions on the airport surface. This paper describes two different approaches to predicting taxi times, which are a data-driven analytical method using machine learning techniques and a fast-time simulation-based approach. These two taxi time prediction methods are applied to realistic flight data at Charlotte Douglas International Airport (CLT) and assessed with actual taxi time data from the human-in-the-loop simulation for CLT airport operations using various performance measurement metrics. Based on the preliminary results, we discuss how the taxi time prediction accuracy can be affected by the operational complexity at this airport and how we can improve the fast-time simulation model for implementing it with an airport scheduling algorithm in real-time operational environment.

Lee, Hanbong↗

NASA NTRS2019

Prediction of Pushback Times and Ramp Taxi Times for Departures at Charlotte Airport

When optimizing the takeoff sequence and schedule for departures at busy airports, it is important to accurately predict the taxi times from gate to runway because those are used to calculate the earliest possible takeoff times. Several airports like Charlotte Douglas International Airport show relatively long taxi times inside the ramp area with large variations, with respect to the travel times in the airport movement area. Also, the pushback process times have not been accurately modeled so far mainly due to the lack of accurate data. The recent deployment of the integrated arrival, departure, and surface traffic management system at Charlotte airport by NASA enables more accurate flight data in the airport surface operations to be obtained. Taking advantage of this system, actual pushback times and ramp taxi times from historical flight data at this airport are analyzed. Based on the analysis, a simple, data-driven prediction model is introduced for estimating pushback times and ramp transit times of individual departure flights. To evaluate the performance of this prediction model, several machine learning techniques are also applied to the same dataset. The prediction results show that the data-driven prediction model is as good as the machine learning algorithms when comparing various prediction performance metrics.

Lee, Hanbong↗

NASA NTRS2023

Measurement of Test Time in the NASA Ames EAST Expansion Cone Facility in Entry 63 and Possible Techniques for Increasing Test Time

The Ames EAST facility and its modes of operation (expansion tube, expansion cone) are described. A buffer section may or may not be used between the driver and the driven tube. Previous expansion tube (without the cone) entries are reviewed. Test times of 4 to 5 microsec were achieved at shock speeds up to 11 km/s. The test conditions and results of the present entry (entry 63) (with the cone) are given. Test times were found to correlate roughly with the density ratio across the buffer gas - driven gas or driver - driven gas interface. Tests with a 12 inch long conical driver without a buffer yielded three runs with test times of ~8 km/s and 3 runs with test times of 4 to 6 microsecs. With a buffer, test times for 4 runs of ~9 microsecs and for 2 runs of 3 to 6 microsecs were obtained. Adding argon to the buffer was found not to improve the test time. Tests with a 30 inch long driver without a buffer yielded test times of 14+, ~10, 7.5 (2 runs) and 5.5 (2 runs) microsecs. Based on one shot, data for the 30 inch driver suggests that test times up to ~14 microseconds could be obtained. The repeatability of that shot, of course, must be established. Suggestions are given to increase test times further.

Electric arc shock tube↗

DOE OSTI2024

Topology property analysis and application of stable time-delay regions for linear multiple time-delay systems

This study examines the relationship between the topology of stable time-delay regions and the stability analysis of an linear multiple time delay system. To analyze the topology of stable time-delay regions, we construct a function with a value equal to zero for the time-delay points on the boundaries of stable time-delay regions. The function is continuous and differentiable in the whole defining field with a global minimum of zero so that we can locate the boundaries by minimizing the value of the function. Based on the topology analysis, we proposed a performance validation approach for controllers that are designed to stabilize the system using feedback signals with time delays. The method based on the topology analysis is simple and reliable so that can deal with a linear time-invariant system with high order and multiple time delays (more than 3). The example case study shows that the above method is reliable and enables ultra-low latency coordination and control for the future power grid with ubiquitous power electronics.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Real-Time High-Accuracy Digital Wireless Time, Frequency, and Phase Calibration for Coherent Distributed Antenna Arrays

his work presents a fully-digital high-accuracy real-time calibration procedure for frequency and time alignment of open-loop wirelessly coordinated coherent distributed antenna array (CDA) modems, enabling radio frequency (RF) phase coherence of spatially separated commercial off-the-shelf (COTS) software-defined radios (SDRs) without cables or external references such as the global navigation satellite system (GNSS). Building on previous work using high-accuracy spectrally-sparse time of arrival (ToA) waveforms and a multistep ToA refinement process, a high-accuracy two-way time transfer (TWTT)-based time–frequency coordination approach is demonstrated. Due to the two-way nature of the high-accuracy TWTT approach, the time and frequency estimates are Doppler and multipath tolerant, so long as the channel is reciprocal over the synchronization epoch. This technique is experimentally verified using COTS SDRs in a lab environment in static and dynamic scenarios and with significant multipath scatterers. Time, frequency, and phase stability were evaluated by beamforming over coaxial cables to an oscilloscope which achieved time and phase precisions of ~60– 70 ps , with median coherent gains above 99% using optimized coordination parameters, and a beamforming frequency root-mean-square error (RMSE) of 3.73 ppb in a dynamic scenario. Finally, experiments were conducted to compare the performance of this technique with previous works using an analog continuous-wave two-tone (CWTT) frequency reference technique in both static and dynamic settings.

Clock synchronization↗

DOE OSTI2023

Assessment and Commissioning of Electrical Substation Grid Testbed with a Real-Time Simulator and Protective Relays/Power Meters in the Loop

Electrical utility substations are wired with intelligent electronic devices (IEDs), such as protective relays, power meters, and communication switches. Substation engineers commission these IEDs to assess the appropriate measurements for monitoring, control, power system protection, and communication applications. Like real electrical utility substations, complex electrical substation grid testbeds (ESGTs) need to be assessed for measuring current and voltage signals in monitoring, power system protection, control (synchro check), and communication applications that are limited by small measurement percentage errors. In the process of setting an ESGT with real-time simulators and IEDs in the loop, protective relays, power meters, and communication devices must be commissioned before running experiments. In this study, an ESGT with IEDs and distributed ledger technology was developed. The ESGT with a real-time simulator and IEDs in the loop was satisfactorily assessed and commissioned. The commissioning and problem-solving tasks of the testbed are described to define a method with flowcharts to assess possible trouble-shooting in ESGTs. This method was based on comparing the simulations versus IED measurements for the phase current and voltage magnitudes, three-phase phasor diagrams, breaker states, protective relay times with selectivity coordination at electrical faults, communication data points, and time-stamp sources.

Piesciorovsky, Emilio↗

DOE OSTI2024

Tensor Network Space-Time Spectral Collocation Method for Time-Dependent Convection-Diffusion-Reaction Equations

Emerging tensor network techniques for solutions of partial differential equations (PDEs), known for their ability to break the curse of dimensionality, deliver new mathematical methods for ultra-fast numerical solutions of high-dimensional problems. Here, we introduce a Tensor Train (TT) Chebyshev spectral collocation method, in both space and time, for the solution of the time-dependent convection-diffusion-reaction (CDR) equation with inhomogeneous boundary conditions, in Cartesian geometry. Previous methods for numerical solution of time-dependent PDEs often used finite difference for time, and a spectral scheme for the spatial dimensions, which led to a slow linear convergence. Spectral collocation space-time methods show exponential convergence; however, for realistic problems they need to solve large four-dimensional systems. We overcome this difficulty by using a TT approach, as its complexity only grows linearly with the number of dimensions. We show that our TT space-time Chebyshev spectral collocation method converges exponentially, when the solution of the CDR is smooth, and demonstrate that it leads to a very high compression of linear operators from terabytes to kilobytes in TT-format, and a speedup of tens of thousands of times when compared to a full-grid space-time spectral method. These advantages allow us to obtain the solutions at much higher resolutions.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2010

Implementation and Comparison of Acoustic Travel-Time Measurement Procedures for the Solar Dynamics Observatory-Helioseismic and Magnetic Imager Time-Distance Helioseismology Pipeline

The Helioseismic and Magnetic Imager (HMI) instrument onboard the Solar Dynamics Observatory (SDO) satellite is designed to produce high-resolution Doppler-velocity maps of oscillations at the solar surface with high temporal cadence. To take advantage of these high-quality oscillation data, a time - distance helioseismology pipeline (Zhao et al., Solar Phys. submitted, 2010) has been implemented at the Joint Science Operations Center (JSOC) at Stanford University. The aim of this pipeline is to generate maps of acoustic travel times from oscillations on the solar surface, and to infer subsurface 3D flow velocities and sound-speed perturbations. The wave travel times are measured from cross-covariances of the observed solar oscillation signals. For implementation into the pipeline we have investigated three different travel-time definitions developed in time - distance helioseismology: a Gabor-wavelet fitting (Kosovichev and Duvall, SCORE'96: Solar Convection and Oscillations and Their Relationship, ASSL, Dordrecht, 241, 1997), a minimization relative to a reference cross-covariance function (Gizon and Birch, Astrophys. J. 571, 966, 2002), and a linearized version of the minimization method (Gizon and Birch, Astrophys. J. 614, 472, 2004). Using Doppler-velocity data from the Michelson Doppler Imager (MDI) instrument onboard SOHO, we tested and compared these definitions for the mean and difference traveltime perturbations measured from reciprocal signals. Although all three procedures return similar travel times in a quiet-Sun region, the method of Gizon and Birch (Astrophys. J. 614, 472, 2004) gives travel times that are significantly different from the others in a magnetic (active) region. Thus, for the pipeline implementation we chose the procedures of Kosovichev and Duvall (SCORE'96: Solar Convection and Oscillations and Their Relationship, ASSL, Dordrecht, 241, 1997) and Gizon and Birch (Astrophys. J. 571, 966, 2002). We investigated the relationships among these three travel-time definitions, their sensitivities to fitting parameters, and estimated the random errors that they produce.

HMI↗

DOE OSTI2025

A Practical Framework for Simulating Time-Resolved Spectroscopy Based on a Real-Time Dyson Expansion

Time-resolved spectroscopy is a powerful tool for probing electron dynamics in molecules and solids, revealing transient phenomena on subfemtosecond time scales. The interpretation of experimental results is often enhanced by parallel numerical studies, which can provide insight and validation for experimental hypotheses. However, developing a theoretical framework for simulating time-resolved spectra remains a significant challenge. The most suitable approach involves the many-body nonequilibrium Green's function formalism, which accounts for crucial dynamical many-body correlations during time evolution. While these dynamical correlations are essential for observing emergent behavior in time-resolved spectra, they also render the formalism prohibitively expensive for large-scale simulations. Substantial effort has been devoted to reducing this computational cost─through approximations and numerical techniques─while preserving the key dynamical correlations. The ultimate goal is to enable first-principles simulations of time-dependent systems ranging from small molecules to large, periodic, multidimensional solids. Here, in this perspective, we outline key challenges in developing practical simulations for time-resolved spectroscopy, with a particular focus on Green's function methodologies. We highlight a recent advancement toward a scalable framework: the real-time Dyson expansion (RT-DE) [Phys. Rev. Lett. 2024, 133, 226902]. We introduce the theoretical foundation of RT-DE and discuss strategies for improving scalability, which have already enabled simulations of system sizes beyond the reach of previous fully dynamical approaches. We conclude with an outlook on future directions for extending RT-DE to first-principles studies of dynamically correlated, nonequilibrium systems.

Reeves, Cian C. [Univ. of California, Santa Barbar↗