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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Model Data Archive for Manuscript Titled "Evaluation of a Coupled Surface–Subsurface Hydrologic Model Using Dense Water‑Level Sensors in a Mixed Urban–Rural Watershed"

This archive provides scripts, input files, and datasets used for the implementation and evaluation of a fully coupled surface–subsurface hydrologic model in the Neches River Basin, southeast Texas. The study uses the Advanced Terrestrial Simulator (ATS) to simulate coupled surface–subsurface hydrologic processes over a mixed urban–rural watershed and evaluates model performance using a dense network of 136 in situ water-level sensors, nine U.S. Geological Survey (USGS) stream gauges, and SSEBop-derived evapotranspiration estimates during the period October 2014–June 2024. The workflow is implemented primarily in Python 3 using the Watershed Workflow package. The Jupyter notebooks can be executed using open-source software such as Anaconda JupyterLab or Visual Studio Code. Other data files include TXT, CSV, XML, SHP, TIF, NetCDF, HDF5, and ExodusII files, which can be processed using the provided Python scripts. ATS input files are provided in XML format and can be edited using any commonly used text editor. This archive contains: *Scripts and input files used to generate the ATS model setup, including watershed discretization, mesh generation, parameter mapping, and model configuration. *Jupyter notebooks used for preprocessing observational data, evaluating streamflow, water levels, and evapotranspiration, computing performance metrics, and generating the figures presented in the manuscript. *ATS simulation outputs and processed observational datasets, including OneRain and DD6 water-level sensors, USGS streamflow observations, GIS data, and supporting spatial datasets used throughout the study.

Dense water-level sensor network↗
NASA NTRS2007

Flight Test Results from the NF-15B Intelligent Flight Control System (IFCS) Project with Adaptation to a Simulated Stabilator Failure

Adaptive flight control systems have the potential to be more resilient to extreme changes in airplane behavior. Extreme changes could be a result of a system failure or of damage to the airplane. A direct adaptive neural-network-based flight control system was developed for the National Aeronautics and Space Administration NF-15B Intelligent Flight Control System airplane and subjected to an inflight simulation of a failed (frozen) (unmovable) stabilator. Formation flight handling qualities evaluations were performed with and without neural network adaptation. The results of these flight tests are presented. Comparison with simulation predictions and analysis of the performance of the adaptation system are discussed. The performance of the adaptation system is assessed in terms of its ability to decouple the roll and pitch response and reestablish good onboard model tracking. Flight evaluation with the simulated stabilator failure and adaptation engaged showed that there was generally improvement in the pitch response; however, a tendency for roll pilot-induced oscillation was experienced. A detailed discussion of the cause of the mixed results is presented.

Bosworth, John T.↗
NASA NTRS2007

Flight Test Results from the NF-15B Intelligent Flight Control System (IFCS) Project with Adaptation to a Simulated Stabilator Failure

Adaptive flight control systems have the potential to be more resilient to extreme changes in airplane behavior. Extreme changes could be a result of a system failure or of damage to the airplane. A direct adaptive neural-network-based flight control system was developed for the National Aeronautics and Space Administration NF-15B Intelligent Flight Control System airplane and subjected to an inflight simulation of a failed (frozen) (unmovable) stabilator. Formation flight handling qualities evaluations were performed with and without neural network adaptation. The results of these flight tests are presented. Comparison with simulation predictions and analysis of the performance of the adaptation system are discussed. The performance of the adaptation system is assessed in terms of its ability to decouple the roll and pitch response and reestablish good onboard model tracking. Flight evaluation with the simulated stabilator failure and adaptation engaged showed that there was generally improvement in the pitch response; however, a tendency for roll pilot-induced oscillation was experienced. A detailed discussion of the cause of the mixed results is presented.

Bosworth, John T.↗
NASA NTRS2010

Flight Test Results from the NF-15B Intelligent Flight Control System (IFCS) Project with Adaptation to a Simulated Stabilator Failure

Adaptive flight control systems have the potential to be more resilient to extreme changes in airplane behavior. Extreme changes could be a result of a system failure or of damage to the airplane. A direct adaptive neural-network-based flight control system was developed for the National Aeronautics and Space Administration NF-15B Intelligent Flight Control System airplane and subjected to an inflight simulation of a failed (frozen) (unmovable) stabilator. Formation flight handling qualities evaluations were performed with and without neural network adaptation. The results of these flight tests are presented. Comparison with simulation predictions and analysis of the performance of the adaptation system are discussed. The performance of the adaptation system is assessed in terms of its ability to decouple the roll and pitch response and reestablish good onboard model tracking. Flight evaluation with the simulated stabilator failure and adaptation engaged showed that there was generally improvement in the pitch response; however, a tendency for roll pilot-induced oscillation was experienced. A detailed discussion of the cause of the mixed results is presented.

Bosworth, John T.↗
DOE OSTI2024

Using convolutional neural networks to detect edge localized modes in DIII-D from Doppler backscattering measurements

In H-mode tokamak plasmas, the plasma is sometimes ejected beyond the edge transport barrier. These events are known as edge localized modes (ELMs). ELMs cause a loss of energy and damage the vessel walls. Understanding the physics of ELMs, and by extension, how to detect and mitigate them, is an important challenge. In this paper, we focus on two diagnostic methods—deuterium-alpha (D α ) spectroscopy and Doppler backscattering (DBS). The former detects ELMs by measuring Balmer alpha emission, while the latter uses microwave radiation to probe the plasma. DBS has the advantages of having a higher temporal resolution and robustness to damage. These advantages of DBS diagnostic may be beneficial for future operational tokamaks, and thus, data processing techniques for DBS should be developed in preparation. In sight of this, we explore the training of neural networks to detect ELMs from DBS data, using D α data as the ground truth. With shots found in the DIII-D database, the model is trained to classify each time step based on the occurrence of an ELM event. The results are promising. When tested on shots similar to those used for training, the model is capable of consistently achieving a high f1-score of 0.93. Furthermore, this score is a performance metric for imbalanced datasets that ranges between 0 and 1. We evaluate the performance of our neural network on a variety of ELMs in different high confinement regimes (grassy ELM, RMP mitigated, and wide-pedestal), finding broad applicability. Beyond ELMs, our work demonstrates the wider feasibility of applying neural networks to data from DBS diagnostic.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

ThunderSecure: deploying real-time intrusion detection for 100G research networks by leveraging stream-based features and one-class classification network

Nowadays, data generated by large-scale scientific experiments are on the scale of petabytes per month. These data are transferred through dedicated high-bandwidth networks (40/100G) across distributed sites for processing, storage, and analysis. Like general purpose networks, research networks experience intrusions. However, monitoring anomalies in such high-speed network traffics is challenging given current cyber-infrastructure. Moreover, traditional network intrusion detection systems (NIDS) are signature based. However, anomaly patterns are difficult to define and that rulesets are often not updated frequently enough to reflect the changes of attack behaviors. We present ThunderSecure, a high-throughput, unsupervised learning-based intrusions detection system for 100G research networks. ThunderSecure implements an efficient packet processing and detection pipeline using multi-cores and GPUs. It extracts statistical and temporal features from real-time network data streams and feeds them to a one-class anomaly detection network. A baseline of normal distribution will be created based on the training observation. Testing traffic deviated from the learned profile will be marked as anomalies. We trained ThunderSecure on hundreds of billions of science data packets mirrored from two 100G network connections at Fermi National Accelerator Laboratory. The detection performance was evaluated on traffic captured from the same research network days and weeks after the training with different types of attack flows injected. Results show that ThunderSecure can recognize science data traffic captured long after the training and made nearly certain detection on the segment of the streams where anomalous flows were injected.

100G research network↗
NASA NTRS1996

Performance Evaluation of Communication Software Systems for Distributed Computing

In recent years there has been an increasing interest in object-oriented distributed computing since it is better quipped to deal with complex systems while providing extensibility, maintainability, and reusability. At the same time, several new high-speed network technologies have emerged for local and wide area networks. However, the performance of networking software is not improving as fast as the networking hardware and the workstation microprocessors. This paper gives an overview and evaluates the performance of the Common Object Request Broker Architecture (CORBA) standard in a distributed computing environment at NASA Ames Research Center. The environment consists of two testbeds of SGI workstations connected by four networks: Ethernet, FDDI, HiPPI, and ATM. The performance results for three communication software systems are presented, analyzed and compared. These systems are: BSD socket programming interface, IONA's Orbix, an implementation of the CORBA specification, and the PVM message passing library. The results show that high-level communication interfaces, such as CORBA and PVM, can achieve reasonable performance under certain conditions.

Fatoohi, Rod↗
DOE OSTI2020

Evaluating factors influencing infrasonic signal detection and automatic processing performance utilizing a regional network

Physical and deployment factors that influence infrasound signal detection and assess automatic detection performance for a regional infrasound network of arrays in the Western U.S. are explored using signatures of ground truth (GT) explosions (yields). Despite these repeated known sources, published infrasound event bulletins contain few GT events. Arrays are primarily distributed toward the south-southeast and south-southwest at distances between 84 and 458 km of the source with one array offering azimuthal resolution toward the northeast. Events occurred throughout the spring, summer, and fall of 2012 with the majority occurring during the summer months. Depending upon the array, automatic detection, which utilizes the adaptive F-detector successfully, identifies between 14% and 80% of the GT events, whereas a subsequent analyst review increases successful detection to 24%–90%. Combined background noise quantification, atmospheric propagation analyses, and comparison of spectral amplitudes determine the mechanisms that contribute to missed detections across the network. This analysis provides an estimate of detector performance across the network, as well as a qualitative assessment of conditions that impact infrasound monitoring capabilities. Finally, the mechanisms that lead to missed detections at individual arrays contribute to network-level estimates of detection capabilities and provide a basis for deployment decisions for regional infrasound arrays in areas of interest.

58 GEOSCIENCES↗
NASA NTRS2017

Design and Benchmarking of a Network-In-the-Loop Simulation for Use in a Hardware-In-the-Loop System

Distributed engine control (DEC) systems alter aircraft engine design constraints be- cause of fundamental differences in the input and output communication between DEC and centralized control architectures. The change in the way communication is implemented may create new optimum engine-aircraft configurations. This paper continues the exploration of digital network communication by demonstrating a Network-In-the-Loop simulation at the NASA Glenn Research Center. This simulation incorporates a real-time network protocol, the Engine Area Distributed Interconnect Network Lite (EADIN Lite), with the Commercial Modular Aero-Propulsion System Simulation 40k (C-MAPSS40k) software. The objective of this study is to assess digital control network impact to the control system. Performance is evaluated relative to a truth model for large transient maneuvers and a typical flight profile for commercial aircraft. Results show that a decrease in network bandwidth from 250 Kbps (sampling all sensors every time step) to 40 Kbps, resulted in very small differences in control system performance.

Networked Systems↗
NASA NTRS2017

Design and Benchmarking of a Network-In-the-Loop Simulation for Use in a Hardware-In-the-Loop System

Distributed engine control (DEC) systems alter aircraft engine design constraints because of fundamental differences in the input and output communication between DEC and centralized control architectures. The change in the way communication is implemented may create new optimum engine-aircraft configurations. This paper continues the exploration of digital network communication by demonstrating a Network-In-the-Loop simulation at the NASA Glenn Research Center. This simulation incorporates a real-time network protocol, the Engine Area Distributed Interconnect Network Lite (EADIN Lite), with the Commercial Modular Aero-Propulsion System Simulation 40k (C-MAPSS40k) software. The objective of this study is to assess digital control network impact to the control system. Performance is evaluated relative to a truth model for large transient maneuvers and a typical flight profile for commercial aircraft. Results show that a decrease in network bandwidth from 250 Kbps (sampling all sensors every time step) to 40 Kbps, resulted in very small differences in control system performance.

Networked Systems↗
NASA NTRS2008

Flight Results of the NF-15B Intelligent Flight Control System (IFCS) Aircraft with Adaptation to a Longitudinally Destabilized Plant

Adaptive flight control systems have the potential to be resilient to extreme changes in airplane behavior. Extreme changes could be a result of a system failure or of damage to the airplane. The goal for the adaptive system is to provide an increase in survivability in the event that these extreme changes occur. A direct adaptive neural-network-based flight control system was developed for the National Aeronautics and Space Administration NF-15B Intelligent Flight Control System airplane. The adaptive element was incorporated into a dynamic inversion controller with explicit reference model-following. As a test the system was subjected to an abrupt change in plant stability simulating a destabilizing failure. Flight evaluations were performed with and without neural network adaptation. The results of these flight tests are presented. Comparison with simulation predictions and analysis of the performance of the adaptation system are discussed. The performance of the adaptation system is assessed in terms of its ability to stabilize the vehicle and reestablish good onboard reference model-following. Flight evaluation with the simulated destabilizing failure and adaptation engaged showed improvement in the vehicle stability margins. The convergent properties of this initial system warrant additional improvement since continued maneuvering caused continued adaptation change. Compared to the non-adaptive system the adaptive system provided better closed-loop behavior with improved matching of the onboard reference model. A detailed discussion of the flight results is presented.

Bosworth, John T.↗
NASA NTRS2012

A Performance Evaluation of NACK-Oriented Protocols as the Foundation of Reliable Delay- Tolerant Networking Convergence Layers

Delay-Tolerant Networking (DTN) is an active area of research in the space communications community. DTN uses a standard layered approach with the Bundle Protocol operating on top of transport layer protocols known as convergence layers that actually transmit the data between nodes. Several different common transport layer protocols have been implemented as convergence layers in DTN implementations including User Datagram Protocol (UDP), Transmission Control Protocol (TCP), and Licklider Transmission Protocol (LTP). The purpose of this paper is to evaluate several stand-alone implementations of negative-acknowledgment based transport layer protocols to determine how they perform in a variety of different link conditions. The transport protocols chosen for this evaluation include Consultative Committee for Space Data Systems (CCSDS) File Delivery Protocol (CFDP), Licklider Transmission Protocol (LTP), NACK-Oriented Reliable Multicast (NORM), and Saratoga. The test parameters that the protocols were subjected to are characteristic of common communications links ranging from terrestrial to cis-lunar and apply different levels of delay, line rate, and error.

Iannicca, Dennis↗
DOE OSTI2021

WIRE: Resource-efficient Scaling with Online Prediction for DAG-based Workflows

This paper introduces WIRE that manages resources for the DAG-based workflows on IaaS clouds. WIRE predicts and plans resources over the MAPE (Monitor-Analyze-Plan-Execute) loops to: 1) Estimate task performance with online data, 2) Conduct simulations to predict the upcoming loads based on online estimates and workflow DAGs, 3) Apply a resource-steering policy to size cloud instance pools for the maximal parallelism that is consistent with low cost. We implement WIRE on Pegasus WMS/HTCondor and evaluate its performance on the ExoGENI network cloud. The results show that WIRE attains low resource cost with the performance that is typically within a factor of two of optimal.

Xie, Bing↗
NASA NTRS1972

Apollo experience report: Electronic systems test program accomplishments and results

A chronological record is presented of the Electronic Systems Test Program from its conception in May 1963 to December 1969. The original concept of the program, which was primarily a spacecraft/Manned Space Flight Network communications system compatibility and performance evaluation, is described. The evolution of these concepts to include various levels of test detail, as well as systems level design verification testing, is discussed. Actual implementation of these concepts is presented, and the facility to support the program is described. Test results are given, and significant contributions to the lunar landing mission are underlined. Plans for modifying the facility and the concepts, based on Apollo experience, are proposed.

Ohnesorge, T. E.↗
NASA NTRS1973

Tracking and data system support for the Mariner Mars 1971 mission. Volume 3: Orbit insertion through end of primary mission

The Tracking and Data System (TDS) Support for the Mariner Mars 1971 Mission final report contains the deep space tracking and data acquisition activities in support of orbital operations. During this period a major NASA objective was accomplished: completion of the 180th revolution and 90th day of data gathering with the spacecraft about the planet Mars. Included are presentations of the TDS flight support pass chronology data for each of the Deep Space Stations used, and performance evaluation for the Deep Space Network Telemetry, Tracking, Command, and Monitor Systems. With the loss of Mariner 8 at launch, Mariner 9 assumed the mission plan of Mariner 8, which included the TV mapping cycles and a 12-hr orbital period. The mission plan was modified as a result of a severe dust storm on the surface of Mars, which delayed the start of the TV mapping cycles. Thus, the end of primary mission date was extended to complete the TV mapping cycles.

Barnum, P. W.↗
NASA NTRS1973

Traffic study of a computer system.

A study which may guide the operations of existing computer installations, as well as the design of future networks, is described. Performance data and evaluations are considered with reference to interarrival time, users' habits, waiting time for execution, time spent in a partition, figures of merit, and states of the system. The analysis of the variables proceeds from examination of typical data with appropriate statistical tests to conclusions about the possible state of nature.

Cramer, R. L.↗
NASA NTRS1996

Research In Nonlinear Flight Control for Tiltrotor Aircraft Operating in the Terminal Area

The research during the first year of the effort focused on the implementation of the recently developed combination of neural net work adaptive control and feedback linearization. At the core of this research is the comprehensive simulation code Generic Tiltrotor Simulator (GTRS) of the XV-15 tilt rotor aircraft. For this research the GTRS code has been ported to a Fortran environment for use on PC. The emphasis of the research is on terminal area approach procedures, including conversion from aircraft to helicopter configuration. This report focuses on the longitudinal control which is the more challenging case for augmentation. Therefore, an attitude command attitude hold (ACAH) control augmentation is considered which is typically used for the pitch channel during approach procedures. To evaluate the performance of the neural network adaptive control architecture it was necessary to develop a set of low order pilot models capable of performing such tasks as, follow desired altitude profiles, follow desired speed profiles, operate on both sides of powercurve, convert, including flaps as well as mastangle changes, operate with different stability and control augmentation system (SCAS) modes. The pilot models are divided in two sets, one for the backside of the powercurve and one for the frontside. These two sets are linearly blended with speed. The mastangle is also scheduled with speed. Different aspects of the proposed architecture for the neural network (NNW) augmented model inversion were also demonstrated. The demonstration involved implementation of a NNW architecture using linearized models from GTRS, including rotor states, to represent the XV-15 at various operating points. The dynamics used for the model inversion were based on the XV-15 operating at 30 Kts, with residualized rotor dynamics, and not including cross coupling between translational and rotational states. The neural network demonstrated ACAH control under various circumstances. Future efforts will include the implementation into the Fortran environment of GTRS, including pilot modeling and NNW augmentation for the lateral channels. These efforts should lead to the development of architectures that will provide for fully automated approach, using similar strategies.

Calise, A. J.↗