The Deep Space Network Stability Analyzer
A stability analyzer is described, for testing of NASA Deep Space Network installations during
Stability↗
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Results for “network analyzer”
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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Calibration Procedure for Measuring S-Parameters in Balun Applications on 150-ohm High-Speed Cables
In the radiofrequency (RF) world, in order to characterize cables that do not conform to the typical 50-omega impedance, a time domain reflectometer (TDR) would probably be the simplest and quickest tool to attain this goal. In the real world, not every engineer has a TDR at their disposal; however, they most likely have a network analyzer available. Given a generic 50-omega vector network analyzer (VNA), we would like to make S-parameter measurements for non-50-omega devices (DUTs). For that, we utilize RF balanced/unbalanced transformers (called baluns for short), which are primarily used to match the impedance between the two VNA ports and the DUT's input and output ports, for the two-port S-parameter measurements.
Theofylaktos, Onoufrios↗
Advanced Data Science Model for Detecting Intelligent Malware
This study focused on developing a robust artificial intelligence (AI) model capable of detecting and characterizing advanced malware in Internet of Things (IoT) devices using network data. By analyzing network traffic with various machine learning (ML) models, our AI model can identify and characterize malicious activities to significantly improve malware detection accuracy and reliability as compared to traditional methods. The developed AI/ML model was trained using network data from IoT devices, leveraging classifiers such as Random Forest, Gradient Boosting, AdaBoost, and others to optimize detection performance. This project demonstrates a scalable framework for real-time malware detection and characterization in IoT networks, capable of identifying infected devices and facilitating the necessary steps to remove or isolate them, thereby preventing further infections. Although digital twin (DT) integration is not yet implemented in the current model, it represents a promising future enhancement. By creating a virtual replica of physical IoT devices, DT technology would allow for real-time monitoring and analysis without directly accessing operational technology, thus reducing the risk of compromising or reducing the performance of actual devices. This integration would further enhance the security of IoT ecosystems, combining AI technology to better flag and detect indications of malware-infected devices within a nuclear system environment.
42 ENGINEERING↗
Attenuator, PC-2.92mm, Fixed (Proficiency Test Report; PT ID Number 6679665)
The PSL has reviewed the documentation and data provided by NNSS–Livermore Operations with respect to this proficiency test. This proficiency test was performed to assess NNSS–Livermore Operations’ ability to perform scattering parameter calibrations. The level of documentation was satisfactory. On 12/28/2021, NNSS–Livermore Operations reported the data for the proficiency test conducted on the attenuator. NNSS–Livermore Operations performed this proficiency test using an Anritsu vector network analyzer, an electronic calibration module, and verification kit. The PSL used a Keysight vector network analyzer and mechanical calibration kit. The PSL results included in this proficiency test report were taken on June 23, 2020.
42 ENGINEERING↗
Attenuator, PC-2.92mm, Fixed (Proficiency Test Report: Document # 6679664_11752120)
The PSL has reviewed the documentation and data provided by NNSS–Livermore Operations with respect to this proficiency test. This proficiency test was performed to assess NNSS–Livermore Operations’ ability to perform scattering parameter calibrations. The level of documentation was satisfactory. On 5/19/2020, NNSS–Livermore Operations reported the data for the proficiency test conducted on the attenuator. NNSS–Livermore Operations performed this proficiency test using an Anritsu vector network analyzer, an electronic calibration module, and verification kit. The PSL used a Keysight vector network analyzer and mechanical calibration kit. The PSL results included in this proficiency test report were taken on June 23, 2020.
47 OTHER INSTRUMENTATION↗
Deep Koopman Neural Network for Analyzing High-Energy-Density Simulations of Electrical Wire Explosions
Megaampere-scale electrical wire experiments (EWEs) provide a platform for studying magnetohydrodynamic (MHD) instability growth in magneto-inertial fusion (MIF) devices. Even when nonlinear simulations of these experiments can digitally reproduce much of the experimentally observed instability growth, interpreting the results and understanding mode growth and evolution can be non-trivial. As a first step toward providing better interpretation of these simulation features, this work investigates the use of a deep neural network that uses Koopman operator theory to analyze the dynamics of pulsed-power-driven explosions of EWEs. This deep neural network is trained on 1-D resistive MHD simulations of EWEs. This neural network learns to transform the nonlinear data into a lower-dimensional representation where the time dynamics are linear. Layers of this neural network are shown to learn features of the simulations, including the locations of shock waves and different physical regimes of the simulation. Using the learned features, the network can compress a time state of the simulation consisting of 5120 data point into a 36-parameter lower-dimensional latent space embedding. Furthermore, these embeddings are shown to be clustered in the latent space by initial radius and time state.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Emissivity measurements in thin metallized membrane reflectors used for microwave radiometer sensors
This paper is concerned with electromagnetic losses in metallized films used for inflatable reflectors. An inflatable membrane is made of tough elastic material such as Kapton, and it is not electromagnetically reflective by design. A film of conducting metal is added to the membrane to enhance its reflective properties. Since the impetus for use of inflatables for spacecraft is the light weight and compact packaging, it is important that the metal film be as thin as possible. However, if the material is not conductive or thick enough, the radiation due to the emissivity of the reflector could be a significant part of the radiation gathered by the radiometer. The emissivity would be of little consequence to a radar or solar collector; but for a radiometer whose signal is composed of thermal radiation, this contribution could be severe. Bulk properties of the metal film cannot be used to predict its loss. For this reason, a program of analysis and measurement was undertaken to determine the emissivities of a number of candidate metallized film reflectors. This paper describes the three types of measurements which were performed on the metallized thin films: (1) a network analyzer system with an L-band waveguide; (2) an S-band radiometer; and (3) a network analyzer system with a C-band antenna free-space transmission system.
Schroeder, Lyle C.↗
Jet classification using high-level features from anatomy of top jets
Recent advancements in deep learning models have significantly enhanced jet classification performance by analyzing low-level features (LLFs). However, this approach often leads to less interpretable models, emphasizing the need to understand the decision-making process and to identify the high-level features (HLFs) crucial for explaining jet classification. To address this, we consider the top jet tagging problems and introduce an analysis model (AM) that analyzes selected HLFs designed to capture important features of top jets. Our AM mainly consists of the following three modules: a relation network analyzing two-point energy correlations, mathematical morphology and Minkowski functionals for generalizing jet constituent multiplicities, and a recursive neural network analyzing subjet constituent multiplicity to enhance sensitivity to subjet color charges. We demonstrate that our AM achieves performance comparable to the Particle Transformer (ParT) while requiring fewer computational resources in a comparison of top jet tagging using jets simulated at the hadronic calorimeter angular resolution scale. Furthermore, as a more constrained architecture than ParT, the AM exhibits smaller training uncertainties because of the bias-variance tradeoff. We also compare the information content of AM and ParT by decorrelating the features already learned by AM. Lastly, we briefly comment on the results of AM with finer angular resolution inputs.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Emulation and detection of physical faults and cyber-attacks on building energy systems through real-time hardware-in-the-loop experiments
The increasing use of remote or mobile access, integrated wearable technologies, data exchange, and cloud-based data analytics in modern smart buildings is steering the building industry towards open communication technologies. The increased connectivity and accessibility could lead to more cyber-attacks in smart buildings. On the other hand, physical faults (e.g., HVAC -heating, ventilation, and air-conditioning faults) may have similar adverse impacts as those from the cyber-attacks on building energy systems, such as occupant discomfort, energy wastage, and equipment downtime. However, current physical behavior-based anomaly detection methods fail to differentiate between cyber-attacks and physical faults in building energy systems. Moreover, the challenge in collecting real-world threat data with ground truth has led researchers to rely on numerical models with user-defined assumptions, which may not accurately reflect real-world conditions due to the lack of in-situ experimental datasets. To address these challenges and gaps, this paper presents a flexible hardware-in-the-loop (HIL) testbed for generating cyber-attack and physical fault datasets and demonstrating threat detection algorithms in a real building automation system (BAS) environment. This testbed combines hardware (i.e., real BAS with local HVAC controllers and a physical network) with software (i.e., high-fidelity models to represent behaviors of building envelope and HVAC energy systems), enabling emulations of realistic threats. Five HIL experiments, including one baseline without any threats, two with physical faults, and two with cyber-attacks, were conducted to generate datasets containing detailed network traffic and system states. A joint classification framework, incorporating a network analyzer and a physical HVAC fault detector, was proposed to automatically detect cyber-physical abnormalities on BAS at both the network and the physical HVAC levels. The network analyzer comprises a conditional random fields (CRF) based command validator and a statistics-based detection strategy. The fault detector employs a weather and schedule-based pattern matching and feature-based principal component analysis (WPM-FPCA) method. Evaluation of the classification using four metrics from the multi-class confusion matrix revealed an average accuracy of 90.2%, recall of 89.7%, precision of 88.5% and F1-score of 89.2%. Finally, these results demonstrate that the proposed joint classification framework can effectively differentiate between specific types of cyber-attacks (e.g., device reinitialization attack, network Denial-of-Service attack) and physical faults (e.g., air handling unit operational fault, cooling coil valve stuck) in real time for improved building energy management.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Securing Grid-interactive Efficient Buildings (GEB) through Cyber Defense and Resilient System (CYDRES)
The DOE CYDRES project is driven by the urgent need to address critical research gaps in the domain of cyber-physical security of smart buildings, including Grid-interactive Efficient Buildings (GEBs). CYDRES, a real-time advanced building resilient platform, aims to enhance the cyber-attack-immune capabilities of buildings through multi-layered prevention, detection, and adaptation mechanisms. CYDRES consists of five key modules: a multi-layer network analyzer, an Automatic Fault Detection, Diagnosis, and Prognosis (AFDDP) framework, an intelligent mode selector, a cyber-resilient control framework, and a situation awareness platform. The Network Analyzer employs a data-driven framework that includes a protocol state learning tool and a CRF (Conditional Random Field) command validator. In Hardware-In-the-Loop (HIL) testbeds, it achieved 100% detection accuracy with a false alarm rate of 3%, validating its efficacy in identifying selected cyber-attacks. The AFDDP framework leverages pattern matching, PCA (Principal Component Analysis)-based strategies, and a DBN (Dynamic Bayesian Network)-based fault diagnosis approach to pinpoint the causes of physical system abnormalities using Building Automation System (BAS) data. In HIL experiments, the AFDDP module attained a detection accuracy of over 95% with a false alarm rate below 7%. Additionally, the fault detector utilized machine learning (Random Forest) and deep learning (Multi-Layer Perceptron) methods with acoustic sensor data to achieve a 100% fault detection accuracy in Heating, Ventilation, and Air-Conditioning (HVAC) equipment. The Mode Selector offered real-time impact analysis, allowing immediate actions to protect BASs in the face of emerging threats. The cyber-resilient control framework included an adaptive Model Predictive Control (MPC) and a measurement compensator, reducing temperature violations by up to 94% and improving the total demand flexibility by up to 70% in HIL experiments. Such HIL experiments covered a cyber-attack case and a physical fault case, showcasing CYDRES’ efficiency in maintaining operational continuity during threats. The situation awareness platform in Grafana enhanced real-time threat detection and response visualization, augmenting the operational awareness for building operators. CYDRES demonstrated high technical effectiveness in various test scenarios, particularly in HIL environments. The project's phased development approach ensured efficient use of resources, highlighting its practical feasibility and readiness for commercialization. By enhancing the security and resilience of building operations, CYDRES represents a significant advance in mitigating risks associated with cyber-physical systems, thereby enhancing public confidence in the safety of modern building infrastructure. Future directions for the project include expanding testing protocols, refining AFDDP methodologies, exploring more comprehensive resilient control strategies, and testing in real commercial buildings.
42 ENGINEERING↗
Series tee splitter for impedance measurements
A series tee splitter comprises a primary electromagnetic transmission line and a secondary electromagnetic transmission line that is placed in a series path with the primary electromagnetic transmission line, wherein a load is attached to the end of the secondary electromagnetic transmission line and a network analyzer is connected to opposite ends of the primary electromagnetic transmission line to measure a load impedance. This configuration increases the high impedance measurement limit of the network analyzer normally seen for reflection measurements. The series tee splitter can be electrically small to provide broadband impedance information.
Halligan, Matthew↗
Metriwave final report
The superconductor-insulator-superconductor (SIS) mixer is a device which is being used in the construction of very sensitive receivers in the millimeter and submillimeter wavelength regions. With its potential for conversion gain and quantum-limited performance, it is becoming a device of prime importance in radio astronomy as well as earth and planetary atmospheric research. Many of the parameters of the SIS mixer cannot be readily measured in the laboratory, however, since most commercially available test instruments use test signal powers large enough to saturate or destroy SIS junctions. Detailed here is the construction of a microwave network analyzer with extremely low test signal powers. The results of a development performed by Dynamics Technology, Inc., under a Phase 2 SBIR contract from NASA (NAS7-1025) are documented. The work resulted in a network analyzer to be delivered to workers at the Jet Propulsion Laboratory, which should be capable of SIS mixer characterization in support of their ongoing work in this area.
Williams, Wyman↗
Measurements of complex permittivity of microwave substrates in the 20 to 300 K temperature range from 26.5 to 40.0 GHz
A knowledge of the dielectric properties of microwave substrates at low temperatures is useful in the design of superconducting microwave circuits. Results are reported for a study of the complex permittivity of sapphire (Al2O3), magnesium oxide (MgO), silicon oxide (SiO2), lanthanum aluminate (LaAlO3), and zirconium oxide (ZrO2), in the 20 to 300 Kelvin temperature range, at frequencies from 26.5 to 40.0 GHz. The values of the real and imaginary parts of the complex permittivity were obtained from the scattering parameters, which were measured using a HP-8510 automatic network analyzer. For these measurements, the samples were mounted on the cold head of a helium gas closed cycle refrigerator, in a specially designed vacuum chamber. An arrangement of wave guides, with mica windows, was used to connect the cooling system to the network analyzer. A decrease in the value of the real part of the complex permittivity of these substrates, with decreasing temperature, was observed. For MgO and Al2O3, the decrease from room temperature to 20 K was of 7 and 15 percent, respectively. For LaAlO3, it decreased by 14 percent, for ZrO2 by 15 percent, and for SiO2 by 2 percent, in the above mentioned temperature range.
Miranda, Felix A.↗
Measurements of complex permittivity of microwave substrates in the 20 to 300 K temperature range from 26.5 to 40.0 GHz
A knowledge of the dielectric properties of microwve substrates at low temperatures is useful in the design of superconducting microwave circuits. Results are reported for a study of the complex permittivity of sapphire (Al2O3), magnesium oxide (MgO), silicon oxide (SiO2), lanthanum aluminate (LaAlO3), and zirconium oxide (ZrO2), in the 20 to 300 Kelvin temperature range, at frequencies from 26.5 to 40.0 GHz. The values of the real and imaginary parts of the complex permittivity were obtained from the scattering parameters, which were measured using an HP-8510 automatic network analyzer. For these measurements, the samples were mounted on the cold head of a helium gas closed cycle refrigerator, in a specially designated vacuum chamber. An arrangement of wave guides, with mica windows, was used to connect the cooling system to the network analyzer. A decrease in the value of the real part of the complex permittivity of these substrates, with decreasing temperature, was observed. For MgO and Al2O3, the decrease from room temperature to 20 K was of 7 and 15 percent, respectively. For LaAlO3, it decreased by 14 percent, for ZrO2 by 15 percent, and for SiO2 by 2 percent, in the above mentioned temperature range.
Miranda, Felix A.↗
Probe Station Antenna Range
This summer I was given the task of programming a Probe Station to collect near field antenna patterns and convert them to far field patterns. The purpose of this project is to provide NASA with another means of antenna characterizing. Currently, NASA Glenn can measure near field and far field patterns of many different types of antennas. The antennas targeted for this lab are small patch antennas at high frequencies that require probe biasing. The Probe Station contains two probes for RF signals and another two for DC Biasing. The way this lab works is as follows: A patch antenna is placed on the probe station and biased properly for testing. This antenna is known as the Antenna Under Test (AUT). The AUT is supplied with an RF signal from a probe that is connected to a network analyzer. Above the AUT hangs a probe for measuring the electric field emitted by the AUT. The probe is controlled by four axis. The axis of movements for this probe are back and forth, left and right, up and down, and rotation. The network analyzer and axis controllers are tied into a computer for reading commands and recording data. The probe scans a rectangular pattern above the AUT to measure the electric field emitted by the AUT. This data is then recorded and analyzed back at the computer.
Zaman, Afroz↗
Equipment for On-Wafer Testing From 220 to 325 GHz
A system of electronic instrumentation, constituting the equivalent of a two-port vector network analyzer, has been developed for use in on-wafer measurement of key electrical characteristics of semiconductor devices at frequencies from 220 to 325 GHz. A prior system designed according to similar principles was reported in Equipment for On-Wafer Testing at Frequencies Up to 220 GHz (NPO-20760), NASA Tech Briefs, Vol. 25, No. 11 (November 2001), page 42. As one would expect, a major source of difficulty in progressing to the present higher-frequency-range system was the need for greater mechanical precision as wavelengths shorten into the millimeter range, approaching the scale of mechanical tolerances of prior systems. The system (see figure) includes both commercial off-the-shelf and custom equipment. As in the system of the cited prior article, the equipment includes test sets that are extended versions of commercial network analyzers that function in a lower frequency range. The extension to the higher frequency range is accomplished by use of custom frequency-extension modules that contain frequency multipliers and harmonic mixers. On-wafer measurement is made possible by waveguide wafer probes that were custom designed and built for this wavelength range, plus an on-wafer calibration substrate designed for use with these probes. In this case, the calibration substrate was specially fabricated by laser milling. The system was used to make the first on-wafer measurements of a semiconductor device in the frequency range from 220 to 320 GHz. Some of the measurement results showed that the device had gain.
Samoska, Lorene↗
High-Temperature Probe Station Developed to Characterize Microwave Devices Through 500 C
A photograph and a block diagram of the high-temperature probe station are shown. The system consists of the ceramic heater mounted on a NASA shuttle tile insulator, a direct current power supply, a personal-computer-based data acquisition and temperature controller, microwave probes, a microscope, and a network analyzer. The ability to perform microwave tests at high temperatures is becoming necessary. There is now a need for sensors and communication circuits that can operate at 500 C and above for aircraft engine development and monitoring during flight. To address this need, researchers have fabricated devices using wide bandgap semiconductors such as SiC with targeted operating temperatures of 500 to 600 C. However, the microwave properties of these devices often change drastically with temperature, so any designs that are intended to be used in such an environment must be characterized at high temperatures. For some reliability, lifetime, and direct-current testing, the device under test can be packaged and characterized in an oven. However, for RF and microwave measurements, it is usually not possible to establish a calibrated reference plane at the device terminals within a package. In addition, the characteristics of the package would vary over a 500 C temperature range, and this would have to be accounted for when the data were analyzed. A high temperature probe station allows circuits and devices to be characterized through on wafer measurements across a broad temperature range with known reference plane. The conventional, commercially available thermal wafer-probe stations that are used to evaluate microwave devices across a controlled temperature range have a typical upper limit of 200 C. Standalone thermal heating chucks are available with an extended upper temperature range of 300 to 400 C. To effectively characterize devices at temperatures up to and surpassing 500 C, Glenn researchers developed a custom probe station. In the past, custom probe stations have been developed to test devices under other extreme environments, such as cryogenic temperatures as low as 37 K. Similarly, this custom probe station was specifically modified for high-temperature use. It allows devices to be measured quickly and flexibly, without the use of wire bonds and test fixtures. The probe station is shown making scattering parameter measurements from 1 to 50 GHz with a Hewlett-Packard 8510C Network Analyzer. There is a half-wafer of silicon directly on top of the heater to provide a uniform heated platform for our sample. A quarter wafer of silicon carbide forms the substrate for our test circuit of several transmission lines.
Downey, Alan N.↗
System for Automated Calibration of Vector Modulators
Vector modulators are used to impose baseband modulation on RF signals, but non-ideal behavior limits the overall performance. The non-ideal behavior of the vector modulator is compensated using data collected with the use of an automated test system driven by a LabVIEW program that systematically applies thousands of control-signal values to the device under test and collects RF measurement data. The technology innovation automates several steps in the process. First, an automated test system, using computer controlled digital-to-analog converters (DACs) and a computer-controlled vector network analyzer (VNA) systematically can apply different I and Q signals (which represent the complex number by which the RF signal is multiplied) to the vector modulator under test (VMUT), while measuring the RF performance specifically, gain and phase. The automated test system uses the LabVIEW software to control the test equipment, collect the data, and write it to a file. The input to the Lab - VIEW program is either user-input for systematic variation, or is provided in a file containing specific test values that should be fed to the VMUT. The output file contains both the control signals and the measured data. The second step is to post-process the file to determine the correction functions as needed. The result of the entire process is a tabular representation, which allows translation of a desired I/Q value to the required analog control signals to produce a particular RF behavior. In some applications, corrected performance is needed only for a limited range. If the vector modulator is being used as a phase shifter, there is only a need to correct I and Q values that represent points on a circle, not the entire plane. This innovation has been used to calibrate 2-GHz MMIC (monolithic microwave integrated circuit) vector modulators in the High EIRP Cluster Array project (EIRP is high effective isotropic radiated power). These calibrations were then used to create correction tables to allow the commanding of the phase shift in each of four channels used as a phased array for beam steering of a Ka-band (32-GHz) signal. The system also was the basis of a breadboard electronic beam steering system. In this breadboard, the goal was not to make systematic measurements of the properties of a vector modulator, but to drive the breadboard with a series of test patterns varying in phase and amplitude. This is essentially the same calibration process, but with the difference that the data collection process is oriented toward collecting breadboard performance, rather than the measurement of output from a network analyzer.
Lux, James↗