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At least 289 records · Page 16

Broadband electrostatic noise and field-aligned currents in Jupiter's middle magnetosphere

Voyager 1 plasma wave observations have revealed the presence of an impulsive electrostatic emission localized to the Jovian middle magnetosphere that appears on the edges of the plasma sheet. This plasma mode has the same spectral and morphological characteristics of an emission that has been extensively studied in the earth's magnetosphere and has been associated with the presence of field-aligned currents. The results of a detailed study of the properties of this Jovian emission are presented by using comparisons with terrestrial observations as a basis for mode identification. The occurrence regions of the waves are compared with the measured magnetic field configuration to establish a correspondence with the plasma sheet. It is argued that this is a quasi-permanent global system of field-aligned currents linking the ionosphere of Jupiter to the middle magnetosphere, which powers energetic plasma heating processes occurring there. On the basis of knowledge of the consequences of field-aligned currents in the terrestrial magnetosphere, a scenario for acceleration/precipitation of inverted V electrons, concomitant aurorae, and energetic (approximately 10 keV) proton deposition into the middle magnetosphere resulting from field-aligned potential drops associated with this current system is suggested.

Barbosa, D. D.↗

Integration of a DER Management System in Riverside. Final report

The tasks in this project covered various aspects, including algorithm development, algorithm integration into a commercial Active Network Management (ANM) platform, hardware-in-the-loop (HIL) testing in an industry-standard testing platform, pilot demonstration in Riverside, California, and also cost and benefit analysis. The DERMS platform in this project can host different algorithms developed on different platforms (e.g., MATLAB and Python) and it can interact with different hardware devices (e.g., different PV inverters, battery inverters, and different sensors). The DER control solution are based on an advanced model-free, layered, and clustered DER control paradigm. At the core of the DER control algorithms was the concept of Extremum Seeking (ES), which is a model-free probing-based control technique. The ES-based control algorithms were tested on major real-world inverters; both individually and in a cluster. It was shown that even legacy equipment (or when paired with a few additional advanced equipment) can support such advanced control. The monitoring algorithms utilize a heterogeneous set of legacy and advanced sensor measurements, such as behind-the-meter DER sensors, distribution-level Phase Measurement Units, distribution-substation Supervisory Control and Data Acquisition (SCADA), and line current sensors, with their limited availability; in order to infer practical network conditions. Sensor data are utilized to achieve resource forecasting, phase identification, and distribution system state estimation. The technology that was developed and demonstrated in this project could be transformational to utilities, including the smaller municipal utilities such as in Riverside, which may not have the resources to deploy advanced distribution system and DERMS solutions in order to support high penetration of solar power integration. This project created a real-world prototype to provide utilities with an assessment of smart grid monitoring and control technologies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

An architecture for object-oriented intelligent control of power systems in space

A control system for autonomous distribution and control of electrical power during space missions is being developed. This system should free the astronauts from localizing faults and reconfiguring loads if problems with the power distribution and generation components occur. The control system uses an object-oriented simulation model of the power system and first principle knowledge to detect, identify, and isolate faults. Each power system component is represented as a separate object with knowledge of its normal behavior. The reasoning process takes place at three different levels of abstraction: the Physical Component Model (PCM) level, the Electrical Equivalent Model (EEM) level, and the Functional System Model (FSM) level, with the PCM the lowest level of abstraction and the FSM the highest. At the EEM level the power system components are reasoned about as their electrical equivalents, e.g, a resistive load is thought of as a resistor. However, at the PCM level detailed knowledge about the component's specific characteristics is taken into account. The FSM level models the system at the subsystem level, a level appropriate for reconfiguration and scheduling. The control system operates in two modes, a reactive and a proactive mode, simultaneously. In the reactive mode the control system receives measurement data from the power system and compares these values with values determined through simulation to detect the existence of a fault. The nature of the fault is then identified through a model-based reasoning process using mainly the EEM. Compound component models are constructed at the EEM level and used in the fault identification process. In the proactive mode the reasoning takes place at the PCM level. Individual components determine their future health status using a physical model and measured historical data. In case changes in the health status seem imminent the component warns the control system about its impending failure. The fault isolation process uses the FSM level for its reasoning base.

Holmquist, Sven G.↗

Demonstration of the feasibility of an integrated x ray laboratory for planetary exploration

The identification of minerals and elemental compositions is an important component in the geological and exobiological exploration of the solar system. X ray diffraction and fluorescence are common techniques for obtaining these data. The feasibility of combining these analytical techniques in an integrated x ray laboratory compatible with the volume, mass, and power constraints imposed by many planetary missions was demonstrated. Breadboard level hardware was developed to cover the range of diffraction lines produced by minerals, clays, and amorphous; and to detect the x ray fluorescence emissions of elements from carbon through uranium. These breadboard modules were fabricated and used to demonstrate the ability to detect elements and minerals. Additional effort is required to establish the detection limits of the breadboard modules and to integrate diffraction and fluorescence techniques into a single unit. It was concluded that this integrated x ray laboratory capability will be a valuable tool in the geological and exobiological exploration of the solar system.

Franco, E. D.↗

Ultra Long-Lived, Self-Surveying Autonomous Air Quality Sensing - Executive Summary

We set out to evolve ultra-low power air quality sensing technologies developed at JSC to add a highly accurate positioning sensor based on SBIR technology to give a self-surveying air quality monitoring platform with years-long lifetime on a small, disposable coin cell battery. Using Radio Frequency Identification (RFID) technology for data transport, the system can take advantage of RFID-based inventory management systems in place on lunar exploration assets to provide this capability with extremely small SWAP impacts. Years-long operational lifetimes enable flexible, autonomous environmental monitoring during lengthy intervals between and unprecedented situational awareness during crewed missions. Software integration of the localization system into the JSC RFID sensing platform was advanced, but the COVID-19 pandemic complicated and slowed maturation of the localization system SBIR product, and center closure indefinitely deferred a final hardware integration and system demonstration. In the meantime, progress was made to mature the air-quality sensing platform for flight, including hardware, software, antenna, and mechanical improvements. The underlying RFID sensing capability was also adapted to a drawer motion sensing system, which is currently (FY21) being taken toward an ISS flight demonstration as part of the RFID Enhanced Autonomous Logistics Management (REALM)-3 experiment.

Raymond Summers Wagner↗

Identification of Rotorcraft Structural Dynamics from Flight and Wind Tunnel Data

Excessive vibration remains one one of the most difficult problems that faces the helicopter industry today, affecting all production helicopters at some phase of their development. Vibrations in rotating structures may arise from external periodic dynamic airloads whose frequencies are are close to the natural frequencies of the rotating system itself. The goal for the structures engineer would thus be to design a structure as free from resonance effects as possible. In the case of a helicopter rotor blade these dynamic loads are a consequence of asymmetric airload distribution on the rotor blade in forward flight, leading to a rich collection of higher harmonic airloads that force rotor and airframe response. Accurate prediction of the dynamic characteristics of a helicopter rotor blade will provide the opportunity to affect in a positive manner noise intensity, vibration level, durability, reliability and operating costs by reducing objectionable frequencies or moving them to a different frequency range and thus providing us with a lower vibration rotor. In fact, the dynamic characteristics tend to define the operating limits of a rotorcraft. As computing power has increased greatly over the last decade, researchers and engineers have turned to analyzing the vibrational characteristics of aerospace structures at the design and development stage of the production of an aircraft. Modern rotor blade construction methods lead to products with low mass and low inherent damping so careful design and analysis is required to avoid resonance and an undesirable dynamic performance. In addition, accurate modal analysis is necessary for several current approaches in elastic system identification and active control.

McKillip, Robert M., Jr.↗

Time series modeling of human operator dynamics in manual control tasks

A time-series technique is presented for identifying the dynamic characteristics of the human operator in manual control tasks from relatively short records of experimental data. Control of system excitation signals used in the identification is not required. The approach is a multi-channel identification technique for modeling multi-input/multi-output situations. The method presented includes statistical tests for validity, is designed for digital computation, and yields estimates for the frequency responses of the human operator. A comprehensive relative power analysis may also be performed for validated models. This method is applied to several sets of experimental data; the results are discussed and shown to compare favorably with previous research findings. New results are also presented for a multi-input task that has not been previously modeled to demonstrate the strengths of the method.

Biezad, D. J.↗

Time Series Modeling of Human Operator Dynamics in Manual Control Tasks

A time-series technique is presented for identifying the dynamic characteristics of the human operator in manual control tasks from relatively short records of experimental data. Control of system excitation signals used in the identification is not required. The approach is a multi-channel identification technique for modeling multi-input/multi-output situations. The method presented includes statistical tests for validity, is designed for digital computation, and yields estimates for the frequency response of the human operator. A comprehensive relative power analysis may also be performed for validated models. This method is applied to several sets of experimental data; the results are discussed and shown to compare favorably with previous research findings. New results are also presented for a multi-input task that was previously modeled to demonstrate the strengths of the method.

Biezad, D. J.↗

Remote Thermal IR Spectroscopy of our Solar System

Indirect methods to detect extrasolar planets have been successful in identifying a number of stars with companion planets. No direct detection of an extrasolar planet has yet been reported. Spectroscopy in the thermal infrared region provides a potentially powerful approach to detection and characterization of planets and planetary systems. We can use knowledge of our own solar system, its planets and their atmospheres to model spectral characteristics of planets around other stars. Spectra derived from modeling our own solar system seen from an extrasolar perspective can be used to constrain detection strategies, identification of planetary class (terrestrial vs. gaseous) and retrieval of chemical, thermal and dynamical information. Emission from planets in our solar system peaks in the thermal infrared region, approximately 10 - 30 microns, substantially displaced from the maximum of the much brighter solar emission in the visible near 0.5 microns. This fact provides a relatively good contrast ratio to discriminate between stellar (solar) and planetary emission and optimize the delectability of planetary spectra. Important molecular constituents in planetary atmospheres have rotational-vibrational spectra in the thermal infrared region. Spectra from these molecules have been well characterized in the laboratory and studied in the atmospheres of solar system planets from ground-based and space platforms. The best example of such measurements are the studies with Fourier transform spectrometers, the Infrared Interferometer Spectrometers (IRIS), from spacecraft: Earth observed from NIMBUS 8, Mars observed from Mariner 9, and the outer planets observed from Voyager spacecraft. An Earth-like planet is characterized by atmospheric spectra of ozone, carbon dioxide, and water. Terrestrial planets have oxidizing atmospheres which are easily distinguished from reducing atmospheres of gaseous giant planets which lack oxygen-bearing species and are characterized by spectra containing hydrocarbons such as methane and ethane. Spectroscopic information on extrasolar planets thus can permit their classification. Spectra and spectral lines contain information on the temperature structure of the atmosphere. Line and band spectra can be used to identify the molecular constituents and retrieve species abundances, thereby classifying and characterizing the planet. At high enough spectral resolution characteristic planetary atmospheric dynamics and unique phenomena such as failure of local thermodynamic equilibrium can be identified. Dynamically induced effects such as planetary rotation and orbital velocity shift and change the shape of spectral features and must be modeled in detailed spectral studies. We will use our knowledge of the compositional, thermal and dynamical characteristics of planetary atmospheres in our own solar system to model spectra observed remotely on similar planets in extrasolar planetary systems. We will use a detailed radiative transfer and beam integration program developed for the modeling and interpretation of thermal infrared spectra measured from nearby planet planets to generate models of an extra-solar "Earth" and "Jupiter". From these models we will show how key spectral features distinguish between terrestrial and gaseous planets, what information can be obtained with different spectral resolution, what spectral features can be used to search for conditions for biogenic activity, and how dynamics and distance modify the observed spectra. We also will look at unique planetary phenomena such as atmospheric lasing and discuss their utility as probes for detection and identification of planets. Results of such studies will provide information to constrain design for instrumentation needed to directly detect extrasolar planets.

Kostiuk, Theodor↗

The Soft X-Ray Variability and Spectrum of 1H0419-577 from a Long EUVE Observation

The active galaxy associated with the hard X-ray source 1H0419-577 was observed with Extreme Ultraviolet Explorer Satellite (EUVE) for about 25 days to obtain a long, contiguous light curve and an Extreme Ultraviolet Radiation (EUV) spectrum. An EUV source was detected which was about as bright as the AGN and was later identified as an AM Her type system. The AGN showed variations as large as a factor of two over 5-10 day time scales and occasionally varied by 20-30% in less than 0.5day. The spectrum is dominated by a continuum that is poorly fit by a simple power law. There are possible emission lines without positive identifications but the lines are likely to be spurious.

Marshall, H. L.↗

The Soft X-Ray Variability and Spectrum of 1H0419-577 from a Long EUVE Observation

The active galaxy associated with the hard X-ray source 1H0419-577 was observed with EUVE (Extreme Ultraviolet Explorer Satellite) for about 25 days to obtain a long, contiguous light curve and an EUV spectrum. An EUV source was detected which was about as bright as the AGN (Active Galactic Nuclei) and was later identified as an AM Her type system. The AGN showed variations as large as a factor of two over 5-10 day time scales and occasionally varied by 20-30% in less than 0.5day. The spectrum is dominated by a continuum that is poorly fit by a simple power law. There are possible emission lines without positive identifications but the lines are likely to be spurious.

Marshall, H. L.↗

Measurement Protocols for In situ Analysis of Organic Compounds at Mars and Comets

The determination of the abundance and chemical and isotopic composition of organic molecules in comets and those that might be found in protected environments at Mars is a first step toward understanding prebiotic chemistries on these solar system bodies. While future sample return missions from Mars and comets will enable detailed chemical and isotopic analysis with a wide range of analytical techniques, precursor insitu investigations can complement these missions and facilitate the identification of optimal sites for sample return. Robust automated experiments that make efficient use of limited spacecraft power, mass, and data volume resources are required for use by insitu missions. Within these constraints we continue to explore a range of instrument techniques and measurement protocols that can maximize the return from such insitu investigations.

Mahaffy, P. R.↗

Measurement Protocols for In Situ Analysis of Organic Compounds at Mars and Comets

The determination of the abundance and chemical and isotopic composition of organic molecules in comets and those that might be found in protected environments at Mars is a first step toward understanding prebiotic chemistries on these solar system bodies. While future sample return missions from Mars and comets will enable detailed chemical and isotopic analysis with a wide range of analytical techniques, precursor insitu investigations can complement these missions and facilitate the identification of optimal sites for sample return. Robust automated experiments that make efficient use of limited spacecraft power, mass, and data volume resources are required for use by insitu missions. Within these constraints we continue to explore a range of instrument techniques and measurement protocols that can maximize the return from such insitu investigations.

Mahaffy, P. R.↗

Identification of natural frequencies and modal damping ratios of aerospace structures from response data

An analysis of one and multidegree of freedom systems with classical damping is presented. Definition and minimization of error functions for each system are discussed. Systems with classical and nonclassical normal modes are studied, and results for first order perturbation are given. An alternative method of matching power spectral densities is provided, and numerical results are reviewed.

Michalopoulos, C. D.↗

Optimization-based control using input convex neural networks

Input convex neural networks (ICNNs) are a family of deep learning models where the outputs are constructed to be convex functions of the inputs. By parameterizing system models using ICNNs, optimization-based control problems can be solved as convex optimization problems, leading to improved performance and robustness. This work proposes a novel framework where the control objective function and constraints are modelled using ICNNs. A case study of optimization-based control with output constraints is conducted on a process with input multiplicity and nonminimum phase behavior. The simulation results demonstrate improved economic yield compared with normal neural networks. Additionally, the input convexity formulation is compared with simple regularization techniques, and unique benefits such as improved data efficiency and robustness of the proposed formulation are shown. Finally, by explicitly incorporating prior knowledge about convexity, this framework provides a good balance between the universal approximation power of deep learning and computational feasibility required by control.

42 ENGINEERING↗

Detecting multi‐scale riverine topographic variability and its influence on Chinook salmon habitat selection

Abstract Quantifying geomorphic conditions that impact riverine ecosystems is critical in river management due to degraded riverine habitat, changing flow and thermal conditions, and increasing anthropogenic pressure. Geomorphic complexity at different scales directly impacts habitat heterogeneity and affects aquatic biodiversity resilience. Here we showed that the combination of continuous spatial survey at high resolution, topobathymetric light detection and ranging (LiDAR), and continuous wavelet analysis can help identify and characterize that complexity. We used a continuous wavelet analysis on 1‐m resolution topobathymetry in three rivers in the Salmon River Basin, Idaho (USA), to identify different scales of topographic variability and the potential effects of this variability on salmonid redd site selection. On each river, wavelet scales characterized the topographic variability by portraying repeating patterns in the longitudinal profile. We found three major representative spatial wavelet scales of topographic variability in each river: a small wavelet scale associated with local morphology such as pools and riffles, a mid‐wavelet scale that identified larger channel unit features, and a large wavelet scale related to valley‐scale controls. The small wavelet scale was used to identify pools and riffles along the entire lengths of each river as well as areas with differing riffle‐pool development. Areas along the rivers with high local topographic variability (high wavelet power) at all wavelet scales contained the largest features (i.e., deepest or longest pools) in the systems. By comparing the wavelet power for each wavelet scale to Chinook salmon redd locations, we found that higher small‐scale wavelet power, which is related to pool‐riffle topography, is important for redd site selection. The continuous wavelet methodology objectively identified scales of topographic variability present in these rivers, performed efficient channel‐unit identification, and provided geomorphic assessment without laborious field surveys.

Duffin, Jenna↗

Molecular structure retrieval directly from laboratory-frame photoelectron spectra in laser-induced electron diffraction

Ubiquitous to most molecular scattering methods is the challenge to retrieve bond distance and angle from the scattering signals since this requires convergence of pattern matching algorithms or fitting methods. This problem is typically exacerbated when imaging larger molecules or for dynamic systems with little a priori knowledge. Here, we employ laser-induced electron diffraction (LIED) which is a powerful means to determine the precise atomic configuration of an isolated gas-phase molecule with picometre spatial and attosecond temporal precision. We introduce a simple molecular retrieval method, which is based only on the identification of critical points in the oscillating molecular interference scattering signal that is extracted directly from the laboratory-frame photoelectron spectrum. The method is compared with a Fourier-based retrieval method, and we show that both methods correctly retrieve the asymmetrically stretched and bent field-dressed configuration of the asymmetric top molecule carbonyl sulfide (OCS), which is confirmed by our quantum-classical calculations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

CalWave Open Water Demo - FMEA Update Budget Period 2

The Failure Modes and Effects Analysis (FMEA) is a qualitative reliability technique for systematically analyzing each possible failure mode within a hardware system, and identifying the resulting effect on that system, the mission, and the personnel. This submission includes an updated FMEA summary for CalWave's open water demonstration including pre- and post-mitigation results, hazard identification (HAZID) analysis, and component/function rooted FMEA.

16 TIDAL AND WAVE POWER↗