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All sources NASA NTRS DOE OSTI

DOE OSTI2025

Bioenergy pathways within United States net-zero CO 2 emissions scenarios in the Energy Modeling Forum 37 study

The Energy Modeling Forum 37 study is organized around carbon dioxide (CO 2 ) mitigation scenarios reaching net-zero CO 2 emissions by 2050 in the United States. Here, this paper summarizes the potential contribution of bioenergy use in the electric power, transportation, industrial, and buildings sectors toward meeting that target based on model results. Thirteen modeling teams reported bioenergy consumption in the Reference and Net Zero scenarios. Consumption of bioenergy increased over time in the Reference scenario, from an average across models of 3.2 exajoules (EJ) in 2020 to 3.8 EJ in 2050. Average bioenergy consumption in 2050 increased further to 7.3 EJ in the Net Zero scenario. All scenarios that reach net-zero emissions required some form of carbon dioxide removal to offset emissions that are difficult to reduce. Carbon dioxide removal using bioenergy with CO 2 capture and storage (BECCS) varies widely across models, up to 1000 Mt CO 2 in 2050. Some models rely instead on direct air carbon capture and storage (DACCS), up to 2200 Mt CO 2 , and others use a combination of BECCS and DACCS. Model results show a strong inverse relationship between the amounts of BECCS and DACCS deployed. All modeling teams assumed a carbon sink from land use, land use change, and forestry, further offsetting a portion of emissions from fossil fuels and industry that are expensive to eliminate. Bioenergy consumption in 2050 decreased by an average of 1.5 EJ across eight models in a Net Zero+ scenario relative to the Net Zero scenario, due in part to a lower equilibrium carbon price resulting from optimistic cost assumptions for all energy technologies.

09 BIOMASS FUELS↗

DOE OSTI2023

Automated reaction kinetics and network exploration (Arkane): A statistical mechanics, thermodynamics, transition state theory, and master equation software

The open-source statistical mechanics software described here, Arkane–Automated Reaction Kinetics and Network Exploration–facilitates computations of thermodynamic properties of chemical species, high-pressure limit reaction rate coefficients, and pressure-dependent rate coefficient over multi-well molecular potential energy surfaces (PES) including the effects of collisional energy transfer on phenomenological kinetics. Arkane can use estimates to fill in information for molecules or reactions where quantum chemistry information is missing. The software solves the internal energy master equation for complex unimolecular reaction systems. Inputs to the software include converged electronic structure computations performed by the user using a variety of supported software packages (Gaussian, Molpro, Orca, TeraChem, Q-Chem, Psi4). The software outputs high-pressure limit rate coefficients and pressure-dependent phenomenological rate coefficients, as well as computed thermodynamic properties (enthalpy, entropy, and constant pressure heat capacity) with added energy corrections. Some of the key features of Arkane include treatment of 1D, 2D or ND hindered internal rotation modes, treatment of free internal rotation modes, quantum tunneling effect consideration, transition state theory (TST) and Rice-Ramsperger-Kassel-Marcus (RRKM) rate coefficient computations, master equation solution with four implemented methods, inverse-Laplace transform of high-pressure limit rate coefficients into the energy domain, energy corrections based on bond-additivity or isodesmic reactions, automated and efficient PES exploration, and PES sensitivity analysis. The present work describes the design of Arkane, how it should be used, and refers to the theory that it employs. Arkane is distributed via the RMG-Py software suite (https://github.com/ReactionMechanismGenerator/RMG-Py).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1991

A semi-automated process for the production of custom-made shoes

A more efficient, cost-effective and timely way of designing and manufacturing custom footware is needed. A potential solution to this problem lies in the use of computer-aided design and manufacturing (CAD/CAM) techniques in the production of custom shoes. A prototype computer-based system was developed, and the system is primarily a software entity which directs and controls a 3-D scanner, a lathe or milling machine, and a pattern-cutting machine to produce the shoe last and the components to be assembled into a shoe. The steps in this process are: (1) scan the surface of the foot to obtain a 3-D image; (2) thin the foot surface data and create a tiled wire model of the foot; (3) interactively modify the wire model of the foot to produce a model of the shoe last; (4) machine the last; (5) scan the surface of the last and verify that it correctly represents the last model; (6) design cutting patterns for shoe uppers; (7) cut uppers; (8) machine an inverse mold for the shoe innersole/sole combination; (9) mold the innersole/sole; and (10) assemble the shoe. For all its capabilities, this system still requires the direction and assistance of skilled operators, and shoemakers to assemble the shoes. Currently, the system is running on a SUN3/260 workstation with TAAC application accelerator. The software elements of the system are written in either Fortran or C and run under a UNIX operator system.

Farmer, Franklin H.↗

NASA NTRS2000

Freja Studies of the Current-Voltage Relation in Substorm-Related Events

Field-aligned currents and electrostatic potentials play important roles in the coupling between the magnetosphere and the ionosphere. If one assumes that the ionosphere-magnetosphere potential difference is mainly due to the mirror force, one can use the single particle adiabatic kinetic theory to describe the system. From this theory, a linear relationship j(sub II) = KV between field-aligned current density j(sub II) and potential drop V along the same field line can be derived, provided that the potential drop is not too large and not too small. With rare exceptions, observational tests of this relation have mainly concentrated on quiet magnetospheric situations, with acceleration voltages V approx. less than 5 kV. Here we use observations from the Freja satellite of precipitating auroral electrons at 1.700 km altitude to study substorm related events, with acceleration voltages up to 20 keV. The observations are found to be consistent with a linear current-voltage relation even i n these conditions, although with values of the field aligned K lower than previously reported (1-5 x 10(exp 11 S/sq m). This can be explained by lower densities and higher characteristic electron energies in the magnetospheric source region of the precipitating electrons. We analyze the data by three different methods, which are all found to be in general agreement. The results are in agreement with a previous study, where the spectra of precipitating electrons --were indirectly inferred by inversion of data from the EISCAT incoherent scatter radar, thereby validating the use of radar data for studies of auroral electrons. Comparisons with previous studies are made, emphasizing the dependence of the results on the type of auroral structure and magnetospheric conditions.

Olsson, A.↗

NASA NTRS2009

2-Micron Laser Transmitter for Coherent CO2 DIAL Measurement

Carbon dioxide (CO2) has been recognized as one of the most important greenhouse gases. It is essential for the study of global warming to accurately measure the CO2 concentration in the atmosphere and continuously record its variation. A high repetition rate, highly efficient, Q-switched 2-micron laser system as the transmitter of a coherent differential absorption lidar for CO2 measurement has been developed in NASA Langley Research Center. This laser system is capable of making a vertical profiling of CO2 from ground and column measurement of CO2 from air and space-borne platform. The transmitter is a master-slave laser system. The master laser operates in a single frequency, either on-line or off-line of a selected CO2 absorption line. The slave laser is a Q-switched ring-cavity Ho:YLF laser which is pumped by a Tm:fiber laser. The repetition rate can be adjusted from a few hundred Hz to 10 kHz. The injection seeding success rate is from 99.4% to 99.95%. For 1 kHz operation, the output pulse energy is 5.5mJ with the pulse length of ~50 ns. The optical-to-optical efficiency is 39% when the pump power is 14.5W. A Ho:YLF laser operating in the range of 2.05 micrometers can be tuned over several characteristic lines of CO2 absorption. Experimentally, a diode pumped Ho:Tm:YLF laser has been successfully used as the transmitter of coherent differential absorption lidar for the measurement of CO2 with a repetition rate of 5 Hz and pulse energy of 75 mJ. For coherent detection, high repetition rate is required for speckle averaging to obtain highly precise measurements. However, a diode pumped Ho:Tm:YLF laser can not operate in high repetition rate due to the large heat loading and up-conversion. A Tm:fiber laser pumped Ho:YLF laser with low heat loading can operate in high repetition rate. A theoretical model has been established to simulate the performance of Tm:fiber laser pumped Ho:YLF lasers. For continuous wave (CW) operation, high pump intensity with small beam size is suitable for high efficiency. For Q-switched operation, the optimal energy extraction relies on the pump intensity, pump volume, and pump duration which is inversely proportion to the repetition rate. CW and Q-switched Ho:YLF lasers with different linear cavity configurations have been designed and demonstrated for a 30 W Tm:fiber pump laser. The CW Ho laser slope efficiency and optical-to-optical efficiencies reach 65% and 55%, respectively. The pulsed laser efficiency depends on the repetition rate. For 1 kHz operation, the optical-to-optical efficiency is 39% when the pump power is 14.5W. Currently, the injection seeding success rate is between 99.4% and 99.95%. After a ten thousand pulses, the standard deviation of the laser frequency jitter is about 3 MHz. It meets the requirements of highly precise CO2 concentration measurement. In conclusion, an injection seeded, high repetition rate, Q-switched Ho:YLF laser has been developed for a coherent CO2 differential absorption lidar. This master-slave laser system has high optical-to-optical efficiency and seeding success rate. It can potentially meet the requirements of the coherent detection of CO2 concentration by a differential absorption lidar technique.

Singh, Upendra N.↗

DOE OSTI2024

Underground hydrogen storage leakage detection and characterization based on machine learning of sparse seismic data

Underground hydrogen storage (UHS) is considered as a scalable approach for massive storage and seasonal extraction of hydrogen (H 2 ). Although conventional leakage detection and characterization methods based on time-lapse seismic imaging and inversion generally apply to H 2 leakage detection problem, a high-fidelity yet cost effective geophysics approach is still missing to reliably inform leakage location and properties based on very sparse data. In response, we develop a novel supervised machine learning method to detect and characterize H 2 leakage from UHS. The input to our neural network are sparse time-lapse seismic waveforms, while the output from the neural network includes the spatial location and physical properties of a H 2 leakage. Here, we generate high-quality time-lapse waveforms using the elastic-wave equations to train the neural network. We train and validate our machine learning model and find that it attains high accuracy in using extremely sparse time-lapse seismic data to detect and characterize H 2 leakage. Our investigation is the first systematic study that focuses on applying machine learning to subsurface H 2 leakage detection and characterization and could potentially serve as a cost-effective geophysical tool for underground hydrogen leakage detection and characterization with high fidelity.

08 HYDROGEN↗

NASA NTRS2004

Intelligent Control for the BEES Flyer

This paper describes the effort to provide a preliminary capability analysis and a neural network based adaptive flight control system for the JPL-led BEES aircraft project. The BEES flyer was envisioned to be a small, autonomous platform with sensing and control systems mimicking those of biological systems for the purpose of scientific exploration on the surface of Mars. The platform is physically tightly constrained by the necessity of efficient packing within rockets for the trip to Mars. Given the physical constraints, the system is not an ideal configuration for aerodynamics or stability and control. The objectives of this effort are to evaluate the aerodynamics characteristics of the existing design, to make recommendaaons as to potential improvements and to provide a control system that stabilizes the existing aircraft for nominal flight and damaged conditions. Towards this several questions are raised and analyses are presented to arrive at answers to some of the questions raised. CART3D, a high-fidelity inviscid analysis package for conceptual and preliminary aerodynamic design, was used to compute a parametric set of solutions over the expected flight domain. Stability and control derivatives were extracted from the database and integrated with the neural flight control system. The Integrated Vehicle Modeling Environment (IVME) was also used for estimating aircraft geometric, inertial, and aerodynamic characteristics. A generic neural flight control system is used to provide adaptive control without the requirement for extensive gain scheduling or explicit system identification. The neural flight control system uses reference models to specify desired handling qualities in the roll, pitch, and yaw axes, and incorporates both pre-trained and on-line learning neural networks in the inverse model portion of the controller. Results are presented for the BEES aircraft in the subsonic regime for terrestrial and Martian environments.

Krishnakumar, K.↗

NASA NTRS2011

Handling Qualities Evaluations of Low Complexity Model Reference Adaptive Controllers for Reduced Pitch and Roll Damping Scenarios

National Aeronautics and Space Administration (NASA) researchers have conducted a series of flight experiments designed to study the effects of varying levels of adaptive controller complexity on the performance and handling qualities of an aircraft under various simulated failure or damage conditions. A baseline, nonlinear dynamic inversion controller was augmented with three variations of a model reference adaptive control design. The simplest design consisted of a single adaptive parameter in each of the pitch and roll axes computed using a basic gradient-based update law. A second design was built upon the first by increasing the complexity of the update law. The third and most complex design added an additional adaptive parameter to each axis. Flight tests were conducted using NASA s Full-scale Advanced Systems Testbed, a highly modified F-18 aircraft that contains a research flight control system capable of housing advanced flight controls experiments. Each controller was evaluated against a suite of simulated failures and damage ranging from destabilization of the pitch and roll axes to significant coupling between the axes. Two pilots evaluated the three adaptive controllers as well as the non-adaptive baseline controller in a variety of dynamic maneuvers and precision flying tasks designed to uncover potential deficiencies in the handling qualities of the aircraft, and adverse interactions between the pilot and the adaptive controllers. The work was completed as part of the Integrated Resilient Aircraft Control Project under NASA s Aviation Safety Program.

Hanson, Curt↗

NASA NTRSDate not supplied

GMAO OSSE Framework in Support of PBL Mission Science

The planetary boundary layer is the bottom layer of the troposphere where most of human activities take place. Atmospheric pollutants are capped by the temperature inversion layer in PBL. The thickness of PBL, ranging from tens of meter to several kilometer, affects pollutant dispersion and air quality. The thickness of PBL typically shows a strong diurnal cycle but it is difficult to model and predict its change because complicated dynamic and thermodynamic processes involved with air-surface exchange of temperature and moisture, convective mixing, surface friction, topography, advection and radiation heating and cooling influence the PBL height. Various parameterization schemes for PBL were developed but the underlying processes of PBL are neither clearly understood nor represented in NWP models and adding large uncertainty into weather and climate predictions. There are no systematic global observations to provide information on thermodynamic structure of PBL and efforts to explore new spaceborne instruments and measurement techniques are growing. This study aims to develop a PBL OSSE framework leveraging existing GMAO’s OSSE system that utilizes GEOS data assimilation and global forecast model (1) to evaluate existing and potential new observation types for the PBL structure analysis and prediction and (2) to test sensitivity of PBL parameterization schemes to PBL forecasts.

Min-Jeong Kim↗

NASA NTRS2013

Variability of a Stellar Corona on a Time Scale of Days: Evidence for Abundance Fractionation in an Emerging Coronal Active Region

Elemental abundance effects in active coronae have eluded our understanding for almost three decades, since the discovery of the first ionization potential (FIP) effect on the sun. The goal of this paper is to monitor the same coronal structures over a time interval of six days and resolve active regions on a stellar corona through rotational modulation. We report on four iso-phase X-ray spectroscopic observations of the RS CVn binary EI Eri with XMM-Newton, carried out approximately every two days, to match the rotation period of EI Eri. We present an analysis of the thermal and chemical structure of the EI Eri corona as it evolves over the six days. Although the corona is rather steady in its temperature distribution, the emission measure and FIP bias both vary and seem to be correlated. An active region, predating the beginning of the campaign, repeatedly enters into our view at the same phase as it rotates from beyond the stellar limb. As a result, the abundances tend slightly, but consistently, to increase for high FIP elements (an inverse FIP effect) with phase. We estimate the abundance increase of high FIP elements in the active region to be of about 75% over the coronal mean. This observed fractionation of elements in an active region on time scales of days provides circumstantial clues regarding the element enrichment mechanism of non-flaring stellar coronae.

Nordon, R.↗

DOE OSTI2021

Design of High-Performance Lead-Free Quaternary Antiperovskites for Photovoltaics via Ion Type Inversion and Anion Ordering

The emergence of halide double perovskites significantly increases the compositional space for lead-free and air-stable photovoltaic absorbers compared to halide perovskites. Nevertheless, most halide double perovskites exhibit oversized band gaps (>1.9 eV) or dipole-forbidden optical transition, which are unfavorable for efficient single-junction solar cell applications. The current device performance of halide double perovskite is still inferior to that of lead-based halide perovskites, such as CH 3 NH 3 PbI 3 (MAPbI 3 ). Here, by ion type inversion and anion ordering on perovskite lattice sites, two new classes of pnictogen-based quaternary antiperovskites with the formula of X 6 B 2 AA' and X 6 BB'A 2 are designed. Phase stability and tunable band gaps in these quaternary antiperovskites are demonstrated based on first-principles calculations. Further photovoltaic-functionality-directed screening of these materials leads to the discovery of 5 stable compounds (Ca 6 N 2 AsSb, Ca 6 N 2 PSb, Sr 6 N 2 AsSb, Sr 6 N 2 PSb, and Ca 6 NPSb 2 ) with suitable direct band gaps, small carrier effective masses and low exciton binding energies, and dipole-allowed strong optical absorption, which are favorable properties for a photovoltaic absorber material. The calculated theoretical maximum solar cell efficiencies based on these five compounds are all larger than 29%, comparable to or even higher than that of the MAPbI 3 based solar cell. Finally, our work reveals the huge potential of quaternary antiperovskites in the optoelectronic field and provides a new strategy to design lead-free and air-stable perovskite-based photovoltaic absorber materials.

three-dimensional electronic transport↗

DOE OSTI2025

Predicting Dynamic-to-Static Correction Factor from Petrophysical Data and Chemostratigraphy using Unsupervised Machine Learning

Estimating static mechanical properties of stratigraphic layers is critical for optimizing subsurface engineering applications. To estimate dynamic-to-static correction factor F ds (static-to-dynamic Young’s modulus ratio) across the Caney shale interval in Oklahoma, USA, we integrated triaxial test measurements and petrophysical data, including well logs and X-ray fluorescence (XRF) using unsupervised machine learning (ML). We used a novel workflow that includes principal component analysis (PCA) to reduce data set dimensionality of well logs and XRF data sets—both separately and combined—creating three scenarios, and later applied inverse distance weighting (IDW) to derive F ds profiles for these scenarios. Furthermore, we applied K-means clustering on each scenario to predict depositional facies, and built a stiffness zonation profile through chemostratigraphic analysis of the terrigenous elements to validate the predicted F ds . The predicted F ds profile from each scenario using the PCA-IDW method was compared with the constant F ds approach from our previous study by calculating the root mean square error (RMSE). The combined data sets scenario yielded the lowest RMSE value of 0.113, while the RMSE values for the well logs and XRF scenarios were 0.131 and 0.129, respectively. In addition, the predicted F ds from the XRF scenario well-matched the stiffness zonation from the chemostratigraphic analysis that was built using the optimized K-means clustering of nine clusters for that scenario. These methods and findings offer a valuable tool for refining lithological classification and improving the F ds profile, potentially enhancing drilling and stimulation strategies for subsurface energy engineering applications.

clastic rock↗

NASA NTRS1991

Contact control for advanced applications of light weight arms

Many applications of robotic and teleoperated manipulator arms require operation in contact and non-contact regimes. This paper deals with both regimes and the transition between them with special attention given to problems of flexibility in the links and drives. This is referred to as contact control. Inverse dynamics is used to plan the tip motion of the flexible link so that the free motion can stop very near the contact surface without collision due to overshoot. Contact must occur at a very low speed since the high frequency impact forces are too sudden to be affected by any feedback generated torques applied to a joint at the other end of the link. The effect of approach velocity and surface properties are discussed. Force tracking is implemented by commands to the deflection states of the link and the contact force. This enables a natural transition between tip position and tip force control that is not possible when the arm is treated as rigid. The effect of feedback gain, force trajectory, and desired final force are of particular interest and are studied. Experimental results are presented on a one link arm and the system performance in the overall contact task is analyzed. Extension to multi-link cases with potential applications are discussed.

Book, Wayne J.↗

DOE OSTI2023

Fission with Exotic Nuclei (Abbreviated Report)

Nuclear fission is a key mechanism involved in the synthesis of heavy elements in the Cosmos and is the primary explanation for the stability of superheavy elements. Nevertheless, our knowledge of fission remains extremely fragmented. Most experiments have been conducted only on a tiny number of stable actinide nuclei and are often incomplete, leading to gaps in our basic understanding of the process. For many radioactive isotopes, basic fission data such as the charge or mass distribution of the fragments is unknown. These gaps cannot always be filled by simulation alone. Common fission models contain too many free parameters and lack predictive power. In contrast, the fundamental theory of fission under development at LLNL is much more predictive, but its current computational cost is too high to be used extensively for data evaluations. A unique window of opportunity to resolve these limitations has recently opened: the U.S. nuclear science community is ramping up major experimental programs at the Facility for Rare Isotope Beams (FRIB, the DOE flagship facility in low-energy nuclear science), and techniques from machine learning have shown great potential to simplify the use of a fundamental, quantum-mechanical theory of fission. This project has two components. On the experimental side, we acquired and deployed at the HIGS facility a new dual Frisch-Grid ionization chamber to measure correlated fragment-mass, kinetic energy, and angular distributions of fission fragments from induced fission. This new device was used to perform measurements of charge, mass and total kinetic energy of fission fragments in the photofission of 238 U and eight gamma-ray beam energies between 6.2 and 13 MeV, which allowed extracting high-precision independent yields for this reaction. The device was also used to perform measurements of the same quantities in the neutron-induced fission of 234 U with monoenergetic beams of energy between 5 and 8 MeV. In parallel, we collaborated with a team at Commissariat à l’énergie atomique et aux énergies alternatives (CEA) to perform a series of measurements of fission yields in inverse kinematics for the two isotopes of 236 U and 240 Pu. The experiment took place at the Grand Accélérateur National d’Ions Lourds in France in June 2023. The deployment of the VAMOS spectrometer with a new array called PISTA allowed determining the excitation energy of the fissioning system within 1 Mega-electronvolts. The second component of the project involved using deep neural networks to build fast and reliable emulators of our current fission models. In an invited paper published in Frontier in Physics, we showed that autoencoders could successfully compress nuclear wavefunctions in nuclear density functional theory. We achieved a dimensionality reduction of the order of two orders of magnitude while keeping the error in the total energy to less than 0.01%. In a second paper submitted to Physical Review Letters in June 2023 with our collaborators at CEA, we showed that variational autoencoders can learn the collective degrees of freedom driving the fission process.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1994

Influence of ocean surface conditions on atmospheric vertical thermodynamic structure and deep convection

The authors analyze the influence of Sea Surface Temperature (SST) and surface wind divergence on atmospheric thermodynamic structure and the resulting effects on the occurrence of deep convection using National Meteorological Center radiosonde data and International Satellite Cloud Climatology Program data for July 1983-July 1985. The onset of deep convection requires not only the existence of positive convective available potential energy (CAPE), but also an unstable planetary boundary layer (PBL). A stable PBL is observed to suppress deep convection even when CAPE is positive. Variations of SST have a major effect on CAPE, but surface wind divergence can also affect deep convection by changing the lapse rate in the lower troposphere and humidity in the PBL. Specifically, when SST is greater than or equal to 28 C, CAPE is always positive, and surface wind divergence does not qualitatively change the buoyancy profile above the PBL. Strong surface wind divergence, however, stabilizes the PBL so as to suppress the initiation of deep convection. In warm SST regions, CAPE is greater than 0 regardless of assumptions about condensate loading, although the pseudoadiabatic limit is more consistent with the observed deep convection than the reversible moist-adiabatic limit under these circumstances. When SST is less than 27 C, CAPE is usually negative and inhibits convection, but strong surface wind convergence can destabilize the inversion layer and moisten the PBL enough to make the atmosphere neutrally stable in the mean. As a result, deep convection is generally enhanced either when SST is greater than or equal to 28 C in the absence of strong surface wind divergence or when strong surface wind convergence occurs even if SST is less than 27 C. The anomalous suppression of deep convection in the warm area of the equatorial west Pacific lying between the intertropical convergence zone (ITCZ) and south Pacific convergence zone (SPCZ) is probably caused by dryness in the PBL and an inversion in that area. The seasonal cycles of deep convection and surface wind divergence are in phase with the maximum solar radiation and lead SST for one to three months in the central Pacific. The change of PBL relative humidity plays a critical role in the changeover to convective instability in this case. The seasonal change of deep convection and associated clouds seems not to have important effects on the seasonal change of local SST in the central Pacific.

Fu, Rong↗

DOE OSTI2024

Magnetic Field Sensing via Acoustic Sensing Fiber with Metglas® 2605SC Cladding Wires

Magnetic field sensing has the potential to become necessary as a critical tool for long-term subsurface geophysical monitoring. The success of distributed fiber optic sensing for geophysical characterization provides a template for the development of next generation downhole magnetic sensors. In this study, Sentek Instrument’s picoDAS is coupled with a multi-material single mode optical fiber with Metglas® 2605SC cladding wire inclusions for magnetic field detection. The response of acoustic sensing fibers with one and two Metglas® 2605SC cladding wires was evaluated upon exposure to lateral AC magnetic fields. An improved response was demonstrated for a sensing fiber with in-cladding wire following thermal magnetic annealing (~400 °C) under a constant static transverse magnetic field (~200 μT). A minimal detectable magnetic field of ~500 nT was confirmed for a sensing fiber with two 10 μm cladding wires. The successful demonstration of a magnetic field sensing fiber with Metglas® cladding wires fabricated via traditional draw processes sets the stage for distributed measurements and joint inversion as a compliment to distributed fiber optic acoustic sensors.

Dejneka, Zach (ORCID:0000000179415708)↗

NASA NTRS2004

Strategy Developed for Selecting Optimal Sensors for Monitoring Engine Health

Sensor indications during rocket engine operation are the primary means of assessing engine performance and health. Effective selection and location of sensors in the operating engine environment enables accurate real-time condition monitoring and rapid engine controller response to mitigate critical fault conditions. These capabilities are crucial to ensure crew safety and mission success. Effective sensor selection also facilitates postflight condition assessment, which contributes to efficient engine maintenance and reduced operating costs. Under the Next Generation Launch Technology program, the NASA Glenn Research Center, in partnership with Rocketdyne Propulsion and Power, has developed a model-based procedure for systematically selecting an optimal sensor suite for assessing rocket engine system health. This optimization process is termed the systematic sensor selection strategy. Engine health management (EHM) systems generally employ multiple diagnostic procedures including data validation, anomaly detection, fault-isolation, and information fusion. The effectiveness of each diagnostic component is affected by the quality, availability, and compatibility of sensor data. Therefore systematic sensor selection is an enabling technology for EHM. Information in three categories is required by the systematic sensor selection strategy. The first category consists of targeted engine fault information; including the description and estimated risk-reduction factor for each identified fault. Risk-reduction factors are used to define and rank the potential merit of timely fault diagnoses. The second category is composed of candidate sensor information; including type, location, and estimated variance in normal operation. The final category includes the definition of fault scenarios characteristic of each targeted engine fault. These scenarios are defined in terms of engine model hardware parameters. Values of these parameters define engine simulations that generate expected sensor values for targeted fault scenarios. Taken together, this information provides an efficient condensation of the engineering experience and engine flow physics needed for sensor selection. The systematic sensor selection strategy is composed of three primary algorithms. The core of the selection process is a genetic algorithm that iteratively improves a defined quality measure of selected sensor suites. A merit algorithm is employed to compute the quality measure for each test sensor suite presented by the selection process. The quality measure is based on the fidelity of fault detection and the level of fault source discrimination provided by the test sensor suite. An inverse engine model, whose function is to derive hardware performance parameters from sensor data, is an integral part of the merit algorithm. The final component is a statistical evaluation algorithm that characterizes the impact of interference effects, such as control-induced sensor variation and sensor noise, on the probability of fault detection and isolation for optimal and near-optimal sensor suites.

Source record↗

NASA NTRS2000

GPS Sounding Rocket Development at NASA with Simultaneous Multi-Payload Tracking Application

An inverse differential GPS system has been developed for Sounding Rocket use which includes the flight unit and a ground station capable of extracting GPS data from sounding rocket telemetry, performing a real time differential solution and graphically displaying the rocket's path relative to a predicted trajectory plot. Accuracy has been proven to within less than 10 meters. Postprocessing has increased the precision to within 10 - 20 centimeters. The system has been successfully flown several times and delivered to the Sounding Program Office for routine field use. In addition to providing position, velocity and time GPS data has been used on sounding rockets for vehicle performance analysis, effecting a one hundred fold improvement in data time tagging, and steering an optical tracking device to intercept payloads launched from over the horizon. Precise velocity separation information and timing has been provided to multiple payload systems. Future plans include its use for Range Safety and enabling of interferometric techniques. The technology and software developed also has potential application to small satellite navigation and formation flying.

Bull, Barton↗