SEARCH · Engineering Papers

Results for “learning rate”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,747 records · Page 97

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Hybrid data-driven and model-informed online tool wear detection in milling machines

Precision machining tool wear is responsible for low product throughput and quality. Monitoring the tool wear online is vital to prevent degradation in machining quality. However, direct real-time tool wear measurement is not practical. This paper presents residual-based anomaly detection models, combining a hybrid model comprised of a physics-based model and a data-driven model (a decision tree or a neural network) to predict signals of interest (e.g., power or forces) under nominal conditions, followed by Page’s cumulative sum test for detecting tool wear on-line using the computer numerical control machine measurements. The most informative features are ranked using dynamic programming and its approximation variants from real-time measurements and machine settings, such as the width of cut, depth of cut, feed rate and spindle speed, that serve as inputs to the predictive models. The baseline nominal model is incrementally updated with experimental data via a gradient boosted adaptation model to generate the residuals that account for discrepancies between the actual machine data under normal conditions and the baseline nominal model predictions. The hybrid model is validated against 20 Mazak milling machine experimental tests and one Haas run-to-failure experiment. The proposed anomaly detector is applied to synthetic data from simulations of the physics-based model at different operating conditions, measurement noise levels, and tool wear levels, and the methods were able to achieve an overall 92% accuracy in data with 1% noise. The anomaly detection methods based on hybrid model reduced the false alarms of either the data-driven or physical-based models alone, and are found to be capable of good online detection of tool wear.

42 ENGINEERING↗

NASA NTRSDate not supplied

BioSentinel Deep Space CubeSat Mission

The BioSentinel mission was recently launched aboard the SLS launch vehicle (LV) as part of the Artemis-1 campaign. This 6U CubeSat carries yeast cells to analyze the effects of radiation at large distances from Earth, becoming the first biological payload in Deep Space. Prelaunch activities included mission design updates, orbit determination rehearsals and the development of a tracking schedule in coordination with the Artemis-1 payload office and the Deep Space Network (DSN). An important influence on the trajectories of Artemis I secondaries was the uncertainty associated with deployment from the Interim Cryogenic Propulsion System (ICPS), the upper stage of the SLS LV. The ICPS was rotating at a rate of 1 rpm; there was also uncertainty in the spin axis attitude, which translated into an unknown clock angle of deployment. The variability in this angle and magnitude of deployment implied the existence of a non-negligible risk of a lunar impact, which was evaluated for various potential launch dates. On November 16 th 2022 BioSentinel successfully deployed from ICPS and the navigation team started to receive tracking data from the DSN and ESA antennas. Soon after deployment, the spacecraft was tumbling and entered safe mode. The mission team recovered the spacecraft and after four tracking passes, we solved for a first ephemeris that was sent to the DSN for better tracking of the spacecraft. After propagating this first ephemeris solution, we determined that we avoided impact with a margin of a few hundred km from the lunar surface. More tracking data over the next few days allowed for a more refined orbit solution predicting a periselene altitude of 406 km and a lunar eclipse lasting 36.5 minutes. Therefore, BioSentinel operators avoided any correction maneuvers on the trajectory and successfully tracked and guide the spacecraft. The spacecraft performed a nominal lunar flyby which provided the pertinent energy to achieve a final Earth-trailing heliocentric orbit. Over the course of two weeks, the mission operators corroborated that the subsystems were functioning as expected after the lunar eclipse and the large ΔV incurred. Science operations started once the mission achieved the nominal orbit in Deep Space. This paper discusses in detail the BioSentinel flight performance, as well as the challenges and lessons learned prior to and during this CubeSat mission.

Andres Dono Perez↗

NASA NTRS2022

Europa Clipper Payload Verification and Validation: Avionics-Instrument Interface Test Campaign

NASA's Europa Clipper mission will investigate Jupiter's icy moon Europa using a payload suite consisting of nine instruments to address a range of scientific objectives concerning Europa's habitability. As the project proceeds past its Critical Design Review, confidence is being built in the system's ability to achieve mission objectives through the implementation of a rigorous payload verification and validation (V&V) program. As part of this payload V&V program, instrument box-level testing was performed by the payload team to verify select instrument-avionics interface requirements. This testing was performed at JPL using the avionics testbed's Bulk Data Storage Emulator (BDSEM) with visiting instrument Test Models. This paper summarizes the Data Link test campaign involving roughly four days of functional testing per instrument, including planning, testing methods, types of issues found, and the requirement closure process. Detail is also provided on the development, deployment, and validation of a standardized analysis tool used in data reviews. This testing verified requirements related to commanding rates, loss of link, packet format, clock counters, loopback test capability, and SpaceWire jitter and skew margins. Additional risk reduction testing of basic commanding, counter behavior, science data collection and transfer, and interface swapping was also performed. Because the BDSEM venue was not originally designed to be a run for record venue, the process of characterizing venue fidelity and establishing suitability for requirement closure using data collected in this venue will also be addressed.In order to close requirements, an extensible tool was developed to post-process instrument command and telemetry data from their original binary to a human-readable format and give visibility to errors detected within the data, such as packets with Cyclic Redundancy Check errors. This tool, called payload-packet-parser, is a Python 3.9 command line tool built using a variety of open-source Python libraries. Payload-packet-parser was designed to support parsing command and telemetry packets for all Europa Clipper instruments and additional analysis tools were developed for verification of specific information interface requirements. This test campaign, including post-processing using a single parsing and verification toolset, allowed for early interface testing, alleviating testing burdens on instrument teams and buying down risk on the instrument-avionics interface by finding hardware and software issues and idiosyncrasies prior to integration with system test venues. Over twenty issues were discovered across the payload, resulting in software updates and instrument rework well in advance of any system impacts. This paper concludes with an assessment of benefits and costs of this type of testing and lessons learned.

Montanez, Leticia↗

NASA NTRS1992

Hydrogen leak detection in the Space Shuttle

This study focuses on a helium gas jet flowing into room air. Measurements of helium concentration and velocity in the jet-air mixture are reported. The objective is to learn about jet characteristics so that dynamically similar hydrogen leaks may be located in the Space Shuttle. The hazardous gas detection system (HGDS) in the mobile launch pad uses mass spectrometers to monitor the shuttle environment for leaks. The mass spectrometers are fed by long sample tubes which draw gas from the payload bay, mid body, aft engine compartment and external tank. The overall purpose of this study is to improve the HGDS especially in its potential for locating hydrogen leaks. A rapid-response leak detection experiment was designed, built, and tested, following on the work done in this program last summer. The apparatus included a Perkin Elmer MGA-1200 mass spectrometer and air velocity transducer, both monitored by a Macintosh IIFX computer using LabVIEW software. A jet of helium flowing into the lab air simulated a gas leak. Steady helium or hydrogen-nitrogen jets were logged for concentration and velocity, and the power spectral density of each was computed. Last year, large eddies and vortices were visually seen with Schlieren imaging, and they were detected in the time plots of the various instruments. The response time of the MGA-1200 was found in the range of 0.05 to 0.1 sec. Pulsed concentration waves were clearly detected at 25 cycles per sec by spectral analysis of MGA data. No peaks were detected in the power spectrum, so in the present study, 10 Hz bandwidth-averaged power levels were examined at regular frequency intervals. The practical consequences of last year's study are as follows: sampling frequency should be increased above the present rate of 1 sample per second so that transients could be observed and analyzed with frequency response methods. Many more experiments and conditions were observed in this second summer, including the effects of orifice diameter, jet velocity, sample tube design, radial effects, vertical flow, and low hydrogen concentrations (1 percent). A frequent observation was that the power spectrum, calculated from the Fourier transform of concentration fluctuations, gives a separate piece of information from concentration. Many of the tests suggest that power is high where mixing occurs at the helium-air interface. This fact is apparently independent of the concentration level, which could be high or low, but depends on the sample location relative to the jet (leak) origin, whereas high concentration may be due to a strong leak far away or a small leak close to the sample tube. If the power is low for any concentration level, this would signify helium is arriving at the sample tube by diffusion, not chaotic mixing caused by the jet interaction with air. The practical result is to propose a modification of the HGDL mass spectrometer data sampling and software so that sampling rates could be capable of observing at least 25 Hz fluctuations.

Barile, Ronald G↗

NASA NTRS2016

Human Flight to Lunar and Beyond - Re-Learning Operations Paradigms

For the first time since the Apollo era, NASA is planning on sending astronauts on flights beyond LEO. The Human Space Flight (HSF) program started with a successful initial flight in Earth orbit, in December 2014. The program will continue with two Exploration Missions (EM): EM-1 will be unmanned and EM-2, carrying astronauts, will follow. NASA established a multi-center team to address the communications, and related tacking/navigation needs. This paper will focus on the lessons learned by the team designing the architecture and operations for the missions. Many of these Beyond Earth Orbit lessons had to be re-learned, as the HSF program has operated for many years in Earth orbit. Unlike the Apollo missions that were largely tracked by a dedicated ground network, the HSF planned missions will be tracked (at distances beyond GEO) by the DSN, a network that mostly serves robotic missions. There have been surprising challenges to the DSN as unique modern human spaceflight needs stretch the experience base beyond that of tracking robotic missions in deep space. Close interaction between the DSN and the HSF community to understand the unique needs (e.g. 2-way voice) resulted in a Concept of Operations (ConOps) that leverages both the deep space robotic and the Human LEO experiences. Several examples will be used to highlight the unique challenges the team faced in establishing the communications and tracking capabilities for HSF missions beyond Earth Orbit, including: Navigation. At LEO, HSF missions can rely on GPS devices for orbit determination. For Lunar-and-beyond HSF missions, techniques such as precision 2-way and 3-way Doppler and ranging, Delta-Difference-of-range, and eventually possibly on-board navigation will be used. At the same time, HSF presents a challenge to navigators, beyond those presented by robotic missions - navigating a dynamic/"noisy" spacecraft. Impact of latency - the delay associated with Round-Trip-Light-Time (RTLT). Imagine trying to have a 2-way discussion (audio or video) with an astronaut, with a 2-3 sec or more delay inserted (for lunar distances) or 20 minutes delay (for Mars distances). Balanced communications link. For robotic missions, there has been a heavy emphasis on higher downlink data rates, e.g. bringing back science data. Higher uplink data rates were of secondary importance, as uplink was used only to send commands (and occasionally small files) to the spacecraft. The ratio of downlink-to-uplink data rates was often 10:1 or more. For HSF, a continuous forward link is established and rates for uplink and downlink are more similar.

Kenny, Edward (Ted)↗

DOE OSTI2024

Dynamic data-driven multiscale modeling for predicting the degradation of a 316L stainless steel nuclear cladding material

Here, we have developed a long short-term memory stacked ensemble (LSTM-SE) surrogate modeling approach that can provide rapid predictions of microstructural evolution and the resultant mechanical properties of American Iron and Steel Institute (AISI) 316L series stainless steel (316LSS) fuel cladding under conditions of varying temperature and radiation dose rate. To acquire training data, we developed and implemented a kinetic Monte Carlo (KMC) model to simulate precipitation kinetics of M 23 C 6 , γ', and G phases within SS316L cladding. Experimentally reported precipitation kinetics of SS316L in literature were linked to the kinetic parameters of the simulated precipitation in our KMC model. The model was then used to simulate microstructure evolution under synthetically generated treatments of varying temperature and radiation dose rate, for periods of up to 3000 hours. Changes in volume fraction, number density, and particle size of precipitates were recorded, and particle area fractions were correlated using statistical methods to develop the surrogate model. Simultaneously, the mechanical properties of the simulated microstructures were evaluated using microstructure-based finite element method (FEM) analysis to determine the elastic modulus, yield stress, ultimate tensile strength, and elongation to failure of the aged microstructures. Using this approach, our surrogate model can predict precipitation behavior within 0.25% volume fraction and mechanical properties within 6% relative error from the values predicted by the KMC and FEM models using 50 training simulations as input. The trained recurrent neural network-based model can return estimations of precipitation kinetics and mechanical properties ~1000 times faster than the physics-based codes. This work demonstrates, as a proof of concept, that reactor material service lifetimes under variable service conditions can be predicted for a statistics-based model from a practicably obtainable dataset.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Effect of laser preheat in magnetized liner inertial fusion at OMEGA

Integrated magnetized liner inertial fusion (MagLIF) experiments on the OMEGA laser system are modeled to investigate the effects of laser preheat on implosion performance. In both simulations and experiments, preheating the fuel with a laser enhances the neutron yield, with the maximum yield occurring at an optimal preheat laser energy. Increasing the preheat energy past the optimal value reduces the neutron yield. In simulations, the rate of the drop in neutron yield depends on the inclusion of the Nernst effect. The Nernst effect advects the magnetic field away from the center of the fuel region during the preheat stage of MagLIF on OMEGA and weakens magnetic-flux compression. If the Nernst effect is not included, the simulated drop in yield past the optimal preheat laser energy is more gradual as opposed to the sharper drop seen in experiments. Simulations are able to model trend in measured ion temperatures seen in experiments. Here, a mix model is used to show that including mix from the wall in the simulated fuel region further degrades the yield and lowers the optimal preheat laser energy. Simulations with mix predict that increasing the initial axial magnetic field may still enhance yield performance in integrated implosions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2023

Quantifying the Importance of Selected Drought Indicators for the United States Drought Monitor

Using information theory, our study quantifies the importance of selected indicators for the U.S. Drought Monitor (USDM) maps. We use the technique of mutual information (MI) to measure the importance of any indicator to the USDM, and because MI is derived solely from the data, our findings are independent of any model structure (conceptual, physically-based, or empirical). We also compare these MIs against the drought representation effectiveness ratings in the North America Drought Indices and Indicators Assessment (NADIIA) survey for Koeppen climate zones. This reveals: [1] agreement between some ratings and our MI values (high for example indicators like Standardized Precipitation-Evapotranspiration Index or SPEI); [2] some divergences (for example, soil moisture has high ratings but near-zero MIs for ESA-CCI soil moisture in the Western U.S., indicating the need of another remotely sensed soil moisture source); and [3] new insights into the importance of variables such as Snow Water Equivalent (SWE) that are not included in sources like NADIIA. Further analysis of the MI results yields findings related to: [1] hydrological mechanisms (summertime SWE domination during individual drought events through snowmelt into the water-scarce soil); [2] hydroclimatic types (the top pair of inputs in the Western and non-Western regions are SPEIs and soil moistures respectively); and [3] predictability (high for the California 2012-2017 event, with longer-timescale indicators dominating). Finally, the high MIs between multiple indicators jointly and the USDM indicate potentially high drought forecasting accuracies achievable using only model-based inputs, and the potential for global drought monitoring using only remotely sensed inputs, especially for locations having insufficient in situ observations.

Drought↗

DOE OSTI2020

Applying Improved Optical Recognition with Machine Learning on Sorting Cu Impurities in Steel Scrap

Annually, 20–55 million tons of electronic waste (e-waste) is produced worldwide (5% of all municipal solid waste). Although e-waste embodies only 2% of America’s municipal waste, it accounts for a significantly larger proportion of the heavy metals and flame retardants present in the waste stream. Currently, less than 20% of all e-waste is recycled in the United States because the heterogeneity of the feedstock limits the opportunity for reuse in high value products and processing of the waste itself is often too costly to justify handling. To address this concern, the aims of this study are: 1) to identify the major plastic and metal compositions within electronic shredder residue (ESR), 2) to formulate solvents and processing conditions to separate 90% of the plastics targeted from consumer shred ESR, and 3) to develop a process design model to estimate the cost and energy efficiency of the proposed solvent-based processing. In this study, a pre-sorted heterogeneous ESR feedstock (one where aluminum, magnetic components, and hazardous battery materials removed by an e-waste recycling facility) was used, with the major compositions of the ESR characterized. It was found that 25 wt.% of the feedstock was composed of plastics, 6 wt.% rubber, 27 wt.% printed circuit boards, 23% wire, and the remainder metals and capacitors. Within the plastic portion, polystyrene (PS, 40 wt.%), acrylonitrile butadiene styrene (ABS, 25 wt.%), and styrene-acrylonitrile (SAN, 9wt.%) were identified to compose the majority of the screened plastics using Fourier transform infrared spectroscopy (FTIR). Next, selective solvents were screened using Hansen Solubility Parameter Theory (HSP) for dissolving PS and ABS. The pre-screening results show that methylene chloride (dichloromethane, DCM) and tetrahydrofuran (THF) are capable of dissolving the most PS and ABS, while methanol (MeOH) and ethylene glycol (EG) are capable of precipitating the most PS and ABS. These solvents were subsequently used to recover polymers and remove. flame retardants within the ESR feedstock. By optimizing the dissolution time and the solvents used, the highest polymer dissolution yield (99 wt.%%) was achieved using DCM for 48 hr. Both pre-screened anti-solvents (MeOH and EG) showed the highest polymer precipitation yield (71 wt.%). In terms of flame retardant removal rate, EG was found to have a high phosphorus-containing flame retardant removal rate (up to 98%). Characterization shows that the proposed solvent-based processing can preserve a high molecular weight fraction of the polymers and effectively remove flame retardants. Cost analysis indicates that the amount of the solvent/anti-solvent recovered after the reaction would play a critical role in reducing the operating costs. The energy analysis shows that the proposed solvent-based processes can save up to 60% of the embodied energy used to manufacture plastics used in electronics (PS and ABS were used for calculations). The results from this project prove the potential of solvent-based processing to produce secondary materials (plastics and metals) from e-waste for cross-industry reuse.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Development and Validation of Quantitative Model-Based Image Reconstruction for NDE of Reinforced Steel-Lined Concrete Structures: Kal-El FY 2020

This project studied the capabilities of Model-Based Image Reconstruction (MBIR) and Machine Learning (ML) algorithms in the imaging and estimation of rebar corrosion from ultrasound signals. The application was challenging due to the introduction of a steel liner between the sensor and the concrete containing the rebar. The study focused in a synthetic specimen with a 6.35 mm thick steel liner, and a 19.05 mm diameter rebar at a depth of 44.5 mm and with four levels of corrosion; 0%, 20%, 50%, and 100% corrosion level. The corrosion was applied uniformly around the rebar, generating a ring in the perimeter of the rebar with different acoustic density. In order to generate a realistic synthetic dataset, we added random texture to the concrete of the synthetic specimens. This texture will mimic the variations encountered in real concrete specimens.We adapted our MBIR algorithm for the application and enhanced the algorithm to integrate in the physical model known specimen features, such as the steel liner thickness. The new MBIR method was able to cancel out reverberation from the steel liner and properly image the rebar. In particular, corrosion for the 50% and 100% cases were easily visible and quantitative metrics showed a slight separation for the 0% and 20% levels. The quantitative results were in agreement with the qualitative assessment. We also developed a ML XGBoost model to estimate corrosion level from the ultrasound signals. By combining the ML method with MBIR, we can pinpoint in the ultrasound signals the section that corresponds to the echoes from the rebar. The extract signals are processed by the XGBoost model for prediction. From each system scan, we obtain 15 predictions. The median prediction value is used as the final prediction. The True Acceptance Rate for the method is over 99%.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Robust In-Situ Strain Measurements to Monitor CO 2 Storage

The goal of this project was to develop and demonstrate robust instrumentation to monitor the in-situ strain tensor in order to improve the reliability and security of CO 2 storage in geologic formations. We met the original goals of the project and the major overarching accomplishment is the advancement of strain tensor monitoring from an intriguing concept to a commercially available technology with a solid foundation of novel instruments supported by theoretical analyses and validation experiments. The main accomplishments of the project are summarized below. We designed, built and evaluated nine new optical fiber strainmeters and tiltmeters using Michelson interferometers to measure deformation with ultra-high resolution at both shallow and deep point locations in the subsurface. These are the robust strainmeters that motivated the title of the project. We designed, built and evaluated a novel method of measuring distributed strain in optical fibers with nanostrain resolution, and cm-scale location, and sampling into the seismic band. The new method is called Coherence-length-gated Microwave Photonics Interfereometry (CMPI). CMPI technology has advantages over existing commercial DAS and DSS methods. We developed and demonstrated capabilities to deploy instruments in the field and used them to measure strain caused by ambient signals like barometric pressure and tides, as well as induced signals like surface loading and pore pressure changes from pumping tests. We deployed a working strainmeter at 1,700 ft depth, slightly above an active reservoir. This is to our knowledge the greatest depth a strainmeter has been deployed and the techniques we used can readily be extended to greater depths. Optical fiber borehole tensor strainmeter techology was advanced from a TRL 4 at the start, to a TRL of 7 at the conclusion of the project. The project included advances in simulations and theoretical analyses. We developed and demonstrated a computational workflow that uses machine learning to reduce the computational requirements and make it practical to use Bayesian inversion to solve large numerical poroelastic analyses needed to interpret strain tensor field data. We evaluated the strain tensor fields and time series that would be caused by leaks of CO 2 or other fluids from reservoirs. These simulations demonstrated that signals from leaks could be measured with instruments developed for the project, opening a potentially new method for ensuring storage security. We showed that strains in caprock can be used to estimate pressure in a reservoir. This avoids the need to drill monitoring wells into the reservoir, and it expands the capabilities of monitoring in the caprock. The project includes a derivation and application of a novel analytical solution to the strains in the vicinity of a pressurized poroelastic inclusion. This solution explains field data measured during injeciton tests at the North Avant Field, and it will simplify future interpretation of strain tensor data. The project included a broad range of experiments, and of the most significant is the characterization of the strain tensor at an array three strainmeters during six injection tests at the North Avant Field, Oklahoma. This demonstrated repeatability of the strain signal measured by the new instruments developed for the project, and it showed similarities between the strain signal at shallow depths and pressure in the underlying reservoir. We also demonstrated that useful strain data can be measured at reservoir depths. This confirms that strain tensor data can be measured throughout the caprock over a reservoir. The project demonstrated the feasibility of using the strain tensor and distributed strain measured in caprock during a variety of different well tests where the pumping rate was constant, sinusoidal and positive, or a periodic square wave with zero net rate. This further strengthens the validity of using strain data to characterize reservoirs and aquifers. We also demonstrated that strain caused be fluctuations of air pressure and water pressure in the vadose zone can be measured and interpreted, suggesting that high resolution distributed strain measurements hold promise for monitoring the vadose zone. The project partially supported nine graduate students in the Environmental Engineering, Hydrogeology, Electrical Engineering programs at Clemson University. The research was described in nine journal papers, 23 talks and conference abstracts. Additional journal papers are in preparation. A new company called Tensora was started to provide strainmeter technology for commercial applications.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2026

Stochastic Thermo-Hydro Modeling and Neural Network Surrogate Development for Thermal Resource Assessment of the Galleries-to-Calories Geobattery

The Galleries-to-Calories Geobattery concept explores the use of abandoned coal mine workings for large-scale thermal energy transport and storage. The system involves injecting waste heat from a supercomputing facility into flooded mine galleries, where groundwater flow can store and transport thermal energy for potential recovery in downgradient district heating and cooling applications. To evaluate the feasibility and performance of the Geobattery under geological and operational uncertainty, we developed a suite of stochastic thermo-hydrological (TH) simulations using Monte Carlo sampling of key uncertain parameters (e.g., permeability, porosity, thermal conductivity, specific heat capacity) and operating conditions (e.g., injection rate, injection temperature). Results identified injection rate and temperature as the most influential parameters governing thermal front propagation, while the geometry of the room-and-pillar structure played a critical role in directing the extent and orientation of thermal advancement. Optimal combinations of material properties for maximizing heat recovery were also determined. To address the high computational cost of coupled-process stochastic modeling, we trained a neural network surrogate model on 24,000 physics-based realizations, achieving an R² > 0.99 and MAE < 0.1 for temperature predictions at monitoring locations. This surrogate enabled an additional 100,000 realizations for global sensitivity analysis and probabilistic thermal resource assessment. The integrated stochastic physics–surrogate modeling framework offers a computationally efficient tool for quantifying uncertainty, identifying key drivers, and informing early-stage design decisions for Geobattery systems.

15 - GEOTHERMAL ENERGY↗

NASA NTRS2014

Prediction of Acoustic Environments from Horizontal Rocket Firings

In recent years, advances in research and engineering have led to more powerful launch vehicles which can reach areas of space not yet explored. These more powerful vehicles yield acoustic environments potentially destructive to the vehicle or surrounding structures. Therefore, it has become increasingly important to be able to predict the acoustic environments created by these vehicles in order to avoid structural and/or competent failure. The current industry standard technique for predicting launch-induced acoustic environments was developed by Eldred in the early 1970's and is published in NASA SP-80721. Recent work2 has shown Eldred's technique to be inaccurate for current state-of-the-art launch vehicles. Due to the high cost of full-scale and even sub-scale rocket experiments, very little rocket noise data is available. Furthermore, much of the work thought to be applicable to rocket noise has been done with heated jets. Tam3,4 has done an extensive amount of research on jets of different nozzle exit shape, diameter, velocity, and temperature. Though the values of these parameters, especially exit velocity and temperature, are often very low compared to these values in rockets, a lot can be learned about rocket noise from jet noise literature. The turbulent nature of jet and rocket exhausts is quite similar. Both exhausts contain turbulent structures of varying scale-termed the fine and large scale turbulence by Tam. The finescale turbulence is due to small eddies from the jet plume interacting with the ambient atmosphere. According to Tam et al., the noise radiated by this envelope of small-scale turbulence is statistically isotropic. Hence, one would expect the noise from the small scale turbulence of the jet to be nearly omni-directional. The coherent nature of the large-scale turbulence results in interference of the noise radiated from different spatial locations within the jet. This interference-whether it is constructive or destructive-results in highly directional noise radiation. Tam3 has proposed a model to predict the acoustic environment due to jets and while it works extremely well for jets, it was found to be inappropriate for rockets8. A model to predict the acoustic environment due to a launch vehicle in the far-field which incorporates concepts from both Eldred and Tam was created. This was done using five sets of horizontally fired rocket data, obtained between 2008 and 2012. Three of these rockets use solid propellant and two use liquid propellant. Through scaling analysis, it is shown that liquid and solid rocket motors exhibit similar spectra at similar amplitudes. This model is accurate for these five data sets within 5 dB of the measured data for receiver angles of 30deg to 160deg (with respect to the downstream exhaust centerline). The model uses the following vehicle parameters: nozzle exit diameter and velocity, radial distance from source to receiver, receiver angle, mass flow rate, and acoustic efficiency.

Giacomoni, Clothilde↗

DOE OSTI2022

Limits on Astrophysical Antineutrinos with the KamLAND Experiment

Abstract We report on a search for electron antineutrinos ( ν ¯ e ) from astrophysical sources in the neutrino energy range 8.3–30.8 MeV with the KamLAND detector. In an exposure of 6.72 kton-year of the liquid scintillator, we observe 18 candidate events via the inverse beta decay reaction. Although there is a large background uncertainty from neutral current atmospheric neutrino interactions, we find no significant excess over background model predictions. Assuming several supernova relic neutrino spectra, we give upper flux limits of 60–110 cm −2 s −1 (90% confidence level, CL) in the analysis range and present a model-independent flux. We also set limits on the annihilation rates for light dark matter pairs to neutrino pairs. These data improve on the upper probability limit of 8 B solar neutrinos converting into ν ¯ e , P ν e → ν ¯ e < 3.5 × 10 − 5 (90% CL) assuming an undistorted ν ¯ e shape. This corresponds to a solar ν ¯ e flux of 60 cm −2 s −1 (90% CL) in the analysis energy range.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Numerical analysis of soot emissions from gasoline-ethanol and gasoline-butanol blends under gasoline compression ignition conditions

In the present work, computational fluid dynamics (CFD) simulations of a single-cylinder gasoline compression ignition (GCI) engine were performed to investigate the impact of blending two biofuels, ethanol and n-butanol, with gasoline on the trade-off between combustion phasing and soot emissions under low load conditions. Here, in order to represent market gasoline (RD5-87), a four-component toluene primary reference fuel (TPRF) + ethanol (ETPRF) surrogate (with 20% ethanol by mole; E20) was formulated using a neural network based octane predictor such that the surrogate had the same ethanol content, Research Octane Number (RON) and Octane Sensitivity (S). In addition, a novel skeletal kinetic mechanism for ETPRF and TPRF + n-butanol (BTPRF) blends, incorporating polycyclic aromatic hydrocarbon (PAH) chemistry, was developed. A three-dimensional (3D) engine CFD formulation employing the skeletal mechanism, adaptive mesh refinement (AMR), finite-rate chemistry approach, and hybrid method of moments (HMOM) was adopted to capture the in-cylinder combustion phenomena and soot emissions. The engine CFD model was validated against RD5-87 experimental data for a broad range of start-of-injection (SOI) timings (-21/-27/-36/-45 crank angle degrees (CAD) after top-dead center (aTDC)), with respect to in-cylinder pressure, heat release rate, combustion phasing, and soot emissions. The closed-cycle simulation results were analyzed to elucidate the non-monotonic trend of soot emissions versus SOI timing: SOI-36 > SOI-45 > SOI-21 > SOI-27. Thereafter, the validated CFD model was employed to simulate the combustion of a gasoline-ethanol blend with 45% (by mole) ethanol (E45) and a gasoline-butanol blend with 45% (by mole) n-butanol (B45) under the same operating conditions to study the effects of fuel composition and SOI timing on combustion phasing and soot emissions. The sooting propensity followed the trend: B45 > E20 > E45 at all SOI timings. Overall, it was observed that the autoignition propensity was primarily related to fuel chemistry. On the other hand, sooting propensity showed strong coupling with both fuel chemistry and physical properties, with greater impact of fuel physical properties at advanced SOI timings.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2022

Automated processing of environmental transmission electron microscopy images for quantification of thin film dewetting and carbon nanotube nucleation dynamics

We report scalable production of carbon nanotubes (CNTs) requires catalysts and reaction conditions that provide high nucleation efficiency. In situ characterization methods such as environmental transmission electron microscopy (ETEM) can reveal fundamental mechanisms of synthesis, but to date have primarily provided qualitative observations on small sample sizes. Here, quantitative analysis is performed using high-resolution, high-rate video capture of ETEM experimentation coupled with automated image processing, involving computer vision algorithms and convolutional neural networks. By this approach, we detect distinct nanoparticle formation from an alumina-supported iron thin film and subsequent CNT nucleation from the nanoparticles. The statistical summary of particles in each video shows that, compared to a H 2 -only atmosphere, pretreatment of the catalyst with carbon added to the H 2 atmosphere results in a smaller average particle diameter, a 2-fold increase in particle density (to 5300 particles/μm 2 ), a 3-fold increase in CNT nucleation efficiency (to 92%), and more than a 5-fold increase in CNT density (to 4800/μm 2 ). Addition of carbon during exposure to H 2 is also more effective than NH 3 at dewetting the catalyst film and increasing the CNT nucleation efficiency, in spite of NH 3 being a stronger reducing agent for iron. Insights from this study are applicable to improving CNT yield and productivity in both batch-style and continuous processes.

25 ENERGY STORAGE↗

NASA NTRS1994

Re-engineering Nascom's network management architecture

The development of Nascom systems for ground communications began in 1958 with Project Vanguard. The low-speed systems (rates less than 9.6 Kbs) were developed following existing standards; but, there were no comparable standards for high-speed systems. As a result, these systems were developed using custom protocols and custom hardware. Technology has made enormous strides since the ground support systems were implemented. Standards for computer equipment, software, and high-speed communications exist and the performance of current workstations exceeds that of the mainframes used in the development of the ground systems. Nascom is in the process of upgrading its ground support systems and providing additional services. The Message Switching System (MSS), Communications Address Processor (CAP), and Multiplexer/Demultiplexer (MDM) Automated Control System (MACS) are all examples of Nascom systems developed using standards such as, X-windows, Motif, and Simple Network Management Protocol (SNMP). Also, the Earth Observing System (EOS) Communications (Ecom) project is stressing standards as an integral part of its network. The move towards standards has produced a reduction in development, maintenance, and interoperability costs, while providing operational quality improvement. The Facility and Resource Manager (FARM) project has been established to integrate the Nascom networks and systems into a common network management architecture. The maximization of standards and implementation of computer automation in the architecture will lead to continued cost reductions and increased operational efficiency. The first step has been to derive overall Nascom requirements and identify the functionality common to all the current management systems. The identification of these common functions will enable the reuse of processes in the management architecture and promote increased use of automation throughout the Nascom network. The MSS, CAP, MACS, and Ecom projects have indicated the potential value of commercial-off-the-shelf (COTS) and standards through reduced cost and high quality. The FARM will allow the application of the lessons learned from these projects to all future Nascom systems.

Drake, Brian C.↗

NASA NTRS2006

NASA Crew and Cargo Launch Vehicle Development Approach Builds on Lessons from Past and Present Missions

The United States (US) Vision for Space Exploration, announced in January 2004, outlines the National Aeronautics and Space Administration's (NASA) strategic goals and objectives, including retiring the Space Shuttle and replacing it with new space transportation systems for missions to the Moon, Mars, and beyond. The Crew Exploration Vehicle (CEV) that the new human-rated Crew Launch Vehicle (CLV) lofts into space early next decade will initially ferry astronauts to the International Space Station (ISS) Toward the end of the next decade, a heavy-lift Cargo Launch Vehicle (CaLV) will deliver the Earth Departure Stage (EDS) carrying the Lunar Surface Access Module (LSAM) to low-Earth orbit (LEO), where it will rendezvous with the CEV launched on the CLV and return astronauts to the Moon for the first time in over 30 years. This paper outlines how NASA is building these new space transportation systems on a foundation of legacy technical and management knowledge, using extensive experience gained from past and ongoing launch vehicle programs to maximize its design and development approach, with the objective of reducing total life cycle costs through operational efficiencies such as hardware commonality. For example, the CLV in-line configuration is composed of a 5-segment Reusable Solid Rocket Booster (RSRB), which is an upgrade of the current Space Shuttle 4- segment RSRB, and a new upper stage powered by the liquid oxygen/liquid hydrogen (LOX/LH2) J-2X engine, which is an evolution of the J-2 engine that powered the Apollo Program s Saturn V second and third stages in the 1960s and 1970s. The CaLV configuration consists of a propulsion system composed of two 5-segment RSRBs and a 33- foot core stage that will provide the LOX/LED needed for five commercially available RS-68 main engines. The J-2X also will power the EDS. The Exploration Launch Projects, managed by the Exploration Launch Office located at NASA's Marshall Space Flight Center, is leading the design, development, testing, and operations planning for these new space transportation systems. Utilizing a foundation of heritage hardware and management lessons learned mitigates both technical and programmatic risk. Project engineers and managers work closely with the Space Shuttle Program to transition hardware, infrastructure, and workforce assets to the new launch systems, leveraging a wealth of knowledge from Shuffle operations. In addition, NASA and its industry partners have tapped into valuable Apollo databases and are applying corporate wisdom conveyed firsthand by Apollo-era veterans of America s original Moon missions. Learning from its successes and failures, NASA employs rigorous systems engineering and systems management processes and principles in a disciplined, integrated fashion to further improve the probability of mission success.

Dumbacher, Daniel L.↗