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At least 559 records · Page 31

Alert Timing Assessment for Unmanned Aircraft System Terminal Area Operations

A Detect and Avoid (DAA) system is an essential enabler for integrating Unmanned Aircraft Systems (UAS) into the U.S. National Airspace System. A DAA system uses a suite of sensors, trackers and alerting and guidance algorithms to assist a remote pilot in maintaining separation from airborne traffic. The initial minimum performance standards focused on en route operations; in order to facilitate operations in and around the airport environment, this paper presents the derivation of the early alert threshold for UAS terminal operations.

Unmanned Aircraft Systems↗

Design of a Manufacturing Demonstration Unit for a Composite Lunar Landing Gear Strut

The goal of the current work was to develop an analytical framework for design of composite struts using various levels of model fidelity. Rapid optimization trade studies were performed using low fidelity two-dimensional (2D) axisymmetric models with smeared composite properties. The optimum 2D model was compared with three-dimensional (3D) models with higher levels of fidelity in material property representation. Good agreement was found with all models. The buckling performance of the highest fidelity 3D model was found to be satisfactory for the intended loading conditions. An additional goal of this work was to perform an initial assessment of using automated fiber placement (AFP) and other advanced manufacturing methods to explore their feasibility for the fabrication of struts for lunar landers, strut-braced wings, and other aerospace components. The designs produced during this study are intended to be used to develop manufacturing demonstration units (MDU) that can be fabricated at the Integrated Structural Assembly of Advanced Composites (ISAAC) facility at Langley Research Center (LaRC) and tested in lab facilities at LaRC.

carbon-epoxy↗

Design of a Manufacturing Demonstration Unit for a Composite Lunar Landing Gear Strut

The goal of the current work was to develop an analytical framework for design of composite struts using various levels of model fidelity. Rapid optimization trade studies were performed using low fidelity two-dimensional (2D) axisymmetric models with smeared composite properties. The optimum 2D model was compared with three-dimensional (3D) models with higher levels of fidelity in material property representation. Good agreement was found with all models. The buckling performance of the highest fidelity 3D model was found to be satisfactory for the intended loading conditions. An additional goal of this work was to perform an initial assessment of using automated fiber placement (AFP) and other advanced manufacturing methods to explore their feasibility for the fabrication of struts for lunar landers, strut-braced wings, and other aerospace components. The designs produced during this study are intended to be used to develop manufacturing demonstration units (MDU) that can be fabricated at the Integrated Structural Assembly of Advanced Composites (ISAAC) facility at Langley Research Center (LaRC) and tested in lab facilities at LaRC.

carbon-epoxy↗

MAB Phase Ceramics for Lunar Applications

During the ten-week internship my work focused on designing characterization protocol for 3D printed MAB phase ceramics on steel and Tiplates. I was mentored by Dr. Samuel Hocker of NASA and advised by Dr. Gupta from University of North Dakota. I also collaborated with Mackenzie Short from the University of North Dakota. The characterization protocol was divided into following steps; initially, we performed visual inspection of the plates. During this process, the coatings which spalled or delaminated were discarded for further evaluation. During the next step, we performed optical microscopy to discern and document surface features and porosities of the samples. We also noted some decomposition under the optical microscope as well. Thereafter, profilometry analysis was performed to understand the effect of power density on the surface roughness. Due to the deposited powder over the samples, the profilometry was inconclusive. We then cleaned the samples on the steel plate using ethanol and cotton swabs to wipe up the loose powder covering the samples. Detailed SEM analysis was then performed on the cleaned specimens. In parallel, the 3D printed samples on the Tiplate were cleaned by using an ultrasonic bath for 1h. Optical imaging showed that this cleaning process was more effective for cleaning except that small cracks propagated through the layered ceramics. The profilometry data gathered on the titanium plate after cleaning was more conclusive. The SEM data on the steel plate showed that there is decomposition at all wattages although at 100 W the extent of decomposition was lower. We are planning to characterize the steel samples after cleaning in ultrasonic bath for 5-10 min to minimize cracking during the cleaning process. In addition, we are also planning to study the fractured surface by SEM analysis.

Additive Manufacturing, Laser Powder Bed Fusion, S↗

Using Trajectory Smoothness Metrics to Identify Drones in Radar Track Data

The identification of unmanned aircraft systems (UAS) using trajectory data is considered. Specifically, a number of smoothness metrics are proposed, which can be used to distinguish UAS from other aerial objects even when they are engaged in accelerative maneuvers (non-constant-velocity flight). The metrics are evaluated on a data set from a UAS sense-and-avoid field test, which contains track data of aerial objects recorded by a vehicle-board radar system during a flight test. The metrics are found to effectively differentiate UAS from other objects such as birds for this data set. In addition, an initial statistical performance analysis of one of the smoothness metrics is undertaken, using 15 data sets deriving from multiple flight tests. The smoothness metric is shown to identify the target UAS with 95% accuracy (95% true positive rate), while achieving a false positive rate of less than 9%.

Sandip Roy↗

Impact of 3D Structure on Magnetic Reconnection

Results from 2.5D and 3D studies of the onset and development of the tearing instability are presented, using high fidelity resistive MHD simulations. A limited parameter study of the strength of the reconnecting field (or shear angle) was performed. An initially simple 1D equilibrium was used, consisting of a modified force-free current sheet, with periodic boundary conditions in all directions. In all cases, the linear and nonlinear evolution led to a primary current sheet between two large flux ropes. The global reconnection rate during this later stage was analyzed in all simulations. It was found that in 2.5D the primary current sheet fragmented owing to plasmoids, and as expected, the global reconnection rate, calculated using multiple methods, increases with the strength of the reconnecting field owing to a stronger Alfvén speed. In 3D, the presence of interacting oblique modes of the tearing instability complicates the simple 2.5D picture, entangling the magnetic field of the inflow and introducing a negative effect on the reconnection rate. The two competing effects of stronger Alfvén speed and entangling, which both increase with the strength of the reconnecting field, resulted in a decrease in the reconnection rate with increasing reconnecting field. For all simulations, the 3D rates were less than in 2.5D but suggest that as one goes to weak reconnecting field (or strong guide field) the system becomes more 2.5D-like and the 2.5D and 3D rates converge. These results have relevance to situations like nanoflare heating and flare current sheets in the corona.

Lars K S Daldorff↗

Advances in PSP Testing in LaRC High Reynolds Number Facilities

The use of luminescent coatings for the global measurement of surface aerodynamic properties at full-flight Reynolds numbers has been ongoing at the NASA Langley Research Center since the late 1990s, beginning with Temperature Sensitive Paint (TSP) for boundary layer analysis at the 0.3-m Transonic Cryogenics Tunnel. Since then, significant work has been made to extend these measurements to pressure using Pressure Sensitive Paint (PSP) as well as develop systems for application in larger scale, full-flight Reynolds number facilities, such as the National Transonic Facility (NTF). Recently, a system for the measurement of time-resolved pressure using recently developed unsteady PSP (uPSP) formulations has been designed and implemented in the Transonic Dynamics Tunnel (TDT). The use of PSP (or uPSP) in either of these large scale, full-fight Reynolds number wind tunnels is complicated by the fact that both facilities operate best in oxygen deficient environments; however, the PSP technique relies on the presence of oxygen to work. The NTF is typically operated in cryogenic conditions, which is achieved using liquid nitrogen. In this facility, temperatures can reach as low as 116 K (-250 °F) with nominal oxygen concentrations of less than 50 ppm. This has resulted in the development of specialized PSP formulations that can operate in the cryogenic environment with the introduction of low amounts of oxygen (typically less than 2000 ppm) for PSP response. Likewise, to achieve full-flight Reynolds number conditions in the TDT, the atmosphere in the tunnel is replaced with a “heavy gas” of R-134A (1,1,1,2-tetrafluoroethane), which also has minimal oxygen native in the flow. The use of uPSP in this case will also depend on the introduction of trace amounts of oxygen, with the precise concentrations to be determined in an upcoming test. This presentation will describe some recent advancements that have been made for PSP measurements in both facilities. For the NTF system, there has been significant development of enhanced lighting for use at cryogenic conditions, as well as improvements in the application efficiency of the PSP. Furthermore, there are efforts underway to incorporate advanced data analysis techniques to acquire additional surface aerodynamic properties using the PSP technique that can yield not only improved experimental efficiency, but also provide data needed for next generation vehicle design and development. For the uPSP system in TDT, significant efforts to improve the data transfer rates to a high-performance computing environment for analysis are underway and performance and initial results from the system in the heavy-gas environment will be presented.

Pressure Sensitive Paint↗

Second-generation Micro-Spec: Spectrometer Design for the Experiment for Cryogenic Large-Aperture Intensity Mapping

Micro-Spec (μ-Spec) is a direct-detection spectrometer that integrates all the components of a diffraction-grating spectrometer onto a ∼10-cm2 chip using superconducting microstrip transmission lines on a single-crystal silicon substrate. The second-generation μ-Spec has been designed to operate with a spectral resolution of ∼512 in the far-infrared and submillimeter (420–540 GHz, 714–555 μm) wavelength range, a band of interest for NASA’s EXperiment for Cryogenic Large-Aperture Intensity Mapping (EXCLAIM). EXCLAIM will be a high-altitude balloon mission that is being designed to map the emission of redshifted carbon monoxide and singly-ionized carbon lines over a redshift range 0 < z < 3.5. EXCLAIM will be the first demonstration of the μ-Spec technology in a space-like environment. This work reviews the status of the μ-Spec design for the EXCLAIM instrument, with emphasis on the spectrometer’s two-dimensional diffractive region, through which light of different wavelengths is focused on microwave kinetic inductance detectors (MKIDs) along the spectrometer focal plane. An optimization process generates a geometrical configuration of the diffractive region that satisfies specific requirements on size, operating spectral range and performance. An initial optical design optimized for EXCLAIM is presented in terms of geometric layout, spectral purity and efficiency.

Giuseppe Cataldo↗

Uncertainty Improvement in the NASA Glenn Research Center 8- by 6-Foot Supersonic Wind Tunnel

Within the past decade, a measurement uncertainty analysis (MUA) team was assembled at the NASA Glenn Research Center to assist the wind tunnel characterization team with quantification of uncertainty estimates for variables of interest in wind tunnels and test cells across the center. The initial analysis performed by the team was conducted on the 8- by 6- Foot Supersonic Wind Tunnel using results from the 1996/97 full calibration test entry. These MUA results were published in 2016 which included recommendations for methods to improve the uncertainty estimates for various variables of interest, such as changes to regression models, tunnel operation philosophy, and instrumentation choices. The wind tunnel characterization team utilized the proposed methods in 2019 during a full characterization test entry. Following publication of the 2019 test section characterization results, the MUA team pursued an update to the uncertainty estimates for the facility, which validated previous recommendations and revealed significantly reduced systematic uncertainties across most variables of interest. Inclusion of within-test repeat points in the 2019 test entry allowed for higher fidelity estimates of random uncertainty to be generated, as well. This collaboration between the facility, wind tunnel characterization, and MUA teams serves as an example of the data quality benefits that can be achieved through rigorous analysis of the sources of uncertainty in a ground-test facility.

Uncertainty↗

Uncertainty Improvement in the NASA Glenn Research Center 8- by 6-Foot Supersonic Wind Tunnel

Within the past decade, a measurement uncertainty analysis (MUA) team was assembled at NASA Glenn Research Center to assist the wind tunnel characterization team with quantification of uncertainty estimates for variables of interest in wind tunnels and test cells across the center. The initial analysis performed by the team was conducted on the 8- by 6-Foot Supersonic Wind Tunnel using results from the 1996/97 full calibration test entry. These MUA results were published in 2016 which included recommendations for methods to improve the uncertainty estimates for various variables of interest, such as changes to regression models, tunnel operation philosophy, and instrumentation choices. The wind tunnel characterization team utilized the proposed methods in 2019 during a full characterization test entry. Following publication of the 2019 test section characterization results, the MUA team pursued an update to the uncertainty estimates for the facility, which validated previous recommendations and revealed significantly reduced systematic uncertainties across most variables of interest. Inclusion of within-test repeat points in the 2019 test entry allowed for higher fidelity estimates of random uncertainty to be generated, as well. This collaboration between the facility, wind tunnel characterization, and MUA teams serves as an example of the data quality benefits that can be achieved through rigorous analysis of the sources of uncertainty in a ground-test facility.

Uncertainty↗

Clifford Neural Operators on Atmospheric Data Influenced Partial Differential Equations

Mathematical representations of the atmosphere are key to forecasting and research tasks across Earth science. Numerically solving the underlying partial differential equations(PDEs) of the atmosphere, however, can be difficult and computationally expensive with numerous trade-offs between computing efficiency and accuracy. Utilizing neural net-works to learn approximations of the PDE solutions from the data can help us model complex phenomena more efficiently than traditional numerical schemes. Here, we have applied Clifford algebra-based neural operators for predicting atmospheric variables. Clifford Fourier neural operators are used with two different backbone architectures, ResNet and UNet, on custom data of U10, V10 and surface pressure as well as U500, V500 and Z500. Clifford Fourier neural operators, coupled with ResNet and UNet architectures, are applied to a key reanalysis dataset. Model performance is initially strong, but we observe increasing errors, resulting in the model becoming highly unstable.

Sujit Roy↗

12-kW Advanced Electric Propulsion System Hall Current Thruster Qualification and Production Status

The AEPS contract was awarded to AR in May of 2016 with the goal of developing a 12.5kW Hall Thruster System, including the Hall Current Thruster (HCT), Power Processor Unit (PPU) and Xenon Flow Controller (XFC). It was originally targeted to support the Asteroid Redirect Mission, which was cancelled early in the project. The project was subsequently restructured to support the Gateway PPE propulsion mission, with modified scope that consisted of the development, qualification and delivery of three 12kW flight thrusters. The PPU and XFC components were designed and development hardware fabricated with initial testing performed prior to being de-scoped from the contract. System level testing was performed by AR using these engineering components in early 2022 at the Aerospace Corporation’s EP-3 test facility.

Hall thruster↗

Development of Solar Flare and Energetic Particle Prediction Portal (SEP 3 )

Solar activity is a primary factor determining the state of the Earth’s space environment, geomagnetic and ionospheric disturbances, and radiation hazards. In the current state of knowledge, machine learning (ML) methods provide essential tools for processing data, investigating relationships among various physical properties and characteristics, uncovering hidden connections, and predicting hazardous solar events. The primary difficulty in developing and applying modern machine-learning tools in heliophysics is that the essential data are scattered among over a hundred data repositories developed by instrument teams of space missions and ground-based observatories. In addition, statistical and ML methods require long time series of homogeneous measurements. To facilitate ML-ready data preparation and access, we have developed an interactive database of solar flares integrating the most essential datasets (https://solarflare.njit.edu/). The database performs an initial data processing and is automatically updated. In addition, we are developing the Solar Energetic Particle Prediction Portal (SEP3, https://sun.njit.edu/SEP3), which hosts web applications that allow users to retrieve the database records. The Portal has a search page for browsing the events from the most widely used catalogs and a dedicated space to share the most recent achievements of the team. The interactive widget can display soft X-ray and proton flux time series from GOES satellites and the flare records. The data portal has been used to evaluate the forecasts of solar proton events and investigate machine-learning approaches to SEP prediction.

SMD↗

Dynamic System Scaling Applied to Zr-4 Cladding under RIA Conditions

The research and development lifecycle for new fuel designs currently has an ideal 20-25 year timeline. Efforts are currrently underway to accelerate fuel design and development using high performance fuel modeling codes and reduced scale experiments with new instrumentation techniques. However current tools available require a full scale prototype to be designed and tested for fuel qualification. The thermal-hydraulics community has leveraged scaling methodologies to use reduced scale integral effect test facilities (Westinghouse AP600/1000, NuScale Power Module) in lieu of building full scale prototypes for reactor design certification. Dynamic System Scaling (DSS) is a recent development to scaling methodologies that enable the tracking and quantification of dynamic scaling distortions experienced throughout a transient. Recent TREAT experiments performed reactivity initiated accident (RIA) pulses on UO2 fuel rodlets in Zr-4 cladding and were accompanied by BISON predictions for the cladding temperature. DSS is applied to pyrometer data of outer cladding temperatures and two BISON predictions after peak cladding temperature has been reached. One BISON case uses a constant gap conductance value between the fuel and cladding and the other using a conventional gap conductance model. Results from the DSS analysis show that there is good agreement between both BISON predictions and the experimental data and that there is not a significant distortion seen between using either gap conductance model.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

PV Lifetime Project (2021 NREL Annual Report)

DOE's PV Lifetime project was initiated in 2016 with the goal of accurately characterizing the early-life evolution of photovoltaic (PV) field performance. Different PV cell and module technologies result in different initial performance loss rates due to effects like light-induced degradation (LID) and light & elevated temperature-induced degradation (LeTID). To accurately characterize the initial field performance loss requires the use of high-accuracy indoor IV curve measurements at standard test conditions. Therefore, PV modules involved in this study are removed from the field once or twice per year and brought indoors for measurement. Current samples deployed and monitored in this way include Jinko Solar (2016), Trina Solar (2016), Hanwha Q-Cells (2017), Panasonic (2018), LG (2018), Canadian Solar (2018), Mission Solar (2019). More recently, modules from Sunpreme (2019), and LONGi (2020) have been deployed but not yet analyzed. Overall annual performance loss rates are as follows: our first modules to be deployed (Jinko and Trina) have annual median performance loss rate between -0.4%/yr and -0.9%/yr, mainly concentrated in the first year. The QCells mono-PERC and multi-PERC modules have an annual degradation rate of -0.76%/yr and -0.69%/yr respectively, also concentrated in the first year of operation. Panasonic and LG modules displayed negligible performance loss in the past two years, at 0.1%/yr and -0.0%/yr respectively. They also were the only modules with initial IV curve measurements consistently above the nameplate rating. Possibly relatedly, these are also the only two N-type silicon module types analyzed so far. Canadian Solar multi-PERC modules demonstrated a -1.3%/yr degradation rate which actually accelerated in the past year, so this will be a module type to monitor in future years. Mission Solar modules exhibited strong recoverable performance loss, consistent with LeTID susceptibility. (The same is true for the Jinko JKM260 module type). Annual performance loss actually showed improvement in time at +0.3%/yr after 2 years in the field, although the module initially was measured at 3% below nameplate rating. These modules could therefore be experiencing a form of post-LeTID recovery. Initial measurements have been conducted on the next two module types - Sunpreme n-HIT and LONGi bifacial mono-PERC. We will report on initial year-1 performance change for these modules in the next PV Lifetime annual report. For the remaining modules, an additional year of field exposure will provide greater certainty in annual degradation rates, particularly for those with degradation concentrated in the initial year of field deployment.

14 SOLAR ENERGY↗

Performance characteristics of a laser-initiated NASA Standard Initiator

The Ensign-Bickford Company has been actively involved in the design and development of a laser equivalent to the electrically initiated NASA Standard Initiator (NSI). The purpose of this paper is to describe the present design and its performance characteristics. Recommendations for advancement of this program are also presented.

Graham, John A.↗

Field-based AFDD for refrigerant undercharge in residential HVAC systems: enhancing reliability through false alarm mitigation

This study evaluated rule-based and machine learning (ML) based automated fault detection and diagnostics (AFDD) algorithms for detecting refrigerant undercharge faults in residential heating, ventilation, and air conditioning (HVAC) systems, using actual building data and a minimal set of features. The ML-based algorithms included Decision Tree (DT) and K-Nearest Neighbors (KNN). Both the rule-based and ML-based algorithms demonstrated the capability to detect refrigerant undercharge faults of -30% or more. Both types of algorithms exhibited false alarms before the implementation of a false alarm mitigation algorithm, which motivated the development of such a mitigation strategy. After applying the mitigation, false alarms were substantially reduced, with the rule-based algorithm decreasing to 0.6% and the ML-based algorithms reaching 0%, while maintaining strong detection performance. Although the rule-based algorithm initially showed lower performance compared to the ML-based algorithms, its detection accuracy improved after mitigation to a level comparable to the ML-based algorithms. These results confirm that combining false alarm mitigation with both rule-based and ML-based AFDD algorithms significantly enhances practical reliability while preserving robust fault detection capabilities. Furthermore, the findings demonstrate the potential for field deployment of these algorithms in residential HVAC systems and highlight the importance of minimizing false alarms.

False Alarm↗

Evaluation of miniature single-wire sheathed thermocouples for turbine blade temperature measurement

Chromel Alumel thermocouples were used, with sheath diameters of 0.15 and 0.25 mm. Tests were conducted at temperatures ranging from 750 to 1250 K. Both steady state and thermal cycling tests were performed for times up to 200 hours. Initial testing was performed in a low velocity gas stream for long time periods using a Meker-type burner. Additional testing was done in a high velocity gas stream for short time periods using a hot gas tunnel and also in a J75 jet engine. A total of eleven 0.15 mm diameter thermocouples and six 0.25 mm diameter thermocouples were tested. Drift rates up to 2.5% in 10 hours were observed. Photomicrographs show that this design is near the limit of miniaturization based on present manufacturing capabilities. Results indicate that the effects of miniaturization on reliability and accuracy must be considered when choosing thermocouples for a particular application.

Hollanda, R.↗