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At least 847 records · Page 47

Fire Detection Organizing Questions

Verified models of fire precursor transport in low and partial gravity: a. Development of models for large-scale transport in reduced gravity. b. Validated CFD simulations of transport of fire precursors. c. Evaluation of the effect of scale on transport and reduced gravity fires. Advanced fire detection system for gaseous and particulate pre-fire and fire signaturesa: a. Quantification of pre-fire pyrolysis products in microgravity. b. Suite of gas and particulate sensors. c. Reduced gravity evaluation of candidate detector technologies. d. Reduced gravity verification of advanced fire detection system. e. Validated database of fire and pre-fire signatures in low and partial gravity.

Source record↗

Boundary Layer Controls on the Shallow-to-Deep Cumulus Transition (Final Technical Report)

This project advanced our understanding of the processes governing cumulus cloud formation and provides an improved observational basis for validating earth system models. To be specific, the project used laser- and radar-remote sensors to examine the physical properties of updrafts that rise from earth’s surface and initiate clouds deeper in the atmosphere. These updrafts comprise “thermals” and “plumes” and occur at small spatial and temporal scales (e.g., 10s of minutes, 100s of meters). These small scales preclude explicit representation in most earth system and climate models, and thus necessitate “sub-grid-scale” parameterization of updraft processes. The innovation of this project was to directly measure the size, shape, strength and water vapor content of these updrafts with Doppler and Raman lidars, respectively, and to link these updraft properties to cloud processes using vertically pointed weather radars. The resulting data sets comprise 100s of thousands of updrafts and thousands of clouds, which far exceeds previous efforts, and thereby provides a robust statistical and physical representation of these processes. From these large datasets the project produced a sequence of scientific analyses that: (1) Elucidate how variations in the turbulent structure of the convective boundary layer control shallow cumulus convection, (2) Quantify the upward transport of water vapor to cloud base via thermals and plumes, (3) Validate large-eddy simulations of updrafts and shallow convective clouds, (4) Demonstrate a size-to-strength relationship between updraft width and updraft speed, and (5) Demonstrate how updrafts interact with the stability at the top of the convective boundary layer to modulate the depth and vigor of convective clouds. These results have been disseminated via several published journal articles, academic theses, and conference presentations. Collectively these results contribute to the Atmospheric System Research (ASR) program’s goal to “improve understanding of the key cloud, aerosol, precipitation, and radiation processes that affect the Earth’s radiative balance and hydrological cycle, particularly processes that limit the predictive ability of regional and global earth system models”.

54 ENVIRONMENTAL SCIENCES↗

IPC-Fusion (Infrastructure Perception and Control (IPC): Multisensor Data Fusion Software) [SWR-25-153]

As part of the National Laboratory of the Rockies' (NLR’s) Infrastructure Perception and Control Laboratory, the IPC-Fusion toolkit provides a probabilistic, scalable, multi-sensor fusion framework that integrates (late-stage fusion) heterogeneous object detection data from traffic sensors to enable robust, real-time tracking of roadway occupants. The algorithmic design of the toolkit is motivated by the need for creating a digital twin of traffic at the edge in a scalable and affordable manner. The software operates by combining object-level measurements (such as position and velocity) from a suite of sensors (such as radar, lidar, camera) using Kalman filtering and probabilistic data association techniques to overcome individual sensor limitations and achieve superior tracking performance in complex traffic zones. The framework addresses key challenges including heterogeneous measurement uncertainties, asynchronous data streams, varying spatiotemporal data resolutions, robust data association, and adaptive object lifecycle management. Validated on real-world traffic intersection data including vehicles and pedestrians, IPC-Fusion demonstrates enhanced tracking reliability across scenarios involving occlusions, sensor failures, and varying traffic densities, supporting the broader IPC initiative's goal of transforming transportation infrastructure through advanced perception capabilities for intelligent transportation systems, traffic safety applications, and autonomous vehicle support.

Sandhu, Rimple [National Laboratory of the Rockies↗

Probing Dark Current Random Telegraph Signal in a Small Pitch Vertically Pinned Photodiode CMOS Image Sensor after Proton Irradiation

Dark Current degradation and Dark Current Ran- dom Telegraph Signal after proton irradiation are studied in new scale silicon microvolumes by using a commercial CMOS Image Sensor. Results show that previously reported empirical models describing the Displacement Damage induced degradations are still valid despite the 10 to 100 times smaller depletion volume used. In addition, no evidence of significant Total Ionizing Dose effects is observed. Finally the reduction of the fraction of Random Telegraph Signal (RTS) pixels detected and of the fraction of multi-level RTS pixels is directly linked to the reduction in pixel volume.

CMOS Image Sensor (CIS)↗

A light-emitting diode- (LED-) based absorption sensor for simultaneous detection of carbon monoxide and carbon dioxide

Here, a sensor was developed for simultaneous measurements of carbon monoxide (CO) and carbon dioxide (CO 2 ) fluctuations in internal combustion engine exhaust gases. This sensor utilizes low-cost and compact light-emitting diodes (LEDs) that emit in the 3–5 µm wavelength range. An affordable, fast response sensor that can measure these gases has a broad application that can lead to more efficient, fuel-flexible engines and regulation of harmful emissions. Light emission from LEDs is spectrally broader and more spatially divergent when compared to that of lasers, which presented many design challenges. Optical design studies addressed some of the non-ideal characteristics of the LED emissions. Measurements of CO and CO 2 were conducted using their fundamental absorption bands centered at 4.7 µm and 4.3 µm, respectively, while a 3.6 µm reference LED was used to account for scattering losses (due to soot, window deposits, etc.) common to the three measurement LEDs. Instrument validation and calibration was performed using a laboratory flow cell and bottled-gas mixtures. The sensor was able to detect CO 2 and CO concentration changes as small as 30 ppm and 400 ppm, respectively. Because of the many control and monitor species with infra-red absorption features, which can be measured using the strategy described, this work demonstrates proof of concept for a wider range of fast (250 Hz) and low-cost sensors for gas measurement and process monitoring.

47 OTHER INSTRUMENTATION↗

Enzymatic Laser-Induced Graphene Biosensor for Electrochemical Sensing of the Herbicide Glyphosate

Glyphosate is a globally applied herbicide yet it has been relatively undetectable in-field samples outside of gold-standard techniques. Its presumed nontoxicity toward humans has been contested by the International Agency for Research on Cancer, while it has been detected in farmers’ urine, surface waters and crop residues. Rapid, on-site detection of glyphosate is hindered by lack of field-deployable and easy-to-use sensors that circumvent sample transportation to limited laboratories that possess the equipment needed for detection. Herein, the flavoenzyme, glycine oxidase, immobilized on platinum-decorated laser-induced graphene (LIG) is used for selective detection of glyphosate as it is a substrate for GlyOx. The LIG platform provides a scaffold for enzyme attachment while maintaining the electronic and surface properties of graphene. The sensor exhibits a linear range of 10–260 µm, detection limit of 3.03 µm, and sensitivity of 0.991 nA µm -1 . The sensor shows minimal interference from the commonly used herbicides and insecticides: atrazine, 2,4-dichlorophenoxyacetic acid, dicamba, parathion-methyl, paraoxon-methyl, malathion, chlorpyrifos, thiamethoxam, clothianidin, and imidacloprid. Sensor function is further tested in complex river water and crop residue fluids, which validate this platform as a scalable, direct-write, and selective method of glyphosate detection for herbicide mapping and food analysis.

47 OTHER INSTRUMENTATION↗

Non-inductive vertical position measurements by Faraday-effect polarimetry on EAST tokamak

Vertical instability control in an elongated plasma is highly desirable for a tokamak reactor. A multi-channel 694 GHz far-infrared laser-based polarimeter-interferometer system has been used to provide a non-inductive vertical position measurement in the long-pulse EAST tokamak. A detailed comparison of vertical position measurements by polarimetry and external inductive flux loops has been used to validate Faraday-effect polarimetry as an accurate high-time response vertical position sensor.

47 OTHER INSTRUMENTATION↗

Development of Monitoring Techniques for Binderjet Additive Manufacturing of Silicon Carbide Structures

The Transformational Challenge Reactor (TCR) program is leveraging additive manufacturing (AM) technologies to fabricate nuclear components to be assembled into a fully functional microreactor core. Compared with traditional manufacturing technologies, AM technologies allow (1) observation of the manufacturing process at a much higher resolution in real-time using in situ monitoring technologies to capture the sensor signature that scientifically describes each event occurring over time and space and (2) validation of the manufacturing process quality using domain-informed data analytics techniques as a potential qualification and certification methodology for the final component. This report provides an update on the program work on binder jetting in situ process monitoring and associated data analytics results, as well as sample placement and tracking for the subsequent chemical vapor infiltration (CVI) process. Examples are provided to illustrate the progress. Elements of the Digital Thread and data management are discussed in the main document, and an extensive supplemental material section is provided detailing the Digital Platform, as well as its implementation and components. In conclusion the path forward for the next fiscal year is discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Development of Monitoring Techniques for Laser Powder Bed Additive Manufacturing of Metal Structures (Progress Report)

The Transformational Challenge Reactor (TCR) program is leveraging additive manufacturing (AM) technologies to fabricate nuclear grade components to be assembled into a fully functional microreactor core. Compared to traditional manufacturing technologies, additive manufacturing technologies allow (1) observation of the manufacturing process at a much higher resolution in real time using in situ monitoring technologies to capture the sensor signature that scientifically describes each event occurring over time and space, and (2) validation of the manufacturing process quality using domain-informed data analytics techniques as a potential qualification and certification methodology for the final component. This report provides an update on the program work on laser powder bed fusion in-situ process monitoring and associated data analytics results. Examples are provided to illustrate the progress. Elements of the Digital Thread and data management are discussed in the main document, and an extensive supplemental material section is provided detailing the Digital Platform, as well as its implementation and components. In conclusion the path forward for the next fiscal year is discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Report on Progress of correlation of in-situ and ex-situ data and the use of artificial intelligence to predict defects

The Transformational Challenge Reactor (TCR) program is leveraging additive manufacturing (AM) technologies to fabricate nuclear components which will be assembled into a fully functional microreactor core. Compared with traditional manufacturing technologies, AM technologies allow (1) real-time observation of the manufacturing process at a much higher resolution using in-situ monitoring technologies to capture the sensor signatures that scientifically describe each event occurring over time and space and (2) validation of the manufacturing process quality using domain-informed data analytics techniques as a potential qualification and certification methodology for the final component. This report provides an update on the program work on in-situ and ex-situ data correlation and associated data analytics results. Examples are provided to illustrate progress with respect to laser powder bed fusion (L-PBF), binder jetting, computed tomography (CT) reconstruction, and mechanical testing. Elements of the Digital Thread and data management infrastructure are discussed in the main document, and an extensive supplemental appendix is provided detailing the Digital Platform, as well as its implementation and subcomponents. In conclusion, the path forward for the next fiscal year is also discussed.

42 ENGINEERING↗

Integrated System for Methane Emissions Monitoring, Mapping, and Quantification

This report presents the work completed under the DOE iM4 project for the development of a methane emission monitoring system for detection, location, and quantification of methane in oil and gas industries. The task was divided into four main areas including: 1) Sensors and Input, 2) Centralized Cloud Information Center, 3) Algorithms, and 4) Testing and Validation. Task 1 focused on researching and developing an understanding of the current, or soon to be, available methane sensing technologies. Task 2 consisted of developing the architecture, selecting hardware, software and elements for the methane monitoring system. Task 3 focused on the algorithms used for the complex inverse model of going from measured methane signatures to the detection, localization, and quantification of sources that are desired. Finally, Task 4 focused on the methods of testing and validating the operation of the system. Attention was also given to the development method and cost breakdown of the system.

03 NATURAL GAS↗

Summary of Michigan multispectral investigations program

The development of techniques to extend spectral signatures in space and time is reported. Signatures that were valid for 30 miles have been extended for 129 miles using transformation and sun sensor data so that a complicated multispectral recognition problem that required 219 learning sets can now be done with 13 learning sets.

Legault, R. R.↗

Preliminary Assessment of Suomi-NPP VIIRS On-orbit Radiometric Performance

The Visible-Infrared Imaging Radiometer Suite (VIIRS) is a key instrument on-board the Suomi National Polar-orbiting Partnership (NPP) spacecraft that was launched on October 28th 2011. VIIRS was designed to provide moderate and imaging resolution of most of the globe twice daily. It is a wide-swath (3,040 km) cross-track scanning radiometer with spatial resolutions of 370.and 740 m at nadir for imaging and moderate bands, respectively. It has 22 spectral bands covering the spectrum between 0.412 11m and 12.01 11m, including 14 reflective solar bands (RSB), 7 thermal emissive bands (TEB), and 1 day-night band (ON B). VIIRS observations are used to generate 22 environmental data products (EORs). This paper will briefly describe NPP VIIRS calibration strategies performed by the independent government team, for the initial on-orbit Intensive Calibration and Validation (ICV) activities. In addition, this paper will provide an early assessment of the sensor on-orbit radiometric performance, such as the sensor signal to noise ratios (SNRs), dual gain transition verification, dynamic range and linearity, reflective bands calibration based on the solar diffuser (SO) and solar diffuser stability monitor (SOSM), and emissive bands calibration based on the on-board blackbody calibration (OBC). A comprehensive set of performance metrics generated during the pre-launch testing program will be compared to VIIRS on-orbit early performance, and a plan for future cal/val activities and performance enhancements will be presented.

Oudrari, Hassan↗

Powered Descent Guidance with General Thrust-Pointing Constraints

The Powered Descent Guidance (PDG) algorithm and software for generating Mars pinpoint or precision landing guidance profiles has been enhanced to incorporate thrust-pointing constraints. Pointing constraints would typically be needed for onboard sensor and navigation systems that have specific field-of-view requirements to generate valid ground proximity and terrain-relative state measurements. The original PDG algorithm was designed to enforce both control and state constraints, including maximum and minimum thrust bounds, avoidance of the ground or descent within a glide slope cone, and maximum speed limits. The thrust-bound and thrust-pointing constraints within PDG are non-convex, which in general requires nonlinear optimization methods to generate solutions. The short duration of Mars powered descent requires guaranteed PDG convergence to a solution within a finite time; however, nonlinear optimization methods have no guarantees of convergence to the global optimal or convergence within finite computation time. A lossless convexification developed for the original PDG algorithm relaxed the non-convex thrust bound constraints. This relaxation was theoretically proven to provide valid and optimal solutions for the original, non-convex problem within a convex framework. As with the thrust bound constraint, a relaxation of the thrust-pointing constraint also provides a lossless convexification that ensures the enhanced relaxed PDG algorithm remains convex and retains validity for the original nonconvex problem. The enhanced PDG algorithm provides guidance profiles for pinpoint and precision landing that minimize fuel usage, minimize landing error to the target, and ensure satisfaction of all position and control constraints, including thrust bounds and now thrust-pointing constraints.

Carson, John M., III↗

Use of 2d-video Disdrometer to Derive Mean Density-size and Ze-SR Relations: Four Snow Cases from the Light Precipitation Validation Experiment

The application of the 2D-video disdrometer to measure fall speed and snow size distribution and to derive liquid equivalent snow rate, mean density-size and reflectivity-snow rate power law is described. Inversion of the methodology proposed by Böhm provides the pathway to use measured fall speed, area ratio and '3D' size measurement to estimate the mass of each particle. Four snow cases from the Light Precipitation Validation Experiment are analyzed with supporting data from other instruments such as Precipitation Occurrence Sensor System (POSS), Snow Video Imager (SVI), a network of seven snow gauges and three scanning C9 band radars. The radar-based snow accumulations using the 2DVD-derived Ze-SR relation are in good agreement with a network of seven snow gauges and outperform the accumulations derived from a climatological Ze-SR relation used by the Finnish Meteorological Institute (FMI). The normalized bias between radar-derived and gauge accumulation is reduced from 96% when using the fixed FMI relation to 28% when using the Ze-SR relations based on 2DVD data. The normalized standard error is also reduced significantly from 66% to 31%. For two of the days with widely different coefficients of the Ze-SR power law, the reflectivity structure showed significant differences in spatial variability. Liquid water path estimates from radiometric data also showed significant differences between the two cases. Examination of SVI particle images at the measurement site corroborated these differences in terms of unrimed versus rimed snow particles. The findings reported herein support the application of Böhm's methodology for deriving the mean density-size and Ze-SR power laws using data from 2D-video disdrometer.

radar↗

Artemis I Flight Instrumentation Data Quality Assessment and Processing

This paper is in support of the SciTech 2024 Space Launch System Aerosciences Special Sessions being organized by Brent Pomeroy and Jeremy Pinier. On November 16th, 2022, NASA launched the inaugural test flight of the Space Launch System (SLS) carrying the Orion capsule into a high orbit far beyond the Moon. The launch vehicle was instrumented with over three thousand flight instrumentation sensors, which monitored aerodynamic, acoustic, structural, and thermal environments. These data are intended to validate experimental and numerical tools used to predict the design environments which the vehicle experiences during launch and ascent. Prior to launch, tests were performed at the SLS Systems Integration Laboratory (SIL) using flight-like avionics and on the integrated flight hardware of Artemis I at the Vehicle Assembly Building (VAB). The purpose of these tests was to characterize the data acquisition units (DAUs) used to record and telemeter flight data to ground stations in order to assure that flight test objectives can be achieved and to quantify the expected quality of the flight data. In addition, pre-flight assessment and development of tools and methods used to process and disseminate flight data at the Huntsville Operations Support Center (HOSC) were conducted and adjustments made with respect to DAU time-synchronization prior to and after the flight. This paper summarizes these tests and some aspects of the post processing of data are discussed.

Developmental Flight Instrumentation↗

Artemis I Flight Instrumentation Data Quality Assessment and Processing

This paper is in support of the SciTech 2024 Space Launch System Aerosciences Special Sessions being organized by Brent Pomeroy and Jeremy Pinier. On November 16th, 2022, NASA launched an inaugural test flight of the Space Launch System (SLS) carrying the Orion capsule around the moon. The vehicle was instrumented with thousands of Developmental Flight Instrumentation (DFI) sensors, which monitored aerodynamic, acoustic, structural, and thermal environments. These data are used to validate experimental and numerical tools used to predict conditions the vehicle experiences during ascent. Prior to launch, a set of tests were performed to quantify the expected quality of the DFI flight data. These included testing of individual components, such as data acquisition units, at the Systems Integration Laboratory (SIL) and testing of integrated vehicle components at the Vehicle Assembly Building (VAB). This paper summarizes these tests. Some aspects of post processing of data are also discussed.

Developmental Flight Instrumentation↗