Search NASA⌕ Search

SEARCH · Search NASA

Results for “Automated calibration”

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.

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

At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Pinatubo and Pre-Pinatubo Optical-Depth Spectra: Mauna Loa Measurements, Comparisons, Inferred Particle Size Distributions, Radiative Effects, and Relationship to Lidar Data

The Ames airborne tracking sunphotometer was operated at the National Oceanic and Atmospheric Administration (NOAA) Mauna Loa Observatory (MLO) in 1991 and 1992 along with the NOAA Climate Monitoring and Diagnostics Laboratory (CMDL) automated tracking sunphotometer and lidar. June 1991 measurements provided calibrations, optical-depth spectra, and intercomparisons under relatively clean conditions; later measurements provided spectra and comparisons for the Pinatubo cloud plus calibration checks. June 1991 results are similar to previous MLO springtime measurements, with midvisible particle optical depth tau(sub p)(lambda = 0.526 microns) at the near-background level of 0.012 +/- 0.006 and no significant wavelength dependence in the measured range (lambda = 0.38 to 1.06 microns). The arrival of the Pinatubo cloud in July 1991 increased midvisible particle optical depth by more than an order of magnitude and changed the spectral shape of tau(sub p)(lambda) to an approximate power law with an exponent of about -1.4. By early September 1991, the spectrum was broadly peaked near 0.5 microns, and by July 1992, it was peaked near 0.8 microns. Our optical-depth spectra include corrections for diffuse light which increase postvolcanic midvisible tau(sub p) values by 1 to 3% (i.e., 0.0015 to 0.0023). NOAA- and Ames Research Center (ARC)-measured spectra are in good agreement. Columnar size distributions inverted from the spectra show that the initial (July 1991) post-Pinatubo cloud was relatively rich in small particles (r less than 0.25 microns), which were progressively depleted in the August-September 1991 and July 1992 periods. Conversely, both of the later periods had more of the optically efficient medium-sized particles (0.25 less than r less than 1 micron) than did the fresh July 1991 cloud. These changes are consistent with particle growth by condensation and coagulation. The effective, or area-weighted, radius increased from 0.22 +/- 0.06 micron in July 1991 to 0.56 +/- 0.12 micron in August-September 1991 and to 0.86 +/- 0.29 micron in July 1992. Corresponding column mass values were 4.8 +/- 0.7, 9.1 +/- 2.7, and 5.5 +/- 2 micro g/sq cm, and corresponding column surface areas were 4.4 +/- 0.5, 2.9 +/- 0.2, and 1.1 +/- 0.1 sq micron/sq cm,. Photometer-inferred column backscatter values agree with those measured by the CMDL lidar on nearby nights. Combining lidar-measured backscatter profiles with photometer-derived backscatter-to-area ratios gives peak particle areas that could cause rapid heterogeneous loss of ozone, given sufficiently low particle acidity and suitable solar zenith angles (achieved at mid- to high latitudes). Top-of-troposphere radiative forcings for the September 1991 and July 1992 optical depths and size distributions over MLO are about -5 and -3 W 1/sq m, respectively (hence comparable in magnitude but opposite in sign to the radiative forcing caused by the increase in manmade greenhouse gases since the industrial revolution). Heating rates in Pinatubo layer over MLO are 0.55 +/- 0.13 and 0.41 +/- 0.14 K/d for September 1991 and July 1992, respectively.

Russell, P. B.↗
NASA NTRS2010

Recent Results on SNRs and PWNe from the Fermi Large Area Telescope

Topics include: Fermi LAT Collaboration groups; galactic results from LAT; a GeV, wide-field instrument; the 1FGL catalog, the Fermi LAT 1FGL source catalog, unidentified gamma-ray sources; variability in 1FGL sources; curvature in 1FGL sources; spectral-variability classification; pulsars and their wind nebulae; gamma-ray pulsars and MSPs; GeV PWN search; Crab pulsar and nebula; Vela X nebular of Vela pulsar; MSH 15-52; supernova remnants, resolved GeV sources, galactic transients, LAT unassociated transient detections; gamma rays from a nova; V407 Cyngi - a symbiotic nova; V407 Cygni: a variable star; and March 11 - a nova. Summary slides include pulsars everywhere, blazars, LAT as an electron detector, cosmic ray spectrum, the Large Area Telescope, the Fermi Observatory, LAT sensitivity with time, candidate gamma-ray events, on-orbit energy calibration and rate, a 1 year sky map, LAT automated science processing, reported GeV flares, early activity and spectacular flare, gamma-ray transients near the galactic plane , two early unassociated transients, counter part search - Fermi J0910-5404; counterpart search 3EG J0903-3531, and a new LAT transient - J1057-6027.

Hays, Elizabeth↗
NASA NTRS2021

Scheduling and Operations of the Orbiting Carbon Observatory-3 Mission

This paper describes the development and use of an automated scheduling system for the National Aeronautics and Space Administration’s (NASA) Orbiting Carbon Observatory-3 (OCO-3) Mission. OCO-3 measures atmospheric carbon dioxide from space. Made from the spare instrument built as a backup to the Orbiting Carbon Observatory-2 (OCO-2), OCO-3 extends the rich set of data collected by OCO-2. OCO-3 is outfitted with an agile Pointing Mirror Assembly (PMA) that allows for more detailed types of observations and rapid mode transitions. The mission uses an adaptation of the Compressed Large-scale Activity Scheduling and Planning (CLASP) system for scheduling nominal operations, as well as a separate automated scheduling system developed for scheduling observations for the calibration of the PMA. CLASP is used to schedule the four types of observational modes: Nadir, Glint, Target, and Snapshot Area Map. OCO-3 has a variety of complex mission-specific geometric constraints that were incorporated into CLASP to produce schedules that ensure instrument safety.

Moy, Alan↗
DOE OSTI2023

Beyond PID Controllers: PPO with Neuralized PID Policy for Proton Beam Intensity Control in Mu2e

We introduce a novel Proximal Policy Optimization (PPO) algorithm aimed at addressing the challenge of maintaining a uniform proton beam intensity delivery in the Muon to Electron Conversion Experiment (Mu2e) at Fermi National Accelerator Laboratory (Fermilab). Our primary objective is to regulate the spill process to ensure a consistent intensity profile, with the ultimate goal of creating an automated controller capable of providing real-time feedback and calibration of the Spill Regulation System (SRS) parameters on a millisecond timescale. We treat the Mu2e accelerator system as a Markov Decision Process suitable for Reinforcement Learning (RL), utilizing PPO to reduce bias and enhance training stability. A key innovation in our approach is the integration of a neuralized Proportional-Integral-Derivative (PID) controller into the policy function, resulting in a significant improvement in the Spill Duty Factor (SDF) by 13.6%, surpassing the performance of the current PID controller baseline by an additional 1.6%. This paper presents the preliminary offline results based on a differentiable simulator of the Mu2e accelerator. It paves the groundwork for real-time implementations and applications, representing a crucial step towards automated proton beam intensity control for the Mu2e experiment.

43 PARTICLE ACCELERATORS↗
NASA NTRS2009

Transmittance Measurement of a Heliostat Facility used in the Preflight Radiometric Calibration of Earth-Observing Sensors

Ball Aerospace and Technologies Corporation in Boulder, Colorado, has developed a heliostat facility that will be used to determine the preflight radiometric calibration of Earth-observing sensors that operate in the solar-reflective regime. While automatically tracking the Sun, the heliostat directs the solar beam inside a thermal vacuum chamber, where the sensor under test resides. The main advantage to using the Sun as the illumination source for preflight radiometric calibration is because it will also be the source of illumination when the sensor is in flight. This minimizes errors in the pre- and post-launch calibration due to spectral mismatches. It also allows the instrument under test to operate at irradiance values similar to those on orbit. The Remote Sensing Group at the University of Arizona measured the transmittance of the heliostat facility using three methods, the first of which is a relative measurement made using a hyperspectral portable spectroradiometer and well-calibrated reference panel. The second method is also a relative measurement, and uses a 12-channel automated solar radiometer. The final method is an absolute measurement using a hyperspectral spectroradiometer and reference panel combination, where the spectroradiometer is calibrated on site using a solar-radiation-based calibration.

Czapla-Myers, J.↗
NASA NTRS2008

In-Flight Validation of Mid and Thermal Infrared Remotely Sensed Data Using the Lake Tahoe and Salton Sea Automated Validation Sites

The presentation includes an introduction, Lake Tahoe site layout and measurements, Salton Sea site layout and measurements, field instrument calibration and cross-calculations, data reduction methodology and error budgets, and example results for MODIS. Summary and conclusions are: 1) Lake Tahoe CA/NV automated validation site was established in 1999 to assess radiometric accuracy of satellite and airborne mid and thermal infrared data and products. Water surface temperatures range from 4-25C.2) Salton Sea CA automated validation site was established in 2008 to broaden range of available water surface temperatures and atmospheric water vapor test cases. Water surface temperatures range from 15-35C. 3) Sites provide all information necessary for validation every 2 mins (bulk temperature, skin temperature, air temperature, wind speed, wind direction, net radiation, relative humidity). 4) Sites have been used to validate mid and thermal infrared data and products from: ASTER, AATSR, ATSR2, MODIS-Terra, MODIS-Aqua, Landsat 5, Landsat 7, MTI, TES, MASTER, MAS. 5) Approximately 10 years of data available to help validate AVHRR.

Lake Tahoe↗
DOE OSTI2020

Evaluating Energy Efficiency Opportunities from Connected and Automated Vehicle Deployments Coupled with Shared Mobility in California

Connected and Automated Vehicles (CAVs) can be considered to be a disruptive transportation technology, with the potential to significantly improve overall transportation system efficiency; however, CAVs may increase induce vehicle miles traveled (VMT) and bring on greater energy consumption. Further, shared mobility is another disruptive transportation event that is reshaping our travel patterns. The primary goal of this project was to extensively collect data from vehicles and associated infrastructure equipped with CAV technologies from both real-world experiments and simulation studies mainly deployed in California, and develop a comprehensive framework for evaluating energy efficiency opportunities from large-scale (e.g., statewide) introduction of CAVs and a wide deployment of shared mobility systems in a variety of scenarios. To quantify the combined impact of CAV and shared mobility on travel behavior, traffic performance, and energy efficiency, a unique mesoscopic simulation-based model was developed for mobility and energy efficiency evaluation considering these disruptive transportation technologies. As a complement to existing studies on nationwide evaluation of CAVs’ energy impacts, this project was focused on data collection efforts and CAV applications under congested traffic environments that are frequently experienced on a massive scale across the major metropolitan areas in California. Extensive real-world data collection supplemented with simulation studies were conducted to cover a variety of CAV and shared mobility scenarios, particularly on scenarios less-explored in the existing research. Another key component of this project was to consider the interaction between different CAV technologies and shared mobility models, and the compound effect on energy efficiency. A comprehensive modeling suite was developed to quantify the impact of new mobility technologies on travel behavior and traffic performance. The developed modeling framework includes an energy intensity module, mode choice module and activity generation module that are integrated into an agent-based BEAM simulation platform to perform impact analysis based on a variety of scenarios. In addition, the RouteE model has been upgraded to incorporate the impact of CAVs on traffic flow, VMT and energy intensity, using micro-simulation data collected from both freeways and urban arterials. A novel fundamental influencing factor (FIF) mode choice model was developed to link CAV and shared mobility components with travel behaviors, and adapted into the BEAM-centered model framework. A statewide energy inventory was constructed under various CAV technology deployment scenarios by incorporating datasets and models for predicting vehicle market share and vehicle usage, which are tightly associated with the penetration of shared mobility systems. Based applying this modeling suite to a calibrated network in Riverside California, it was found that cooperative automated driving in general will improve mobility, but automated vehicles, even when deployed in a shared autonomous fleet, will likely bring an increase of VMT (up to 36%) due to mode shifts and deadheading. Ride-hailing vehicles typically have better energy efficiency and a higher share of electric vehicles, which helps offset the negative impact from VMT increases when estimating the system-level energy consumption. In general, simulation results show a 6% increase in energy consumption for the scenarios with an increasing shift to ride-hailing modes. The statewide analysis based on the National Household Travel Survey (NHTS) sample data is consistent with the findings from the Riverside network and validate the developed clustering-prediction modeling methodology. The outcomes from this project will help close the knowledge gap on recognizing the potential performance and energy impacts of a broad deployment of CAV and shared mobility technologies across a wide range of roadway infrastructure with varying levels of congestion. Results from this project: 1) will support policymakers in steering CAV development and deployment towards an energy favorable direction; 2) reduce uncertainties in estimating energy saving opportunities from new mobility technologies and services; 3) increase the confidence of CAV technology investors both on the infrastructure side (i.e., transportation agencies) and on the vehicle side (i.e., OEMs); and 4) expedite the deployment of energy-efficient CAV and shared mobility applications.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1993

Icing research tunnel rotating bar calibration measurement system

In order to measure icing patterns across a test section of the Icing Research Tunnel, an automated rotating bar measurement system was developed at the NASA Lewis Research Center. In comparison with the previously used manual measurement system, this system provides a number of improvements: increased accuracy and repeatability, increased number of data points, reduced tunnel operating time, and improved documentation. The automated system uses a linear variable differential transformer (LVDT) to measure ice accretion. This instrument is driven along the bar by means of an intelligent stepper motor which also controls data recording. This paper describes the rotating bar calibration measurement system.

Gibson, Theresa L.↗
NASA NTRS1993

Icing Research Tunnel rotating bar calibration measurement system

In order to measure icing patterns across a test section of the Icing Research Tunnel, an automated rotating bar measurement system was developed at the NASA Lewis Research Center. In comparison with the previously used manual measurement system, this system provides a number of improvements: increased accuracy and repeatability, increased number of data points, reduced tunnel operating time, and improved documentation. The automated system uses a linear variable differential transformer (LVDT) to measure ice accretion. This instrument is driven along the bar by means of an intelligent stepper motor which also controls data recording. This paper describes the rotating bar calibration measurement system.

Gibson, Theresa L.↗
NASA NTRS1993

The Hubble Space Telescope quasar absorption line key project. II - Data calibration and absorption-line selection

We present the observational and data processing aspects of the Hubble Space Telescope Quasar Absorption Line Key Project. Topics discussed include the observational technique, calibration of the data, software that simulates the data, the automated procedure used to identify and characterize the absorption features, and the determination of the sensitivity limits of the survey.

Schneider, Donald P.↗
NASA NTRS2005

Satellite Calibration With LED Detectors at Mud Lake

Earth-monitoring instruments in orbit must be routinely calibrated in order to accurately analyze the data obtained. By comparing radiometric measurements taken on the ground in conjunction with a satellite overpass, calibration curves are derived for an orbiting instrument. A permanent, automated facility is planned for Mud Lake, Nevada (a large, homogeneous, dry lakebed) for this purpose. Because some orbiting instruments have low resolution (250 meters per pixel), inexpensive radiometers using LEDs as sensors are being developed to array widely over the lakebed. LEDs are ideal because they are inexpensive, reliable, and sense over a narrow bandwidth. By obtaining and averaging widespread data, errors are reduced and long-term surface changes can be more accurately observed.

Hiller, Jonathan D.↗
NASA NTRSDate not supplied

Spectral characterization of the Roman Space Telescope Grism and Prism assemblies

The Roman Space Telescope (RST) Wide Field Instrument (WFI) recently completed its thermal vacuum (TVAC) campaign in Boulder, CO. This campaign, which concludes multiple years of preparation, represented the last opportunity for characterization and verification of the Grism and Prism spectral properties before launch; currently scheduled for late-2026. To this end, a highly-automated series of measurements were performed to acquire images of calibration spectra at many field points. Features that were measured during these efforts include dispersion scale, blue/red bandpass edges, diffraction order radiometry, and ghost images. A summary of the techniques and results for several of these efforts is provided here.

Astronomy↗
NASA NTRS1975

Interim Report of the Astronomy Spacelab Payloads Study: Ultraviolet and Optical Astronomy - Volume 2

The Space Shuttle will comprise NASA's primary transportation system into near-earth orbit during the 1980s. The Shuttle will provide the astronomical community with a major new capability to send a wide variety of instrumentation into orbit, to utilize it there under manned or automatic control for periods from seven to thirty days, and to return it to the ground. To this end the European Space Research Organization (ESRO) is developing Spacelab, an array of interchangeable components -pressurized manned modules, unpressurized pallets and related support systems - to be mounted in the Shuttle payload bay. Spacelab will offer important opportunities to carry out astronomical research with instruments optimized for specific objectives. With a high flight frequency and with the ability to modify or interchange telescopes and instruments between flights, one will not need to make rigid long-term commitments to specific and compromised telescope/instrument/ detector combinations as is the case for automated satellites. Observational techniques demanding the physical return of data and equipment - in particular the use of photographic film, instruments requiring tight calibration controls, cryogens, high-risk detectors and degradeable optical coatings -will open research areas not readily addressed by automated satellites. Although Shuttle flight duration will be limited to periods from seven to thirty days, substantial data can be obtained with a single instrument on short missions, if targets are carefully selected and prioritized, and a large number of instruments can be accommodated on a single flight. Important astronomical data are regularly obtained on sounding rocket flights of five minutes duration. Spacelab will provide far longer observing periods for large and small telescopes, with resources greatly exceeding those of sounding rockets, while retaining much of the sounding rocket philosophy in terms of instrument flexibility, simplicity, reliability assurance and development costs. The Ultraviolet and Optical Astronomy Program on Spacelab is being planned to provide optical astronomers with relatively simple and regular access to the extended wavelength coverage, the superior image quality and the darkness of the night sky available above the earth's atmosphere. In a rapidly evolving science one cannot predict what problems will be timely in the 1980s. Extrapolating from the current epoch, however, one can envision a continuing interest in such areas as the structure, composition and phenomenology of planetary surfaces and atmospheres; the composition and physical nature of the interstellar medium; the composition, structure and life history of stars, especially those in advanced stages of evolution; the stellar population of other galaxies; such enigmatic phenomena as X-ray binary black holes, pulsars, active galactic nuclei and quasars; large scale interactions between galaxies and the nature of the intergalactic medium; precise calibration of the Hubble law for the expansion of the universe; the average density of the universe; and the existence of extraterrestrial life.

Source record↗
DOE OSTI2023

Exploring the working range of automated standard dilution analysis of nutrient elements in foods by inductively coupled plasma optical emission spectrometry

Inductively coupled plasma optical emission spectrometry (ICP-OES) is an important tool for measuring nutrient elements in food. ICP-OES methods typically determine analytical concentrations using external standard calibration but can be susceptible to matrix effects. The method of standard additions does not suffer from matrix effects but is time consuming and labor intensive. Automated standard dilution analysis (SDA) allows for online matrix matched calibration without preparing individual standard additions for each sample matrix. This approach may solve both time and matrix issues and has been described in the literature as an attractive alternative to standard additions. The working range of the method for nutrient elements, however, is an understudied feature of SDA that may be a potential drawback to routine analysis of foods. We evaluated automated SDA performance through the analysis of 10 reference materials and four fortified (i.e., spiked) foods spanning the AOAC food triangle. We evaluated the working range, accuracy, and precision for analyses of nutrient elements in foods. Accepted accuracy (80–120% recovery) was achieved for 10 nutrient elements, Ca, Cu, Fe, K, Mg, Mn, Na, P, S, and Zn, when the analytical solution concentration to standard concentration ratio was less than 10. This equates to a working range for each element spanning at least two orders of magnitude. Removing outliers, Z scores (n = 95) ranged from –1.8 to 0.88, and the average recovery (n = 85) from fortification experiments was 97 ± 12% (2σ). Therefore, automated SDA applied to ICP-OES may be used for nutrient elemental analyses in samples with difficult matrices such as foods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

The value of human data annotation for machine learning based anomaly detection in environmental systems

Anomaly detection is the process of identifying unexpected data samples in datasets. Automated anomaly detection is either performed using supervised machine learning models, which require a labelled dataset for their calibration, or unsupervised models, which do not require labels. While academic research has produced a vast array of tools and machine learning models for automated anomaly detection, the research community focused on environmental systems still lacks a comparative analysis that is simultaneously comprehensive, objective, and systematic. This knowledge gap is addressed for the first time in this study, where 15 different supervised and unsupervised anomaly detection models are evaluated on 5 different environmental datasets from engineered and natural aquatic systems. To this end, anomaly detection performance, labelling efforts, as well as the impact of model and algorithm tuning are taken into account. As a result, our analysis reveals the relative strengths and weaknesses of the different approaches in an objective manner without bias for any particular paradigm in machine learning. Most importantly, our results show that expert-based data annotation is extremely valuable for anomaly detection based on machine learning.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Unifying simulation and inference with normalizing flows

There have been many applications of deep neural networks to detector calibrations and a growing number of studies that propose deep generative models as automated fast detector simulators. We show that these two tasks can be unified by using maximum likelihood estimation (MLE) from conditional generative models for energy regression. Unlike direct regression techniques, the MLE approach is prior independent and non-Gaussian resolutions can be determined from the shape of the likelihood near the maximum. Using an ATLAS-like calorimeter simulation, we demonstrate this concept in the context of calorimeter energy calibration. Published by the American Physical Society 2025

Hadronic calorimiters↗
DOE OSTI2022

Dynamic calibration of differential equations using machine learning, with application to turbulence models

We present a methodology for calibration of parametric ordinary and partial differential equation models, using off-the-shelf software for back-propagation in Neural Networks (NN). As a prototypical example, we consider calibration of a Reynolds-averaged Navier-Stokes (RANS) turbulence closure model, against ground truth data from direct numerical simulations (DNS) of two different turbulent flows. Numerical time integration is represented as a custom NN, where only the RANS model parameters are trainable. A loss function is defined to quantify the mismatch between the NN prediction and the ground truth over a predefined, finite time integration window. This loss function is then minimized using a gradient descent method utilizing the back-propagation algorithm. Furthermore, this dynamic approach to training is to be contrasted with a static approach, wherein a least square regression estimate for parameters is obtained in the limit of an infinitesimal time integration window. In a first test of static and dynamic approaches against ground truth data generated by the model, the former proves to be significantly faster and more accurate than the latter at recovering the parameters. When both calibration approaches are tested against DNS data, for which it is known that the model cannot achieve a perfect fit, the static approach yields a good prediction only for short times, while the dynamic approach results in physical and stable predictions over the entire integration window. After optimization of the dynamic approach for time step, spatial resolution, stability, and physics-based constraints, we obtain a 50% improvement of outcomes over those obtained from the existing, manually calibrated set of parameters, demonstrating the merits of this systematic and automated procedure.

97 MATHEMATICS AND COMPUTING↗