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DOE OSTI2017

On-line monitoring of I and C transmitters and sensors for calibration verification and response time testing was successfully implemented at ATR - 326

The Advanced Test Reactor (ATR) has always had a comprehensive procedure to verify the performance of its critical transmitters and sensors, including RTDs, and pressure, level, and flow transmitters. These transmitters and sensors have been periodically tested for response time and calibration verification to ensure accuracy. With implementation of on-line monitoring techniques at ATR, the calibration verification and response time testing of these transmitters and sensors are verified remotely, automatically, hands off, include more portions of the system, and can be performed at almost any time during process operations. The work was done under a DOE funded SBIR project carried out by AMS. As a result, ATR is now able to save the manpower that has been spent over the years on manual calibration verification and response time testing of its temperature and pressure sensors and refocus those resources towards more equipment reliability needs. More importantly, implementation of OLM will help enhance the overall availability, safety, and efficiency. Together with equipment reliability programs of ATR, the integration of OLM will also help with I and C aging management goals of the Department of Energy and long-time operation of ATR. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS1994

Fixture For Calibrating Pressure Probe

Fixture in form of specially designed clamshell housing enables in situ calibration of pressure transducer mounted in body of pressure probe in wind tunnel. Includes two metal half shells machined with necks and matching cavities, when put together, define larger neck and cavity accommodating probe. Probe secured to bottom half shell by use of clamp before installing top half shell: necessary to follow sequence to protect probe during assembly. Clamshell calibration fixture attached to pressure probe in few minutes, making it possible to calibrate pressure transducer at convenient times. Calibrations performed before and after wind-tunnel runs each day, between runs in event of delays or suspected malfunctions, and essentially any other time, without having to remove probe from wind tunnel.

Ashby, George C., Jr.↗

NASA NTRS1994

Remote clocks linked by a fully calibrated two-way timing link

Fully calibrated two-way time transfers between the U.S. Naval Observatory (USNO) and the U.S. Naval Observatory Time Service Substation (NOTSS) have become operational. The calibration method employed was the co-located Earth station method. Results concerning timing, stability, comparison of two-way and Global Positioning System (GPS) timing links, and remote clock contribution to local time scale computation will be presented.

Deyoung, James A.↗

NASA NTRS1993

Streak camera based SLR receiver for two color atmospheric measurements

To realize accurate two-color differential measurements, an image digitizing system with variable spatial resolution was designed, built, and integrated to a photon-counting picosecond streak camera, yielding a temporal scan resolution better than 300 femtosecond/pixel. The streak camera is configured to operate with 3 spatial channels; two of these support green (532 nm) and uv (355 nm) while the third accommodates reference pulses (764 nm) for real-time calibration. Critical parameters affecting differential timing accuracy such as pulse width and shape, number of received photons, streak camera/imaging system nonlinearities, dynamic range, and noise characteristics were investigated to optimize the system for accurate differential delay measurements. The streak camera output image consists of three image fields, each field is 1024 pixels along the time axis and 16 pixels across the spatial axis. Each of the image fields may be independently positioned across the spatial axis. Two of the image fields are used for the two wavelengths used in the experiment; the third window measures the temporal separation of a pair of diode laser pulses which verify the streak camera sweep speed for each data frame. The sum of the 16 pixel intensities across each of the 1024 temporal positions for the three data windows is used to extract the three waveforms. The waveform data is processed using an iterative three-point running average filter (10 to 30 iterations are used) to remove high-frequency structure. The pulse pair separations are determined using the half-max and centroid type analysis. Rigorous experimental verification has demonstrated that this simplified process provides the best measurement accuracy. To calibrate the receiver system sweep, two laser pulses with precisely known temporal separation are scanned along the full length of the sweep axis. The experimental measurements are then modeled using polynomial regression to obtain a best fit to the data. Data aggregation using normal point approach has provided accurate data fitting techniques and is found to be much more convenient than using the full rate single shot data. The systematic errors from this model have been found to be less than 3 ps for normal points.

Varghese, Thomas K.↗

NASA NTRS1990

A Solar-luminosity Model and Climate

Although the mechanisms of climatic change are not completely understood, the potential causes include changes in the Sun's luminosity. Solar activity in the form of sunspots, flares, proton events, and radiation fluctuations has displayed periodic tendencies. Two types of proxy climatic data that can be related to periodic solar activity are varved geologic formations and freshwater diatom deposits. A model for solar luminosity was developed by using the geometric progression of harmonic cycles that is evident in solar and geophysical data. The model assumes that variation in global energy input is a result of many periods of individual solar-luminosity variations. The 0.1-percent variation of the solar constant measured during the last sunspot cycle provided the basis for determining the amplitude of each luminosity cycle. Model output is a summation of the amplitudes of each cycle of a geometric progression of harmonic sine waves that are referenced to the 11-year average solar cycle. When the last eight cycles in Emiliani's oxygen-18 variations from deep-sea cores were standardized to the average length of glaciations during the Pleistocene (88,000 years), correlation coefficients with the model output ranged from 0.48 to 0.76. In order to calibrate the model to real time, model output was graphically compared to indirect records of glacial advances and retreats during the last 24,000 years and with sea-level rises during the Holocene. Carbon-14 production during the last millenium and elevations of the Great Salt Lake for the last 140 years demonstrate significant correlations with modeled luminosity. Major solar flares during the last 90 years match well with the time-calibrated model.

Perry, Charles A.↗

NASA NTRS1986

Calibrated Ancillary System (CAS) user's guide, volume 3

Source record↗

NASA NTRS1986

Calibrated Ancillary System (CAS) user's guide, volume 1

The Calibrated Ancillary System (CAS) provides real-time calibrated parameters from the orbiter downlink (ancillary data) to the Goddard Space Flight Center (GSFC). This user's guide contains the introduction to the equipment, operation, general procedures, and specific procedures of the CAS. Volume 1 includes a general overview of the CAS relationships with other equipment, physical design, and hardware and software subsystems. In addition, a description of the user levels and tasks, an introduction to CAS operation, and an outline of general operating procedures are included.

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NASA NTRS1986

Calibrated Ancillary System (CAS) user's guide, volume 2

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NASA NTRS1986

Calibrated Ancillary System (CAS) user's guide, volume 4

The Calibrated Ancillary System (CAS) provides real-time calibrated parameters from the orbiter downlink (ancillary data) to the Goddard Space Flight Center (GSFC). This user's guide contains the introduction to the equipment, operation, general procedures, and specific procedures of the CAS. Volume 4 presents the GSFC user mission planning procedures covering the mission planning main menu, bulletin board system, ancillary products menu, utility menu procedures, and ancillary support files procedures.

Source record↗

NASA NTRS1986

Calibrated Ancillary System (CAS) user's guide, volume 6

The Calibrated Ancillary System (CAS) provides real-time calibrated parameters from the orbiter downlink (ancillary data) to the Goddard Space Flight Center (GSFC). This user's guide contains the introduction to the equipment, operation, general procedures, and specific procedures of CAS. Volume 6 describes ancillary products procedures, enhancement menu and processing task procedures for SDT/TDT (shuttle data tape/telemetry descriptor tape), database errors and network data driver (NDD) product menu procedures, and utility menu procedures.

Source record↗

NASA NTRS1986

Calibrated Ancillary System (CAS) user's guide, volume 7

The Calibrated Ancillary System (CAS) provides real-time calibrated parameters from the orbiter downlink (ancillary data) to the Goddard Space Flight Center (GSFC). This user's guide contains the introduction to the equipment, operation, general procedures, and specific procedures of CAS. Volume 7 describes the data flow engineer (DFE) user mission planning procedures which include instructions for processing the SDT/TDT (shuttle data tape/telemetry descriptor tape).

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NASA NTRS1986

Calibrated Ancillary System (CAS) user's guide, volume 8

Source record↗

NASA NTRS1986

Calibrated Ancillary System (CAS) user's guide, volume 9

The Calibrated Ancillary System (CAS) provides real-time calibrated parameters from the orbiter downlink (ancillary data) to the Goddard Space Flight Center (GSFC). This user's guide contains the introduction to the equipment, operation, general procedures, and specific procedures of CAS. Volume 9 contains the menu-independent CAS commands. Examples of each command and command parameters are presented. A listing of acronyms and applicable documentation is also provided.

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NASA NTRS1992

SSME Automated Engine Calibration System (AECS)

An algorithm is derived for the real-time calibration of the engine fuel flowmeter and the engine mixture ratio during Space Shuttle Main Engine (SSME) ground testing. Because currently used calibration methods are post-test operations, there exists no fail-safe way of predicting at what mixture ratio a planned test will run. It is proposed that the algorithm developed here be used as part of an Automated Engine Calibration System (AECS) which could ensure that nearly all SSME tests are run at the proper mixture ratio. In this way, AECS has the potential of increasing the efficiency of the SSME ground test program. In addition to the derivation of the algorithm, an overview of this calibration system is presented along with the list of test stand facility instrumentation necessary for AECS implementation.

Greene, William D.↗

NASA NTRS1993

SSME Automated Engine Calibrating System (AECS) alternative algorithm

An algorithm is derived for the real-time calibration of the engine mixture ratio during SSME ground testing. Because currently used calibration methods are post-test operations, there exists no fail-safe way of predicting at what mixture ratio a planned test will run. It is proposed that the algorithm developed here be used as part of an AECS which could ensure that nearly all SSME tests are run at the proper mixture ratio. In this way, AECS has the potential of increasing the efficiency of the SSME ground test program. This algorithm is an alternative to that presented in a previous paper. In addition to the derivation of the algorithm, an overview of this calibration system is presented along with a discussion of a possible single coefficient calibration system and the list of test stand facility instrumentation necessary for AECS implementation.

Greene, William D.↗

DOE OSTI2014

SU-E-T-246: MU Model Implementation for a Passively Scattered Proton Beam: Inclusion of the Bolus Gap and Nozzle Extension Factors

Purpose: To develop and implement an MU model for a passively scattered proton beam, and eliminate the need for patient specific calibrations for field sizes from 3cm to 15cm. This would enable consistent and timely calibrations for a wide variety of patient portals, streamlining the treatment process. Methods: Measurements were initially made using a Standard Imaging A-16 ion chamber and a modified water tank to determine the bolus gap factors (BGF) for multiple combinations of aperture size, bolus thickness, and air gap. The BGF was then separated into two component factors: the bolus thickness factor (BTF) and the nozzle extension factor (NEF). Polynomial curves were generated using the measured data to produce BTF tables for air gaps from 0cm to 30cm and for bolus thicknesses from 0cm to 10cm, and NEF tables for the full range of clinically used nozzle extensions. Additionally, data tables were created for every factor that affects beam output in the MU model. The MUs were then modeled for 487 patient portals and retrospectively compared to the MUs generated from the physical calibrations previously performed. Results: Of the 487 patient portals tested, 100% of the portals used for the comparison were within 2.5% from the MUs generated using a physical calibration, and 95.9% of the MU model portals tested were within 2%. The patient portals tested had field sizes ranging from 2.1cm to 10.1cm, with air gaps from 2cm to 25cm. Output factors for field sizes below 3cm with irregularly shaped fields demonstrated inconsistent results and will be further studied. Conclusion: The most problematic output factor, the BGF, was modeled accurately and consistently using the lowest order polynomial curve fits and interpolation between measured data. The study results demonstrate the robustness of the MU model and the potential for saving valuable personnel and beam time.

07 ISOTOPE AND RADIATION SOURCES↗

NASA NTRS1977

Automated secondary standard for liquid flowmeters

Calibration time is reduced from one hour to fifteen minutes. Accuracies of flowmeter calibrations are approximately 99.75 percent, using this standard. Standard is also used to test or set flow switches.

Hobart, H. F.↗

DOE OSTI2024

Bayes_Opt-SWMM: A Gaussian process-based Bayesian optimization tool for real-time flood modeling with SWMM

Real-time flood model plays a pivotal role in averting urban flood damage, particularly when there is minimal lead time for preparatory measures. However, urban flood modeling in real-time often contends with inherent uncertainties arising from input data uncertainty and parameter ambiguities. Here this study introduces a real-time calibration (RTC) tool called Bayes_Opt-SWMM, specifically tailored for real-time urban flood modeling and uncertainty optimization. This tool leverages the Gaussian process-based Bayesian optimization algorithm and interfaces seamlessly with the Stormwater Management Model (SWMM). It integrates real-time model forcing data and flood monitoring collected through sensors and gauges which are strategically placed within critical locations of urban drainage systems. Our approach hinges on the Surrogate Model based Uncertainty Optimization (SMUO) concept, providing an avenue for enhancing real-time flood modeling. Bayes_Opt-SWMM runs the optimization process using a surrogate model called Gaussian Process emulator with two inference methods: (1) the Gaussian Process (GP) model and (2) Markov Chain Monte Carlo (MCMC) algorithm in GP model (GP_MCMC). Furthermore, three acquisition functions, namely Expected Improvement (EI), Maximum Probability of Improvement (MPI), and Lower Confidence Bound (LCB), facilitate optimal parameter fitting within the surrogate models. The efficiency of GP-based surrogate models in learning SWMM model parameters, leads to an improved uncertainty quantification and accelerated real-time flood modeling in urban areas. Overall, Bayes_Opt-SWMM emerges as a cost-effective and valuable tool for real-time flood modeling and monitoring, with significant potential for managing intelligent storm water systems in urban environments.

54 ENVIRONMENTAL SCIENCES↗