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Enhanced Dual Confocal Measurement System
A measurement instrument utilizing dual, chromatic, confocal, distance sensors has been jointly developed by General Atomics (GA) and Sandia National Laboratories (SNL) for thickness and flatness measurement of target components used in dynamic materials properties (DMP) experiments on the SNL Z-Machine (Z). Compared to previous methods used in production of these types of targets, the tool saves time and yields a 4x reduction in thickness uncertainty which is one of the largest sources of error in equation of state (EOS) measurements critical to supporting the NNSA’s Stockpile Stewardship program and computer modeling of high energy density experiments. It has numerous differences from earlier instruments operating on the dual confocal sensor principle to accommodate DMP components including larger lateral travel, longer working distance, ability to measure flatness in addition to thickness, built-in thickness calibration standards for quickly checking calibration before and after each measurement, and streamlined operation. Thickness and flatness of 0.2mm-3.3mm thick sections of diamond machined copper and aluminum can be measured to “sub-micron” accuracy. Sections up to 6mm thick can be measured with as-yet undermined accuracy. Furthermore, samples must have one surface which is flat to within 300µm, lateral dimensions of no more than 50mm x 50mm, and height less than 40mm.
Calculational Model of the Radiation Calibration Lab (RCL) and the Neutron Measurements performed at the Facility, with a 252 Cf Source
Calibration of detectors measuring gamma, neutron, alpha and beta radiation, and of personal dosimeters used at Lawrence Livermore National Laboratory (LLNL), is performed at the Radiation Calibration Lab (RCL). The calibrations done with a standard calibrated 252 Cf source are a function of the energy spectra, fluence and dose of the source. A detailed calculational model of the RCL has been carried out with the MCNP6 code. The calculations have also reproduced quite well the measurements of the fluence and dose rates for the bare and moderated 252 Cf source carried out by R. Radev using the Rospec Spectrometer and by Clark and Wilson using a Passive Neutron Spectrometer. The importance of having the calculational model of the RCL facility is to calculate the dose rates expected for a given planned measurement, optimizing the choice of detectors, design and shielding materials before the actual measurement are carried out, resulting in a more efficient and time saving measurement. Furthermore, an accurate model of the facility allows to detect possible problems with the measurement.
Infrared Cloud Imager Instrument Intercomparison Report
The Infrared Cloud Imager Instrument Intercomparison was a guest instrument deployment by NWB Sensors to the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) User Facility observatory on the Southern Great Plains (SGP) between May 18 and December 12, 2023. NWB Sensors is a company that has developed a commercially available infrared cloud imager (ICI). The ICI provides radiometrically calibrated, full-sky images of the downwelling infrared radiance in the 7.3-14 µm band. In addition, it provides cloud radiance as the residual between the observed radiance and the modeled cloud-free radiance as well as derived cloud products. The instrument is used in applications that require consistent detection of clouds across day and night. For more information, consult the instrument's webpage. The primary goal of the deployment was to validate the radiometric accuracy of the ICI. The ICI uses a proprietary calibration method to convert the raw data from its infrared camera into downwelling radiance. Unlike similar instruments, the system does not have an onboard blackbody calibration standard. Instead, NWB Sensors characterizes each ICI camera individually in an environmental chamber while looking at a blackbody standard. The resulting (proprietary) calibration is used operationally in the instrument and has been demonstrated to be stable over long periods. To validate the radiometric products from the ICI, an intercomparison between the ICI data products and those from ARM’s atmospheric emitted radiance interferometer (AERI) was made. The AERI is a best-in-class instrument for measuring downwelling infrared radiance (Gero et al. 2025). A weighted integration of the AERI’s spectral radiances across the ICI’s camera response was performed. The resulting radiance (herein called the AERI radiance) was directly compared to the zenith radiance concurrently observed by the ICI. The results of these comparisons are reported in the next section of this report.
Diode laser spectrum of nitric acid at 5.9 microns and carbonyl sulfide frequency/wavelength standards for calibration of nitric acid bands both at 5.9 and 11.4 microns
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IUVS echelle‐mode observations of interplanetary hydrogen: Standard for calibration and reference for cavity variations between Earth and Mars during MAVEN cruise
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Calibrated permeation standards
A permeation standard is provided. The permeation standard may include a substrate that is impermeable to an analyte, an orifice disposed in the substrate, and a permeable material filling the orifice. The orifice and the permeable material are configured to provide a predetermined transmission rate of the analyte through the permeation standard. Also provided herein are methods for forming the permeation standard.
A Derivative Standard Polarimeter Calibration
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Precision calibration of calorimeter signals in the ATLAS experiment using an uncertainty-aware neural network
The ATLAS experiment at the Large Hadron Collider explores the use of modern neural networks for a multi-dimensional calibration of its calorimeter signal defined by clusters of topologically connected cells (topo-clusters). The Bayesian neural network (BNN) approach not only yields a continuous and smooth calibration function that improves performance relative to the standard calibration but also provides uncertainties on the calibrated energies for each topo-cluster. The results obtained by using a trained BNN are compared to the standard local hadronic calibration and to a calibration provided by training a deep neural network. The uncertainties predicted by the BNN are interpreted in the context of a fractional contribution to the systematic uncertainties of the trained calibration. They are also compared to uncertainty predictions obtained from an alternative estimator employing repulsive ensembles.
Problems in calibrating a polar nephelometer
A calibration procedure for nephelometers which is based on the method developed by Pritchard and Elliott (1960) is outlined. Basically, the method consists of comparing the intensity of the light scattered from the particles in the common volume with the intensity reflected from a calibration standard. A proof of the calibration method is given.
Measurements of Line Positions and Strengths of HD O-18 and D2 O-18 in the 2500-4280 cm(exp -1) Region
Measurements of line positions and strengths of D2 O-18 and HD O-18 were obtained with a Fourier transform spectrometer. The data were analyzed to obtain energy levels of the (100), (020), and (001) vibrational states of HD O-18 and the (001) and (011) states of D2 O-18 and the vibrational bands of these states connected to the ground state covered the spectral region from 2500 to 4278 cm(exp -1). 456 absorption lines of D2 O-18 and 856 lines of HD O-18 were assigned from the spectra. The measurements were of oxygen-18 enriched samples of deuterated water vapor and the spectra also contained features of HD O-16, D2 O-16, H2 O-16, H2 O-17 and H2 O-18 of which several were used as frequency calibration standards.
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.
Preparation of calibrated test packages for particle impact noise detection
A standard calibration method for any particle impact noise detection (PIND) test system used to detect loose particles responsible for failures in hybrid circuits was developed along with a procedure for preparing PIND standard test devices. Hybrid packages were seeded with a single gold ball, hermetically sealed, leak tested, and PIND tested. Conclusions are presented.
Design Optimization and Measurement Uncertainty of an Electromagnetic Level Sensor for Liquid Metal Reactors
Here, this article describes the design and operation of a prototype mutual inductance level sensor (MILS) and the development and validation of a finite-element analysis (FEA) model describing its behavior. The MILS was designed for use in liquid sodium up to temperatures of 650 °C in the Mechanisms Engineering Test Loop (METL) at Argonne National Laboratory (ANL). Preliminary testing was performed in a room temperature test stand with aluminum acting as an analog for the sodium to better understand sensor performance and provide accurate code validation data. This experimental data, along with material properties found in literature, were used to validate an FEA model in ANSYS Maxwell. The validated ANSYS Maxwell model was used to examine the performance of the MILS in various environments and under various operating conditions. Simulations suggest the following: The MILS will perform adequately in liquid sodium and liquid lead at temperatures up to 650 °C . The temperature dependence of electrical conductivity imposes a temperature dependence on the sensor that requires proper compensation. The MILS signal sensitivity is maximized when mutual inductance between sensor coils is maximized, and sensor geometry should be selected to account for this factor. The operating frequency of the MILS can be optimized and is dependent on process fluid material, operating temperature, and materials/geometry of sensor system. Finally, the use of a stainless-steel isolating thimble does not adversely affect the sensor signal. The primary sources of error for this MILS system are the accuracy of the calibration standard against which the sensor is calibrated, and the temperature dependence of the sensor. This work contains all the necessary details to recreate the FEA model and results. This model can be used to optimize the performance of a MILS in any operating environment to read any electrically conductive working fluid.
Calibration of 2-D soil zymography for correct analysis of enzyme distribution
Soil zymography is a new technique developed to visualize two-dimensional distributions of enzyme activities. The method is composed of incubating a membrane saturated with an enzyme-specific fluorogenic substrate on a surface of the soil sample, followed by recording the membrane image generated by a fluorescent product (e.g. MUF: methylumbelliferone) in ultraviolet light. Despite its relative ease of use, performing zymography involves multiple user-made decisions that might affect the accuracy of enzyme activity estimates. Thus, unification of the zymography methodology is required for correct estimations and comparisons of various studies. We investigated the following methodological aspects of the implementation of zymography: (a) camera settings and image processing, (b) effects of evaporation and (c) calibration procedures. Camera settings (shutter speeds or exposure time) affected the intensity of background fluorescence and signal-to-noise ratios (SNR). However, because their combined effects varied depending on MUF concentrations, light and camera setting need to be optimized for the expected range of MUF concentrations prior to zymography. Evaporation of MUF solution from the membrane had no effect on fluorescence. Relations between MUF concentration and intensity of fluorescence during calibrations demonstrated a saturated pattern and were strongly affected by image noise outside the optimal range (e.g. 8–14 μm MUF pixel -1 ). We developed a new calibration approach that is based on a piecewise linear regression. The new approach accounted for specific ranges of MUF concentration and uses nonuniformly saturated membranes, reflecting the real distribution of enzyme activities in soil. The new calibration algorithm eliminated biases of the standard calibration and resulted in greater accuracy in predicting MUF concentrations.
High-Resolution Electron-Impact Study of the Far-Ultraviolet Emission Spectrum of Molecular Hydrogen
The emission spectrum of molecular hydrogen produced by electron-impact excitation at 100 eV has been measured in the wavelength range 1140-1690 A. High-resolution, optically thin spectra (delta(lambda) = 0.136 A) of the far-ultraviolet (FUV) Lyman and Werner band systems have been obtained with a newly constructed 3 m spectrometer. Synthetic spectral intensities based on the transition probabilities calculated by Abgrall et al. are in very good agreement with experimentally observed intensities. Previous modeling that utilized Allison & Daigarno band transition probabilities with Hoenl-London factors breaks down when the transition moment has significant J dependence or when ro-vibrational coupling is significant. Ro-vibrational perturbation between upsilon = 14 of the B(sup 1)Sigma(sup +, sub u) state and upsilon = 3 of the C(sup 1)Pi(sub u) state and the rotational dependence of the transition moment in the bands of the Lyman system are examined. Complete high-resolution experimental reference FUV spectra, together with the model synthetic spectra based on the Abgrall transition probabilities, are presented. An improved calibration standard is obtained, and an accurate calibration of the 3 m spectrometer has been achieved.
Application of Indirect Quantification of 133mXe to Calibration of HPGe Detector
The INL Noble Gas Laboratory provides intercomparison samples for the noble gas analysis laboratories as part of the CTBTO PrepCom IMS. Xe-133m is one of the four relevant radionuclides in nuclear explosion monitoring. Without commercially available Xe-133m calibration standards laboratories must create and improve calibration methods. Improvements in calibration methods at the INL NGL benefit the CTBTO PrepCom through better certified values for Xe-133m intercomparison samples. Calibration of High Purity Germanium detectors for Xe-133m quantification is complicated by the coexistence of Xe-133 in samples under analysis. Xe-133 is typically produced in larger quantities, has higher gamma emission probabilities, and its gammas are detected more efficiently than Xe-133m. Xe-133m activity of samples can be indirectly inferred through the 133:133m activity ratio of a batch of material, and the Xe-133 counts in the assay of a small aliquot of the same material. This indirect quantification method can be leveraged to perform detector calibrations for quantification of Xe-133m. Calibrations can be performed by inferring the Xe-133m to certify the sample, and direct counting to determine detector efficiency. A comparison of method results will be shown.
Characterization and Uncertainty Analysis of a Reference Pressure Measurement System for Wind Tunnels
This paper presents the calibration results and uncertainty analysis of a high-precision reference pressure measurement system currently used in wind tunnels at the NASA Langley Research Center (LaRC). Sensors, calibration standards, and measurement instruments are subject to errors due to aging, drift with time, environment effects, transportation, the mathematical model, the calibration experimental design, and other factors. Errors occur at every link in the chain of measurements and data reduction from the sensor to the final computed results. At each link of the chain, bias and precision uncertainties must be separately estimated for facility use, and are combined to produce overall calibration and prediction confidence intervals for the instrument, typically at a 95% confidence level. The uncertainty analysis and calibration experimental designs used herein, based on techniques developed at LaRC, employ replicated experimental designs for efficiency, separate estimation of bias and precision uncertainties, and detection of significant parameter drift with time. Final results, including calibration confidence intervals and prediction intervals given as functions of the applied inputs, not as a fixed percentage of the full-scale value are presented. System uncertainties are propagated beginning with the initial reference pressure standard, to the calibrated instrument as a working standard in the facility. Among the several parameters that can affect the overall results are operating temperature, atmospheric pressure, humidity, and facility vibration. Effects of factors such as initial zeroing and temperature are investigated. The effects of the identified parameters on system performance and accuracy are discussed.