Experimental Measurement Uncertainty Research Articles

Measurement uncertainty of vertical combustion test of civil aircraft interior materials

The civil cabin interior materials vertical combustion test is the necessary test to verify the flame retardancy ability of the floor coverings, textiles, seat cushions and cushions. It is an inspection step required for cabin interior materials before installation, which is of great significance for the safe flight of civil aircraft. During the experiment process, variable factors such as personnel and equipment are highly likely to impact the test results. To ensure the reliability of test results, it is necessary to summarize and evaluate the factors that may affect the results of the test process. Thus, in this paper, the test method, measurement model, and sources of measurement uncertainty have been analysed, and the calculation case of experimental measurement uncertainty has been introduced.

Unified construction of relativistic Hamiltonians.

It is shown that the four-component (4C), quasi-four-component (Q4C), and exact two-component (X2C) relativistic Hartree-Fock equations can be implemented in a unified manner by making use of the atomic nature of the small components of molecular 4-spinors. A model density matrix approximation can first be invoked for the small-component charge/current density functions, which gives rise to a static, pre-molecular mean field to be combined with the one-electron term. As a result, only the nonrelativistic-like two-electron term of the 4C/Q4C/X2C Fock matrix needs to be updated during the iterations. A "one-center small-component" approximation can then be invoked in the evaluation of relativistic integrals, that is, all atom-centered small-component basis functions are regarded as extremely localized near the position of the atom to which they belong such that they have vanishing overlaps with all small- or large-component functions centered at other nuclei. Under these approximations, the 4C, Q4C, and X2C mean-field and many-electron Hamiltonians share precisely the same structure and accuracy. Beyond these is the effective quantum electrodynamics Hamiltonian that can be constructed in the same way. Such approximations lead to errors that are orders of magnitude smaller than other sources of errors (e.g., truncation errors in the one- and many-particle bases as well as uncertainties of experimental measurements) and are, hence, safe to use for whatever purposes. The quaternion forms of the 4C, Q4C, and X2C equations are also presented in the most general way, based on which the corresponding Kramers-restricted open-shell variants are formulated for "high-spin" open-shell systems.

Use of Bayesian Methods in the Process of Uranium Bioleaching by Acidithiobacillus ferrooxidans

This research is focused on investigating the utilization of Bayesian methodologies, specifically the Markov Chain Monte Carlo method, as well as filter sampling by importance and sequential resampling. The objective is to estimate kinetic parameters and state variables associated with the uranium bioleaching process by Acidithiobacillus ferrooxidans. Experimental data of cell concentration, uranium concentration, and concentrations of ferrous and ferric ions, obtained from literature, were employed. These measurements were evaluated using a mathematical model expressed by a system of ordinary differential equations. Three different mathematical models were evaluated, considering different uncertainties in experimental measurements and mathematical models (1% and 5%). The estimation results presented a good fit to the experimental data, with coefficients of determination in the range of 0.95 to 0.99. The validation of the mathematical models was obtained by reproducing the experimental measurements and the Bayesian techniques proved to be suitable for application in the bioleaching process.

Optimization of calibration interval based on equipment metrological history.

The purpose of this paper is to describe a method for optimizing the calibration period of a dosimetry measurement system with a focus on the personal dose equivalents Hp(d) and individual monitoring services. The systematic and analytical method developed provides a justification to the calibration interval based on experimental data and measurement uncertainties. Its main input is the metrological history of the equipment that is then used to predict the drift of the measurement system. The method is used to make the calibration operation more efficient over time in terms of cost and metrology. After a description of the method itself, the example of the OSL dosemeter reading process will be discussed and results will be shown. The method developed may be applied to other measurement processes no matter the technology used.

A modular Bayesian approach to model calibration of low‐fidelity simulation models

AbstractLow‐fidelity computational models have been widely used for the computation of complex engineered systems to greatly save the computational time while sacrificing the computational precision. Model calibration can be implemented for low‐fidelity simulation models to remedy the errors of simulation results. This article proposes a modular Bayesian updating framework that considers epistemic uncertainty to achieve model calibration of low‐fidelity simulation models. The proposed framework mainly contains two steps: (1) A model calibration framework based on Bayesian theory is proposed that can simultaneously quantify the model form uncertainty, model parameter uncertainty, and the experimental measurement uncertainty, (2) the proposed method updates a low‐fidelity surrogate model via a Metropolis–Hastings (M–H) algorithm by using high‐fidelity experimental data. The proposed method greatly improves the prediction accuracy of the simulation model and enhances the computational efficiency. A mathematical example is used to testify the accuracy of the developed method, while the aerodynamics simulation of the NACA0012 airfoil is leveraged to demonstrate the engineering application. The results show that the posterior prediction mean is in better agreement with the experimental mean than the prior prediction mean, suggesting that the modular Bayesian updating method improves the prediction accuracy of low‐fidelity simulation models.

Laser-driven ramp-compression experiments on the national ignition facility

This report details the analyses and related uncertainties in measuring longitudinal-stress–density paths in indirect laser-driven ramp equation-of-state (EOS) experiments [Smith et al., Nat. Astron. 2(6), 452–458 (2018); Smith et al., Nature 511(7509), 330–333 (2014); Fratanduono et al., Science 372(6546), 1063–1068 (2021); and Fratanduono et al., Phys. Rev. Lett. 124(1), 015701 (2020)]. Experiments were conducted at the National Ignition Facility (NIF) located at the Lawrence Livermore National Laboratory. The NIF can deliver up to 2 MJ of laser energy over 30 ns and provide the necessary laser power and control to ramp compress materials to TPa pressures (1 TPa = 10 × 106 atmospheres). These data provide low-temperature solid-state EOS data relevant to the extreme conditions found in the deep interiors of giant planets. In these experiments, multi-stepped samples with thicknesses in the range of 40–120 µm experience an initial shock compression followed by a time-dependent ramp compression to peak pressure. Interface velocity measurements from each thickness combine to place a constraint on the Lagrangian sound speed as a function of particle velocity, which in turn allows for the determination of a continuous stress–density path to high levels of compressibility. In this report, we present a detailed description of the experimental techniques and measurement uncertainties and describe how these uncertainties combine to place a final uncertainty in both stress and density. We address the effects of time-dependent deformation and the sensitivity of ramp EOS techniques to the onset of phase transformations.

Isospin-breaking corrections to light-meson leptonic decays from lattice simulations at physical quark masses

The decreasing uncertainties in theoretical predictions and experimental measurements of several hadronic observables related to weak processes, which in many cases are now smaller than O(1%), require theoretical calculations to include subleading corrections that were neglected so far. Precise determinations of leptonic and semi-leptonic decay rates, including QED and strong isospin-breaking effects, can play a central role in solving the current tensions in the first-row unitarity of the CKM matrix. In this work we present the first RBC/UKQCD lattice calculation of the isospin-breaking corrections to the ratio of leptonic decay rates of kaons and pions into muons and neutrinos. The calculation is performed at fixed lattice spacing (a−1 ≃ 1.730 GeV) on a 483× 96 volume with Nf = 2 + 1 dynamical quarks close to the physical point and domain wall fermions in the Möbius formulation are employed. Long-distance QED interactions are included according to the QEDL prescription and the crucial role of finite-volume electromagnetic corrections in the determination of leptonic decay rates, which produce a large systematic uncertainty, is extensively discussed. Finally, we study the different sources of uncertainty on |Vus|/|Vud| and observe that, if finite-volume systematics can be reduced, the error from isospin-breaking corrections is potentially sub-dominant in the final precision of the ratio of the CKM matrix elements.

Improved Method for the Detection of Highly Polar Pesticides and Their Main Metabolites in Foods of Animal Origin: Method Validation and Application to Monitoring Programme

The application of polar pesticides in agricultural production has been of great interest due to their low costs and their high effectiveness. For this reason, the possibility of their transfer to foods of animal origin is of great concern for human health. The manuscript describes the implementation and validation of an analytical method to detect polar pesticides, at regulatory levels, in three foods of animal origin, including bovine fat, chicken eggs, and cow milk. The method was fully validated to detect glyphosate, glufosinate, and their respective metabolites in the above-mentioned foods obtaining fit-for-purpose sensitivity, recoveries (76–119%), repeatability (≤20%), within-laboratory reproducibility (≤20%), and experimental measurement uncertainty less than 50% as required by the SANTE/11312/2021 criteria. Given the satisfactory results, the applicability of the method to additional molecules belonging to the same category (AMPA, cyanuric acid, ethephon, fosetyl aluminum, HEPA, maleic hydrazide, and N-acetyl-glyphosate) was also evaluated in order to meet possible future requests. Finally, the implemented method was applied to analyse samples over the period of March 2021 to August 2022 from two Italian regions (Umbria and Marche) within the national monitoring programme. In agreement with previously available data, none of the samples analysed showed the presence of glyphosate and glufosinate at levels above the legal limit.

Biaxial strain improving carrier mobility for inorganic perovskite: ab initio Boltzmann transport equation

Inorganic halide perovskites have attracted interest due to their high efficiency and low cost. Considering the uncertainty of experimental measurements, it was important to predict the upper limit of carrier mobility. In this study, the ab initio Boltzmann transport equation, including all electron–phonon interactions, was used to accurately predict the mobilities of CsPbI3, CsSnI3, CsPbBr3, and CsSnBr3. Using the iterative Boltzmann transport equation (IBTE), the calculated mobility for CsPbI3 is µ e = 512/µ h = 379 cm2 V−1 s−1, and Sn-based perovskite exhibited high hole mobility. The longitudinal optical phonons associated with the stretching between halogen anions and divalent metal cations were revealed to be the dominant scattering source for the carriers. Furthermore, the effect of biaxial strain on mobility was investigated. We observed that biaxial compressive strain could improve the mobility of CsPbI3 and CsPbBr3. Surprisingly, under a compressive strain of , the mobilities of CsPbI3 using IBTE approach were improved to µ e = 1176/µ h = 936 cm2 V−1 s−1. It was revealed that the compressive strain could decrease the effective mass of CsPbI3 and CsPbBr3.

Fabrication and Characterization of an Optimized Low-Loss Two-Mode Fiber for Optoacoustic Sensing.

An optimized multi-step index (MSI) 2-LP-mode fiber is proposed and fabricated with low propagation loss of 0.179 dB/km, low intermodal crosstalk and excellent bend resistance. We experimentally clarified the characteristics of backward Brillouin scattering (BBS) and forward Brillouin scattering (FBS) induced by radial acoustic modes (R0,m) in the fabricated MSI 2-LP-mode fiber, respectively. Via the use of this two-mode fiber, we demonstrated a novel discriminative measurement method of temperature and acoustic impedance based on BBS and FBS, achieving improved experimental measurement uncertainties of 0.2 °C and 0.019 kg/(s·mm2) for optoacoustic chemical sensing. The low propagation loss of the sensing fiber and the new measurement method based on both BBS and FBS may pave the way for long-distance and high spatial resolution distributed fiber sensors.

Validation of CFD simulations of the moored DeepCwind offshore wind semisubmersible in irregular waves

This article examines the use of computational fluid dynamics (CFD) simulations to predict the response of a floating wind platform to irregular-wave excitation. This work was conducted as part of the Reproducible CFD Joint Industry Project for Floating Offshore Wind Applications and involved verification across several participants and modeling tools and validation against experiments. The authors pay special attention to the uncertainties in both CFD results and experimental measurements. We perform detailed comparisons of the incident waves and the motion of a moored structure. The nonlinear, low-frequency resonance motion is of particular interest because it potentially drives the mooring and tower-base loads. The verification and validation study is partially successful in that the CFD simulations capture the low-frequency slow-drift motion well but underpredict the low-frequency pitch resonance. This underprediction can be attributed in part to the CFD incident waves, which showed some discrepancies with the experimental waves, especially around extreme events. The effects of the wave discrepancies are also estimated and investigated using a mid-fidelity OpenFAST model. Overall, the present study increases our confidence in using CFD simulations to predict the global performance of offshore wind platforms in irregular waves and to produce data for the calibration of lower-fidelity models.

Evaluation of Fire Models by Using Local and Global Metrics and Experimental Uncertainty Estimates: Application to OECD/NEA Prisme Door Tests

The use of numerical methods in fire safety investigations for civil buildings and nuclear facilities has received enormous attention in recent years. To evaluate quantities—such as gas temperatures—in fire models, local metrics using single points (e.g. comparing maximum or minimum peak value of two time series) are well-established. Experimental (measurement and model input) uncertainty estimates can be used to quantify the model uncertainty. Although the peak value is a relevant and well-defined quantity, global metrics comparing the entire course of two time series can often provide additional information for the validation of fire models. A comparative methodology COMET for evaluating the predictive power of fire models is developed and presented in this paper. In the methodology, both local and global metrics are combined to incorporate the explanatory power of both quantities in the validation process. While uncertainty analysis is well established for peak values, to the best of our knowledge, there are no analytic results on quantifying the uncertainty of the global metric in the literature. We address the latter based on experimental measurements and derive confidence regions for both metrics. Finally, this paper summarizes the results using COMET to validate the Fire Dynamics Simulator (FDS) version 6 for a room fire scenario. Validation examples are tests 3, 4 and 5 of the DOOR series of the international OECD/NEA PRISME project, in which the transport of heat and flue gases through a door between two rooms was examined. Using COMET, we can easily identify sensors with high level of agreement between model and experimental results with respect to the local and/or the global metric.

Characterization of particle size and moisture content effects on mechanical and feeding behavior of milled corn (Zea mays L.) stover

Interest in biofuels has grown in recent years. Unfortunately, biofuel refineries are unable to operate at full capacity due to handling and feeding issues as the feeding systems for biomass are often poorly designed. To inform more effective and reliable handling and feeding systems, this study presents mechanical (moisture, particle size/distribution, bulk density, compressibility, and elastic recovery) and flow characterization (critical arching distance and feed rate in a wedge hopper and screw feeder) of corn (Zea mays L.) stover. Results showed that particle size has the most significant effect on flowability, while moisture content plays a role for a sample with large particles. For example, the feed rate of a sample with a nominal particle size of 3 mm and 10% moisture content was 44 lb./h, compared a feed rate of 24 lb./h for a sample with the same moisture content but larger nominal particle size of 25 mm. Samples with nominal particle sizes of 3 mm and moisture contents of 10% and 30% exhibited much smaller differences in feed rate. The feed rate of the former sample was 44 lb./h, and the feed rate of the latter 46 lb./h, such that the difference was within experimental measurement uncertainty. Additionally, the critical arching distance increases with increasing particle size and exhibits a small dependence on moisture content. The overall study concludes that milled corn stover feedstocks with smaller particles exhibit substantially better flowability.

Development of an optical thermography system using a pumped two-dye fluorescence technique

This work demonstrates the development of a novel backside thermography technique based on the temperature sensitivity of laser-induced fluorescence in flowing two-dye solutions. The approach utilizes visible light and optically transparent packaging materials to obtain spatially resolved transient thermal measurements. This makes it a relatively simple, inexpensive, and flexible approach for lab-scale experimental characterizations using economical cameras and optics. Additionally, both heating and cooling of the thermography stage can be achieved by passing temperature-controlled water through plastic packaging components. A custom-built experimental setup was designed, constructed, and used to study the performance of seven two-dye Rhodamine B (RhB)-Rhodamine 110 (Rh110) fluorescent solutions. The effect of dye concentration ratio on sensitivity, maximum frame rate, and excitation area was characterized. Using an optimal dye concentration of unity, it was shown that frame rates of 265–3200 Hz are achievable for excitation areas with diameters of 15.5–4.3 mm, respectively, using the current setup. The calibrated system was used to demonstrate in-situ measurements showing the importance of two-dye light compensation, as well as backside thermography using a simple droplet contact method to investigate temporal response. Experiments were conducted in the range of 25–55 °C with a spatial resolution of 30 µm. The experimental uncertainty of the temperature measurements was calculated to be ±2.1 °C and the technique's ability to account for error due to light fluctuations and non-uniform illumination was demonstrated. Finally, the effect of dye photobleaching during prolonged testing was studied and it was shown that photobleaching can be reduced, and even eliminated, by maintaining a nominal low flow rate of the pumped two-dye solution.

Distributed strain and temperature fast measurement in Brillouin optical time-domain reflectometry based on double-sideband modulation.

A novel distributed strain and temperature fast measurement method in Brillouin optical time-domain reflectometry (BOTDR) system based on double-sideband (DSB) modulation is proposed. The single-wavelength probe light is modulated into dual-wavelength probe light with a fixed phase difference by using carrier suppressed DSB modulation. The interaction between the Brillouin scattering signals corresponding to dual-wavelength probe light forms a Brillouin beat spectrum (BBS). The distributed temperature and strain are obtained by only measuring the peak power trace of the BBS and one of the slope power trace of the two Brillouin gain spectrum (BGS) corresponding to dual-wavelength probe light. The proposed method does not require scanning the Brillouin spectrum and does not require using optical fibers with multiple Brillouin scattering peaks as sensing fibers, and thus features fast measurement speed and wide variety of sensing fiber types. In a proof-of-concept experiment, the temperature uncertainty of 1.3 °C and the strain uncertainty of 36.3 με are respectively achieved over a 4.5-km G.657 fiber with 3 m spatial resolution and 30 s measurement time. The experimental measurement uncertainties of temperature and strain of the proposed method are almost equivalent to that of the method by using BGS scanning and special fibers.

High-Precision Surface Scattering Measurement System and Uncertainty Analysis Applied in Laser Protective Materials Diagnostics

The current measurement system of surface scattering rate applied in laser protective materials has the defects of low accuracy, discontinuous diagnosis region and narrow infrared measuring waveband. In order to make up for these shortcomings, a high-precision material-surface-scattering-rate measurement system based on a three-hole integrating sphere is proposed, which can realize the high-precision quantitative measurement on any region of coating surface from near-infrared to far-infrared band. Firstly, a new quantitative relationship between the luminous flux received by detector and the surface scattering rate of coating is obtained by modifying the existing integrating sphere scattering model. Secondly, a high-precision scattering characteristic measurement system based on a three-hole integrating sphere is designed and achieved. The influence of the main design parameters of the integrating sphere on the expected measuring accuracy of the system is investigated by using a TracePro simulation. Accordingly, the optimal design parameters of the system are given. Then, the main sources of the relative measurement uncertainty for the scattering rate are investigated experimentally, and four main relative uncertainty factors are evaluated quantitatively. Finally, according to the error propagation theory, the total experimental relative measurement uncertainty of the system is obtained, which is ±2.22% and 26–56% higher than the current measuring accuracy. The new coating-scattering-rate measurement system proposed in this paper can provide an effective experimental detection means for high-precision quantitative measurement and a performance evaluation for laser-protective-coating surface-scattering rate.

Multichannel autocalibration for the Atmospheric Imaging Assembly using machine learning

Context. Solar activity plays a quintessential role in affecting the interplanetary medium and space weather around Earth. Remote-sensing instruments on board heliophysics space missions provide a pool of information about solar activity by measuring the solar magnetic field and the emission of light from the multilayered, multithermal, and dynamic solar atmosphere. Extreme-UV (EUV) wavelength observations from space help in understanding the subtleties of the outer layers of the Sun, that is, the chromosphere and the corona. Unfortunately, instruments such as the Atmospheric Imaging Assembly (AIA) on board the NASA Solar Dynamics Observatory (SDO), suffer from time-dependent degradation that reduces their sensitivity. The current best calibration techniques rely on flights of sounding rockets to maintain absolute calibration. These flights are infrequent, complex, and limited to a single vantage point, however. Aims. We aim to develop a novel method based on machine learning (ML) that exploits spatial patterns on the solar surface across multiwavelength observations to autocalibrate the instrument degradation. Methods. We established two convolutional neural network (CNN) architectures that take either single-channel or multichannel input and trained the models using the SDOML dataset. The dataset was further augmented by randomly degrading images at each epoch, with the training dataset spanning nonoverlapping months with the test dataset. We also developed a non-ML baseline model to assess the gain of the CNN models. With the best trained models, we reconstructed the AIA multichannel degradation curves of 2010–2020 and compared them with the degradation curves based on sounding-rocket data. Results. Our results indicate that the CNN-based models significantly outperform the non-ML baseline model in calibrating instrument degradation. Moreover, multichannel CNN outperforms the single-channel CNN, which suggests that cross-channel relations between different EUV channels are important to recover the degradation profiles. The CNN-based models reproduce the degradation corrections derived from the sounding-rocket cross-calibration measurements within the experimental measurement uncertainty, indicating that it performs equally well as current techniques. Conclusions. Our approach establishes the framework for a novel technique based on CNNs to calibrate EUV instruments. We envision that this technique can be adapted to other imaging or spectral instruments operating at other wavelengths.

High-energy density hohlraum design using forward and inverse deep neural networks

We present the results of a study where we use machine learning to enhance hohlraum design for opacity measurement experiments. Opacity experiments on laser facilities use hohlraums, which, when their interior walls are illuminated by the National Ignition Facility (NIF) lasers, produce a high radiation flux that heats a central sample to a temperature that is constant over a measurement time window. Given a baseline hohlraum design and a computational model, we train a deep neural network to predict the time evolution of the radiation temperature as measured by the Dante diagnostic. This enables us to rapidly explore design space and determine the effect of adjusting design parameters. We also construct an “inverse” machine learning model that predicts the design parameters given a desired time history of radiation temperature. Calculations using the machine learning model demonstrate that improved performance over the baseline hohlraum could reduce sensitivities and uncertainties in experimental opacity measurements.

Contribution of the Darwin operator to non-leptonic decays of heavy quarks

We compute the Darwin operator contribution ( 1/{m}_b^3 correction) to the width of the inclusive non-leptonic decay of a B meson (B+, Bd or Bs), stemming from the quark flavour-changing transition b → {q}_1{overline{q}}_2{q}_3 , where q1, q2 = u, c and q3 = d, s. The key ideas of the computation are the local expansion of the quark propagator in the external gluon field including terms with a covariant derivative of the gluon field strength tensor and the standard technique of the Heavy Quark Expansion (HQE). We confirm the previously known expressions of the 1/{m}_b^3 contributions to the semi-leptonic decay b → {q}_1mathrm{ell}{overline{nu}}_{mathrm{ell}} , with ℓ = e, μ, τ and of the 1/{m}_b^2 contributions to the non-leptonic modes. We find that this new term can give a sizeable correction of about −4 % to the non-leptonic decay width of a B meson. For Bd and Bs mesons this turns out to be the dominant correction to the free b-quark decay, while for the B+ meson the Darwin term gives the second most important correction — roughly 1/2 to 1/3 of the phase space enhanced Pauli interference contribution. Due to the tiny experimental uncertainties in lifetime measurements the incorporation of the Darwin term contribution is crucial for precision tests of the Standard Model.

Uranium concentration using reactive polymer thin films for spectroscopic analyses

This contribution describes the development of reactive polymer films for the concentration of uranium from circumneutral pH solutions for spectroscopic analyses. These films were prepared by grafting uranium-selective polymers from polyethersulfone (PES) films via UV-initiated polymerization, and by introducing uranium-selective functional groups to polyacrylonitrile (PAN) films by chemical reaction. Ellipsometry was used to study poly(phosphoric acid 2-hydroxyethyl methacrylate ester) film growth kinetics on PES films. X-ray photoelectron spectroscopy of modified PAN films revealed conversion of nitrile groups to amidoxime groups to be as high as 40% and showed that the extent and depth of reaction could be varied precisely. Static uptake experiments with solutions of depleted uranium spiked with 233U were conducted to determine uranium binding capacities and kinetics of the modified polymer films at different pH values from 4 to 8. Sorption isotherm data were fitted to the Langmuir model, and the highest sorption capacities of 1.09 × 10−2 ± 1.03 × 10−3 mmol m−2 and 1.02 × 10−2 ± 3.00 × 10−3 mmol m−2 were obtained at pH 6 for modified PAN (M-PAN) and PES (M-PES) films. Capacities at pH 4 and 8 were lower and could be explained by differences in sorption mechanisms. Uranium batch uptake kinetics followed a pseudo-second order rate model. Equilibrium uptake was attained within 3 h for M-PAN film and 1 h for M-PES film. Alpha spectroscopy pulse height spectra were analyzed to study the role of selective layer film thickness on peak energy resolution. Full width at half maximum values from 29 to 41 keV were recorded for M-PAN film and from 26 to 45 keV for M-PES film. Whereas uranium uptake increased with selective layer film thickness and varied with polymer chemistry/extent of modification, the peak energy resolution was independent of layer thickness and polymer chemistry within the experimental measurement uncertainties. Results from this work are being used to guide the development of thin-film composite membrane-based detection methods for the rapid, fieldable analysis of radionuclides in water for nuclear forensics investigations and environmental studies.