Experimental Measurement Uncertainty Research Articles

Precision comparison of intensity ratios and area ratios in spectral analysis

The long-debated question in analytical chemistry of which of the area ratio or the intensity ratio is the more precise has yielded no definitive analytical conclusion. To address this issue theoretically, we derived analytical solutions for the lower limits of estimation precision for spectral parameters, including the intensity ratio and area ratio, based on the Cramér–Rao lower bound (CRLB) framework for a Gaussian spectrum. The precisions of spectral parameter estimations from the analytical solutions were consistent with results obtained from Monte Carlo simulations. Our theoretical and simulation results revealed that the precision of estimating the area ratio surpassed that of the intensity ratio by a factor of 2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sqrt{2}$$\\end{document}. Additionally, our experimental results aligned well with both theoretical predictions and simulation outcomes, further validating our approach. This increased precision of the area ratio is due to negative covariance between intensity and bandwidth, rather than the area containing more intensity information, as often misinterpreted. Consequently, and quite counter intuitively, prior bandwidth and intensity related information does not improve the area ratio precision: it worsens it. The analytical solution we derived represents the fundamental limits of spectral parameter measurement precision. Thus, it can be used as an alternative method for estimating the minimum error when experimental measurement uncertainty cannot be determined.

Acoustic flow resonances in installed rectangular jets

Zonal Large Eddy Simulations (LES) of complex installed rectangular jet flows are performed for subsonic jet conditions of the Central Institute for Aviation Motors (CIAM) experiment, where a strong tone was reported. For far-field noise modelling, the zonal LES solutions are coupled with the permeable formulation of the Ffowcs Williams and Hawkings (FW-H) method. The obtained noise spectra predictions are compared with the acoustic measurements in the CIAM facility. To reduce statistical noise of the relatively short LES time series, contributions due to several dominant low frequency tones and the remaining broadband signal are computed separately, using a tailored Fourier transform technique for each signal type. For cross-validation, noise spectra measurements of an equivalent isolated round jet in the CIAM facility are compared with the empirical sJet model calibrated on the NASA Small Hot Jet Acoustic Rig (SHJAR) jet noise database. While the two datasets agree reasonably well for mid to high frequencies, larger discrepancies are observed for low frequencies, which are attributed to acoustic reflections in the non-anechoic CIAM facility. The differences in noise levels between the CIAM dataset and the sJet model representing the NASA jet noise data are used to determine the experimental uncertainty of the CIAM noise measurements for each frequency and observer angle. For the installed rectangular jet, it is shown that far-field noise spectra predictions of the zonal LES-FW-H method for both the fundamental tone, its sixth harmonic corresponding to the jet Strouhal number of around 1, and the broadband component are broadly within the experimental error bar for most observer angles. Some discrepancies between predictions of the zonal LES method and the CIAM measurements for the main low frequency tone for the 30o and 90o, where the experimental uncertainty at low frequencies is largest are also noted. After validating the acoustic solutions, spectral and conditional averaging analysis methods are applied to elucidate mechanisms of the acoustic-flow resonance in the installed rectangular jet flow. The numerical dispersion relation is obtained to analyse phase velocities of the upstream and downstream travelling pressure waves in the stream-wise direction. The conditional analysis of pressure fluctuations inside the jet reveals the emergence of internal reflection points corresponding to a rapid change of the acoustic wave phase as well as the saddle points interpreted as localised zones of vorticity shed from the side-wall edges. To independently investigate the effect of trailing edges and corner points of the jet embodiment geometry on closing the acoustic-flow resonance cycle, several modifications of the baseline rectangular nozzle are considered, such as introducing chevron-like lobes and cuts on the trailing edges of the side walls as well as smoothing the sharp corner points of the wall edges. Following the series of additional zonal LES runs with the modified installed nozzle geometries, an optimized tone-less modification of the original installed nozzle was obtained, in broad agreement with the conditional analysis results. The obtained tone-less modification of the installed rectangular jet is further analyzed to provide insights into its similarity and differences from the aeroacoustics of the reference isolated round jet in the same CIAM facility.

Uncertainty evaluation in density and viscosity of nanofluids at different temperatures using Gaussian process regression-based Monte-Carlo simulations

Uncertainty in experimental measurements is likely to be incorporated due to various limitations in measurement instruments, experimental procedures, quantity of chemicals, etc. Obtaining the true properties of nanofluids is a difficult task. Hence, the evaluation of the dynamic viscosity and density is strenuous. The present work aims to study the influence of uncertainties in temperature and concentration on density and dynamic viscosity of Graphene nanoparticle/distilled water, multiwall carbon nanotube/distilled water, and alumina/distilled water nanofluids using Gaussian Process Regression (GPR) learning algorithm guided Monte-Carlo simulations. The GPR algorithm is employed to predict the properties of the nanofluids which are then fed to Monte-Carlo simulations to predict the uncertainty. The noise and uncertainties are introduced in the mole fraction and temperature artificially and are validated using the Kolmogorov-Smirnov test and Quantile-Quantile plot. The influence of different noise levels in the data is also carried out.

Experimental uncertainty evaluation by measuring a micro gear standard using focus variation

Abstract Micro gears play an increasingly important role in various industrial applications, and the minimization of their deviations is challenging for metrology and manufacturing. A promising method is the focus variation technology, which enables areal measurements of micro gears. Practice-related standards are used to determine measurement uncertainties by comparison with calibration values. In this work, the external micro gear standard of the Physikalisch-Technische Bundesanstalt (PTB) is used to evaluate experimental measurement uncertainties of a focus variation coordinate measurement system for the first time. The traceable standard with modules between 0.1 and 1 mm is calibrated using micro tactile coordinate measurements. Optical and tactile measurements are then compared. As a result, small expanded measurement uncertainties of less than 4 µm are achieved.

An experimental platform for semi-autonomous kinetic model refinement combining optimal experimental design, computer-controlled experiments, and optimization leads to new understanding of N[formula omitted]O + O

Automated platforms could enable the unprecedented pace required for modeling the countless proposed alternative fuels relevant to future technologies, but existing platforms rely exclusively on automatically generated computational data and lack experimental validation. Here, we introduce an experimental platform for rapid kinetic model refinement that combines optimal experimental design, computer-controlled experiments, and optimization—each of which are tailored in novel ways to form a cohesive platform together. The optimal experimental design considers (1) realistic uncertainties in both experimental conditions and measurements and (2) diverse reactant mixtures that can include “chemical sensitizers,” which are not necessarily reactants in a specified Quantity of Interest (QoI) but sensitize kinetic information relevant to a QoI. Similarly, our High-Throughput Jet-Stirred Reactor (HT-JSR) features (1) rapid multi-species diagnostics that can measure dozens of species within minutes, (2) a flow delivery system that can prepare up to ∼10-component reactant mixtures, and (3) computer-controlled operation of all components. Finally, a post-processing code automatically retrieves data from the instruments, quantifies uncertainties in both experimental conditions and measurements, and produces self-contained files usable for optimization in our MultiScale Informatics software. This platform is demonstrated for the rate constant for N2O + O ⇌ N2 + O2 as the QoI where, unlike for N2O + O ⇌ NO + NO, proposed values at ∼1000 K span ∼5 orders of magnitude yet give equally good agreement with previous experimental data—suggesting that previous experiments fail to constrain the branching ratio of N2O + O. The results show that optimal conditions with more species as both reactants and analytes—particularly NO2 as both a reactant and analyte—enable unambiguous discrimination of the main products of N2O + O. Specifically, the data preclude N2 + O2 as the main products at ∼1000 K—contrary to most recently proposed values.Novelty and significance statementWe introduce a novel experimental platform for rapid kinetic model refinement that combines optimal design, computer-controlled experiments, and optimization—each uniquely tailored to form a cohesive platform. It notably employs high levels of automation, high-throughput multi-species diagnostics, and uniquely diverse reactant mixtures to accelerate scientific discovery. This platform is shown to achieve a goal that no previous experiment has: decipher the main products of N2O + O. This success—attributable to the platform’s unique design principles—demonstrates the effectiveness of this experimental platform as a tool for accelerating scientific discovery and kinetic model development.

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.