Iterative model-based experimental design for efficient uncertainty minimization of chemical mechanisms

The uncertainties of chemical kinetic model parameters induce uncertainties in model predictions. Automatic optimization and uncertainty minimization techniques have been developed to constrain these uncertainties based on sets of experimental target data for quantities of interest. While such methods were frequently used to optimize models for relatively well-studied systems with large numbers of available targets, only few of these experimental data points may be of crucial importance. In addition, for novel fuel candidates such as biofuels and synthetic fuels, the number of available measurements is generally limited. Thus, an important aspect to be explored in this context is the number of experimental data points required to achieve a certain degree of uncertainty reduction, and the determination of optimal experimental conditions for these. To target this question, a model-based experimental design framework based on the criterion of D-optimality is used in the present work to automatically identify these optimal conditions. As an example, the auto-ignition of dimethyl ether is investigated. The majority of experiments with high priority cover the intermediate- and low-temperature regimes, where the employed prior model exhibits the largest prediction uncertainties. It is also found that 90 % of the maximum observed reduction of average prediction uncertainty in ignition delay times can be achieved based on only the ten most informative experiments alone. The results thus demonstrate that few well-selected measurements allow for efficient model uncertainty reduction, and the employed approach provides an effective means of identifying the optimal conditions, which is useful for further experimental investigation. On the other hand, the inclusion of more experiments into the calibration process still provides additional benefit in terms of the posterior uncertainties of a number of important model parameters, which points to the importance of taking such data into account in case of their availability.     

From inherent correlation to constrained measurement: Model-assisted calibration in MBMS experiments

Synchrotron-based molecular-beam mass spectrometry (MBMS) can provide detailed species-resolved information to help develop, validate and optimize combustion kinetic models. While quantification of stable species can be achieved within 30% uncertainty, the measured mole fractions of reactive intermediates often have large systematic errors, mainly due to the large uncertainties associated with estimated photoionization cross sections. These measurements are therefore less effective in improving the model accuracy, and it remains a challenge to make full use of those data for important reactive intermediates with relatively large uncertainties. In the present work, we propose a model-assisted calibration method to reduce the uncertainty of the measurements for those reactive species in the MBMS experiments. The method takes advantage of the inherent correlation of the systematic uncertainty in the MBMS measurements and uses the accurate model predictions to calibrate the correlated experimental data. By global uncertainty analysis, the kinetic model for the methanol/O₂ flame was analyzed to select the optimal experimental conditions for which the model prediction of the hydroxymethyl radical (CH₂OH) has the smallest uncertainty. Then the correlation factor for the systematic uncertainty is determined by analyzing the new measurement and the model prediction under the designed condition. The correlation factor determined has been successfully used to calibrate the peak mole fraction of the CH₂OH radical in a laminar premixed methanol flame, reported earlier.     

不确定海洋环境中基于主成分量的稳健检测器

传统的信号检测算法在不确定的海洋环境中性能出现下降。基于贝叶斯原理的最优检测算法可以实现对不确定海洋环境中信号的有效检测,但是其突出问题是计算量较大。本文提出了一种基于主成分量分析的稳健信号检测器,该检测器利用贝叶斯原理将环境先验信息引入到检测算法中,同时使用主成分量分析方法来降低运算量,实现了对信号的快速有效检测。分别使用标准失配海洋模型和海上实测数据进行了计算机仿真和实验验证,结果表明:(1)基于主成分量的稳健信号检测器检测性能达到最优贝叶斯检测器的效果。(2)本文方法在线运算速度是贝叶斯最优检测器的5^一8倍。(3)环境先验信息失配的情况下,扩大海洋环境参数模型的不确定度范围有助于提高检测性能。      

Measurement of the neutron lifetime using a proton trap

We report a new measurement of the neutron decay lifetime by the absolute counting of in-beam neutrons and their decay protons. Protons were confined in a quasi-Penning trap and counted with a silicon detector. The neutron beam fluence was measured by capture in a thin 6LiF foil detector with known absolute efficiency. The combination of these simultaneous measurements gives the neutron lifetime: tau(n)=(886.8+/-1.2[stat]+/-3.2[syst]) s. The systematic uncertainty is dominated by uncertainties in the mass of the 6LiF deposit and the 6Li(n,t) cross section. This is the most precise measurement of the neutron lifetime to date using an in-beam method.     

A two-dimensional multispecies fluid model of the plasma in an ACplasma display panel

A time dependent, two-dimensional model for simulating the plasma evolution in an AC plasma display panel (AC-PDP) is described. Reaction-convection (mobility)-diffusion equations for charged particles and excited heavy neutral species are solved along with Poisson's equation, a radiation transport equation, a surface charge buildup equation, and an external L-R-C circuit equation using a fully implicit numerical method. Electron-driven rate coefficients are computed with a 0-D Boltzmann solver in the local field approximation. For studying the particle dynamics in pure helium, we consider a reduced model in which radiation transport is ignored and the excited species manifold is collapsed to composite metastable and excited states. The model predictions of breakdown voltage are quite sensitive to the value of the secondary electron emission coefficient assumed and the uncertainties in the electron-driven reaction rates. An initial comparison between the model predictions and I-V measurements from a specially constructed helium-filled panel is made with qualitatively similar behavior. The lack of quantitative agreement can be explained by a combination of uncertainties in the model input data and uncertainty in the initial surface charge state in the experiments     

Deep-inelastic inclusive ep scattering at low x and a determination of \alpha_s

A precise measurement of the inclusive deep-inelastic scattering cross section is reported in the kinematic range GeV and . The data were recorded with the H1 detector at HERA in 1996 and 1997, and correspond to an integrated luminosity of 20 pb. The double differential cross section, from which the proton structure function and the longitudinal structure function are extracted, is measured with typically 1% statistical and 3% systematic uncertainties. The measured derivative is observed to rise continuously towards small x for fixed . The cross section data are combined with published H1 measurements at high for a next-to-leading order DGLAP QCD analysis. The H1 data determine the gluon momentum distribution in the range to within an experimental accuracy of about 3% for GeV. A fit of the H1 measurements and the data of the BCDMS collaboration allows the strong coupling constant and the gluon distribution to be simultaneously determined. A value of is obtained in NLO, with an additional theoretical uncertainty of about , mainly due to the uncertainty of the renormalisation scale. Received: 21 December 2000 / Revised version: 10 May 2001 / Published online: 6 July 2001     

Friction-induced vibration: Quantifying sensitivity and uncertainty

The limited success of predictive models of friction-induced vibration can, in part, be attributed to the inherent sensitivity of friction-coupled systems to variations, often uncontrolled, in parameter values such as the friction coefficient. This paper explores the sensitivity and uncertainty of predictions from a modal point of view, using models of a realistic complexity. A method for efficiently estimating prediction error bounds is presented and validated using representative parametric uncertainties. Measurement uncertainties are quantified providing an input for the error-bound analysis. Taken together, this forms the foundation for a direct comparison of predictions with experimental results from sliding contact tests.     

中子散射成像探测角分辨研究

中子散射成像技术是近年来国外正在发展的一项新型辐射成像技术, 在深空宇宙探测、核材料监控等方面具有广阔的应用前景. 角分辨是衡量该技术成像能力的一项重要参数. 研究了位置不确定度和能量分辨对角分辨的影响. 理论分析表明: 以不同角度散射, 成像的角分辨不同; 位置不确定不仅直接影响角分辨, 还通过影响能量不确定度对角分辨间接贡献; 位置分辨主要来源于探测器的结构尺寸, 当探测器尺寸小于5 cm, 影响角分辨的主要来源是能量不确定度. 利用所获得的理论结果指导设计了原理探测系统, 并对设计的原理系统开展了初步实验研究. 结果表明, 分析结果与实验得到的角分辨参数基本一致.     

Uncertainty Relations for Coherence

Quantum mechanical uncertainty relations are fundamental consequences of the incompatible nature of noncommuting observables. In terms of the coherence measure based on the Wigner-Yanase skew information, we establish several uncertainty relations for coherence with respect to von Neumann measurements, mutually unbiased bases(MUBs), and general symmetric informationally complete positive operator valued measurements(SIC-POVMs),respectively. Since coherence is intimately connected with quantum uncertainties, the obtained uncertainty relations are of intrinsically quantum nature, in contrast to the conventional uncertainty relations expressed in terms of variance,which are of hybrid nature(mixing both classical and quantum uncertainties). From a dual viewpoint, we also derive some uncertainty relations for coherence of quantum states with respect to a fixed measurement. In particular, it is shown that if the density operators representing the quantum states do not commute, then there is no measurement(reference basis) such that the coherence of these states can be simultaneously small.     

A novel robust proportional-integral （PI） adaptive observer design for chaos synchronization

In this paper, chaos synchronization in the presence of parameter uncertainty, observer gain perturbation and exogenous input disturbance is considered. A nonlinear non-fragile proportional-integral (PI) adaptive observer is designed for the synchronization of chaotic systems; its stability conditions based on the Lyapunov technique are derived. The observer proportional and integral gains, by converting the conditions into linear matrix inequality (LMI), are optimally selected from solutions that satisfy the observer stability conditions such that the effect of disturbance on the synchronization error becomes minimized. To show the effectiveness of the proposed method, simulation results for the synchronization of a Lorenz chaotic system with unknown parameters in the presence of an exogenous input disturbance and abrupt gain perturbation are reported.     

The role of sensitivity and uncertainty analysis in combustion modelling

Models play an important role in improving our understanding of combustion processes and more and more are able to assist in the design of advanced energy conversion devices. Due to constant improvements in computing power and techniques such as automatic kinetic mechanism generation, we have the ability to represent combustion processes with increasing levels of detail. This is particularly true for kinetic processes where complex mechanisms are being developed which describe the oxidation of both conventional and alternative fuels. These mechanisms may comprise of up to hundreds of species and thousands of reactions with thermo-kinetic data derived from a wide variety of sources including direct measurements, global combustion experiments, and theoretical calculations. However, significant uncertainties in the data used to parametrise combustion models still exist. These input uncertainties propagate through models of combustion devices leading to uncertainties in the prediction of key combustion properties. In order to improve confidence in these models to the extent where they can successfully be used in design, input uncertainties need to be reduced as far as possible. This requires focussing efforts on those parameters which drive predictive uncertainty, which may be identified through sensitivity analysis. The paper will describe the methodologies available for the sensitivity and uncertainty analysis of combustion models with examples focussed on chemical kinetics. It will then discuss how such techniques can be incorporated into strategies for model improvement and will try to provide some future perspectives on how we can proceed in this direction as a research community.     

基于延伸期可预报性的集合预报方法和数值试验

集合预报是考虑初始条件和模式不确定性的有效途径. 结合延伸期可预报性特征,对具有不同特性的可预报分量和随机分量采用不同的集合预报方案和策略,发展了一种基于延伸期可预报性的集合预报新方法(PBEP).该方法以延伸期数值预报模式为平台,对可预报分量采用多个模式误差订正方案,从考虑模式不确定性的角度进行集合;而对随机分量则利用历史资料从气候概率的角度给出集合概率分布,避免模式误差对随机分量概率分布的影响.试验结果表明,相比于国家气候中心的业务动力延伸集合预报系统,该集合预报方法对全球各区域环流预报技巧均有提高,对不同空间尺度的波也有不同程度的改进,显示出潜在的业务应用前景.     

Underwater source detection using a spatial stationarity test

The problem of detecting a source in shallow water is addressed. The complexity of such a propagation channel makes precise modeling practically impossible. This lack of accuracy causes a deterioration in the performance of the optimal detector and motivates the search for suboptimal detectors which are insensitive to uncertainties in the propagation model. A novel, robust detector which measures the degree of spatial stationarity of a received field is presented. It exploits the fact that a signal propagating in a bounded channel induces spatial nonstationarity to a higher degree than mere background noise. The performance of the proposed detector is evaluated using both simulated data and experimental data collected in the Mediterranean Sea. This performance is compared to those of three other detectors, employing different extents of prior information. It is shown that when the propagation channel is not completely known, as is the case of the experimental data, the novel detector outperforms the others in terms of threshold signal-to-noise ratio (SNR). In the presence of environmental mismatch, the threshold SNR of the novel detector for the experimental data appears 2-5 dB lower than the other detectors. That is, this detector couples good performance with robustness to propagation uncertainties.     

Bayesian analysis of syngas chemistry models

Syngas chemistry modelling is an integral step toward the development of safe and efficient syngas combustors. Although substantial effort has been undertaken to improve the modelling of syngas combustion, models nevertheless fail in regimes important to gas turbine combustors, such as low temperature and high pressure. In order to investigate the capabilities of syngas models, a Bayesian framework for the quantification of uncertainties has been used. This framework, given a set of experimental data, allows for the calibration of model parameters, determination of uncertainty in those parameters, propagation of that uncertainty into simulations, as well as determination of model evidence from a set of candidate syngas models. Here, three syngas combustion models have been calibrated using laminar flame speed measurements from high pressure experiments. After calibration the resulting uncertainty in the parameters is propagated forward into the simulation of laminar flame speeds. The model evidence is then used to compare candidate models for the given set of experimental conditions and results. Additionally, the technique MUM-PCE, an interesting uncertainty minimisation method for kinetics models, has been compared to the Bayesian method for this application to the prediction of syngas laminar flame speeds. This comparison shows the importance of model form error and experimental error representations in the uncertainty quantification context, for these choices significantly affect uncertainty quantification results.     

角点检测不确定度评定方法

 提出一种评定角点检测不确定度的新方法。建立了一个像素强度不确定度数学模型,该数学模型在像素强度不确定度与像素强度和图像梯度之间建立了联系。给出了实现角点检测不确定度评定的具体方法：首先利用像素强度不确定度数学模型估计每个参与角点检测的像素的强度不确定度,然后再用蒙特卡罗方法估计出角点检测的不确定度。以经典SUSAN角点检测算子为例,对文中提出的角点检测不确定度评定方法进行了验证。实验结果表明,使用该方法能准确地估计出角点检测结果的不确定度。     

Predicting Box-Office Markets with Machine Learning Methods

The accurate prediction of gross box-office markets is of great benefit for investment and management in the movie industry. In this work, we propose a machine learning-based method for predicting the movie box-office revenue of a country based on the empirical comparisons of eight methods with diverse combinations of economic factors. Specifically, we achieved a prediction performance of the relative root mean squared error of 0.056 in the US and of 0.183 in China for the two case studies of movie markets in time-series forecasting experiments from 2013 to 2016. We concluded that the support-vector-machine-based method using gross domestic product reached the best prediction performance and satisfies the easily available information of economic factors. The computational experiments and comparison studies provided evidence for the effectiveness and advantages of our proposed prediction strategy. In the validation process of the predicted total box-office markets in 2017, the error rates were 0.044 in the US and 0.066 in China. In the consecutive predictions of nationwide box-office markets in 2018 and 2019, the mean relative absolute percentage errors achieved were 0.041 and 0.035 in the US and China, respectively. The precise predictions, both in the training and validation data, demonstrate the efficiency and versatility of our proposed method.     

Analysis of uncertainties in instantaneous soot volume fraction measurements using two-dimensional, auto-compensating, laser-induced incandescence (2D-AC-LII)

Laser-induced incandescence (LII) is an optical measurement technique capable of measuring soot volume fraction over a wide range of conditions. However, development of two-dimensional auto-compensating LII (2D-AC-LII) in the literature has been limited and until now, instantaneous measurements have not been demonstrated. In this paper, we successfully demonstrate instantaneous 2D-AC-LII soot volume fraction (SVF) measurements in an ethylene-air co-annular diffusion flame. Results were then used to support a detailed uncertainty analysis based on a Monte-Carlo simulation. Agreement between both the instantaneous and average SVF measurements with published data from attenuation measurements under identical conditions was found to be good. Uncertainties are discussed both in terms of an overall accuracy of the SVF measurement, which is strongly dominated by uncertainty in the optical properties of soot, and the comparative uncertainties with optical properties fixed. The uncertainty in an instantaneous 2D determination of SVF for a comparative measurement is dominated by photon shot noise, and in regions of high soot volume fraction it is below 25% (95% confidence interval). Shot noise uncertainty could be further reduced with additional pixel averaging at the expense of spatial resolution. This diagnostic shows significant promise for quantitative planar soot concentration measurements within turbulent flames.     

Calculation of transport coefficient profiles in modulation experiments as an inverse problem

The calculation of transport profiles from experimental measurements belongs in the category of inverse problems which are known to come with issues of ill-conditioning or singularity. A reformulation of the calculation, the matricial approach, is proposed for periodically modulated experiments, within the context of the standard advection-diffusion model where these issues are related to the vanishing of the determinant of a 2×2 matrix. This sheds light on the accuracy of calculations with transport codes, and provides a path for a more precise assessment of the profiles and of the related uncertainty.     

洛伦兹-哈肯激光混沌系统有限时间稳定主动控制方法研究

研究了洛伦兹-哈肯激光混沌系统基于主动控制方法的有限时间稳定问题. 在研究Terminal 吸引子的基础上, 考虑系统不确定性, 提出一种基于Terminal 吸引子且具有动态主动补偿特性的主动控制方法, 使受控洛伦兹-哈肯激光混沌系统近似实现有限时间稳定.同时, 为解决系统不确定性问题, 设计了一种新的观测器, 并使这种观测器能在很短时间内跟踪系统的不确定性.通过引入奇异扰动性理论, 详细地分析了闭环系统近似有限时间稳定性.仿真实验结果验证了该主动控制方法及观测器的有效性.