校准条件下的数值模拟不确定度量化方法

当存在众多不确定输入因素时,不确定度的传递分析往往导致对数值模拟不确定度的过高估计.利用校准行为能够消减系统级数值模拟中认知不确定度的客观机制,提出一个综合利用已有系统级试验对比信息和新增建模与模拟传递信息的不确定度量化方法,结合一个虚拟试验的例子对该方法进行展示和验证.     

基于数值模拟的QMU决策体系

裕度及不确定度量化方法（Quantification of Margin and Uncertainty,QMU）能够基于裕度及其不确定度信息对系统是否达到其指标要求进行科学的判断与决策.借助新的数值模拟不确定度量化方法,建立基于数值模拟预测及其不确定度的QMU决策技术体系.结合库存产品可靠性评估的实例,展示该体系的主要思想及其实现过程.     

爆轰流体力学模型敏感度分析与模型确认

验证、确认与不确定度量化(VVUQ)是评估物理模型可信度和量化复杂工程数值模拟结果置信度的系统方法.验证是要回答数值模拟程序是否正确求解了物理模型和程序是否正确实施或给出求解模型的误差、不确定性大小及使用范围,确认是要通过数值结果回答物理模型是否反映了真实客观世界或反映真实客观世界的可信程度.文章围绕爆轰流体力学模型,剖析了模型中不确定性因素,给出了影响模拟结果不确定性的关键因素清单,并对其开展了敏感度分析,确认了模型的适应性.     

可靠性数值模拟的不确定度量化

根据可靠性认证对不确定度量化的技术要求,结合复杂工程系统的层级结构和数值模拟从校准、验证与确认到最终具有预测能力的历程,对可靠性数值模拟不确定度量化的要求和方法进行探索,并结合爆轰算例对这些方法进行演示和验证.     

抽样法与灵敏度法k_(eff)不确定度量化

核反应堆的中子学模拟计算中,核数据的不确定度导致的积分量计算结果的不确定度,通常采用基于微扰理论的灵敏度与不确定度分析方法 (简称灵敏度法)量化.灵敏度分析法原则上只适用于线性模型,且一般输运计算程序难以直接进行灵敏度分析.而抽样法直接抽样核数据输入中子学计算程序进行计算,通过对计算结果的统计分析评估计算量的不确定度.抽样法易于实现、计算精确、且适用性强.在灵敏度分析与不确定度量化程序SURE中,增加了抽样法不确定度的量化功能.为将抽样法不确定度量化应用于复杂问题的模拟计算,需对其进行细致的考核.为此,选取简单的临界基准实验模型,分别采用灵敏度分析法和抽样法进行不确定度量化,得到了各核素各反应道核数据导致的k_(eff)计算不确定度.对比显示,两种方法的不确定度计算结果有很好的符合,验证了SURE程序抽样法功能的正确性.抽样法计算的k_(eff)符合正态分布,说明在一般核数据的不确定度范围内,k_(eff)与核数据近似成线性关系,利用灵敏度分析法评估k_(eff)计算值的不确定度是适用的.     

辐射不透明度计算中含温有界原子结构理论的不确定度量化

以交换势的泛函表达式为核心,分析产生原子结构理论不确定度的主要原因,阐述辐射不透明度计算中含温有界原子结构理论不确定度量化的具体步骤,给出能级、矩阵元的不确定度量化计算公式,以及判定理论模型优劣的判据.以汞、金、铁元素为例,通过数值计算,根据对比分析,验证该不确定度量化方法的可行性.     

测量不确定度的评定与表示

测量不确定度和如何正确评定与表示，是个极其重要的问题，文章指出了研究不确定度的意义，介绍了不确定度的有关概念，按实际工作的测量模型，给出了标准不确定度Ａ类、Ｂ类评定的各种具体方法，提出了标准不确定度的俣成方法与展伸不确定度的给出方法，对不确定度评定与表示的程序进行了汇总，并举出了应用实例。     

荧光增白剂CXT紫外吸收测量不确定度的评估

对荧光增白剂CXT紫外吸收测量不确定度进行了评估,分析了整个检测过程中不确定度的来源,测量结果的不确定度由重复性测量、仪器的校准及仪器显示读数的分辨力等所引入的不确定度分量组成.评估结果表明,重复性测量是影响该方法不确定度的主要因素.     

ICP-MS测定三七中铬、砷、汞、镉和铅的测量不确定度的评估

合理评估ICP-MS测定三七中铬、砷、汞、镉、铅的测量不确定度,对测试方法的每一步骤进行不确定度的分析评估.     

激光量热计不确定度分析

 基于激光量热平台,对ISO 11551涉及的3种弱吸收数据处理方法——指数法、脉冲法和梯度法进行了不确定度分析。从回归分析的角度对拟合参数γ和A等进行了不确定度评估,采用Matlab软件进行不确定度的计算。采用B类评定法对质量、功率等测量参数进行不确定度评估。随机选取样本进行多次测量,验证了本文不确定度评估的有效性。分析和实验表明,拟合偏差是弱吸收测量不确定度的主要来源。指数法的相对不确定度约为0.0129,脉冲法的相对不确定度约为0.0029,是最优的数据处理方法,梯度法采用的样本点过于单一,相对不确定度约为0.0961。提高量热计精度的可行途径是改进数据处理方法和提高激光功率测量精度。     

Numerical studies on autoignition and detonation development from a hot spot in hydrogen/air mixtures

Detonation development inside spark ignition engines can result in the so called super-knock with extremely high pressure oscillation above 200?atm. In this study, numerical simulations of autoignitive reaction front propagation in hydrogen/air mixtures are conducted and the detonation development regime is investigated. A hot spot with linear temperature distribution is used to induce autoignitive reaction front propagation. With the change of temperature gradient or hot spot size, three typical autoignition reaction front modes are identified: supersonic reaction front; detonation development and subsonic reaction front. The effects of initial pressure, initial temperature, fuel type and equivalence ratio on detonation development regime are examined. It is found that the detonation development regime strongly depends on mixture composition (fuel and equivalence ratio) and thermal conditions (initial pressure and temperature). Therefore, to achieve the quantitative prediction of super-knock in engines, we need use the detonation development regime for specific fuel at specific initial temperature, initial pressure, and equivalence ratio.     

Health risk assessment for nanoparticles: A case for using expert judgment

Uncertainties in conventional quantitative risk assessment typically relate to values of parameters in risk models. For many environmental contaminants, there is a lack of sufficient information about multiple components of the risk assessment framework. In such cases, the use of default assumptions and extrapolations to fill in the data gaps is a common practice. Nanoparticle risks, however, pose a new form of risk assessment challenge. Besides a lack of data, there is deep scientific uncertainty regarding every aspect of the risk assessment framework: (a) particle characteristics that may affect toxicity; (b) their fate and transport through the environment; (c) the routes of exposure and the metrics by which exposure ought to be measured; (d) the mechanisms of translocation to different parts of the body; and (e) the mechanisms of toxicity and disease. In each of these areas, there are multiple and competing models and hypotheses. These are not merely parametric uncertainties but uncertainties about the choice of the causal mechanisms themselves and the proper model variables to be used, i.e., structural uncertainties. While these uncertainties exist for PM2.5 as well, risk assessment for PM2.5 has avoided dealing with these issues because of a plethora of epidemiological studies. However, such studies don’t exist for the case of nanoparticles. Even if such studies are done in the future, they will be very specific to a particular type of engineered nanoparticle and not generalizable to other nanoparticles. Therefore, risk assessment for nanoparticles will have to deal with the various uncertainties that were avoided in the case of PM2.5. Consequently, uncertainties in estimating risks due to nanoparticle exposures may be characterized as ‘extreme’. This paper proposes a methodology by which risk analysts can cope with such extreme uncertainty. One way to make these problems analytically tractable is to use expert judgment approaches to study the degree of consensus and/or disagreement between experts on different parts of the exposure–response paradigm. This can be done by eliciting judgments from a wide range of experts on different parts of the risk causal chain. We also use examples to illustrate how studying expert consensus/disagreement helps in research prioritization and budget allocation exercises. The expert elicitation can be repeated over the course of several years, over which time, the state of scientific knowledge will also improve and uncertainties may possibly reduce. Results from expert the elicitation exercise can be used by risk managers or managers of funding agencies as a tool for research prioritization.     

Generalized Uncertainty Principle in a Simple Varying Speed of Light Model

In this paperwewill derive a generalized uncertainty principle (GUP) in a simple varying speed of light (VSL) model. First we will show that VSL is an immediate consequence of GUP. Then, within the framework of a simple VSL model, we will show that GUP can be expressed as a function of cosmological scale factor. This expression gives two main results: uncertainties in position and momentum are actually cosmological models dependent and these uncertainties depend on mass and momentum of the particle under consideration. The relationship between matter content of the Universe and the values of uncertainties in early stages of the evolution of the Universe will be discussed in a mini-superspace approach.     

Effects of different product phases in aluminum dust detonation modeling

Modeling aluminum (Al) dust detonation is difficult due to uncertainties in the product species and fractions. Recent experiments indicate both gaseous and solid alumina may appear in the detonation product, but only the gaseous one was considered before. To resolve this drawback, we study the effects of different product phases on the detonation parameters with the hybrid combustion model proposed recently. Numerical results demonstrate that the assumption of gaseous product induces high velocity and pressure, while the assumption of solid product induces low velocity and pressure. To clarify how close-to-experiment results have been obtained with one phase assumption, we revisit previous studies and analyze the models. The inconsistency between the product phase and heat release is found, and then one model with variable heat release dependent on the product phase is proposed. Then simulations with both the gaseous and solid products are carried out, and results reveal the necessity of establishing a relationship between the heat release and reaction products.     

An experimental investigation of the propagation mechanism of critical deflagration waves that lead to the onset of detonation

The reflection of a CJ detonation from a perforated plate is used to generate high speed deflagrations downstream in order to investigate the critical conditions that lead to the onset of detonation. Different perforated plates were used to control the turbulence in the downstream deflagration waves. Streak Schlieren photography, ionization probes and pressure transducers are used to monitor the flow field and the transition to detonation. Stoichiometric mixtures of acetylene–oxygen and propane–oxygen were tested at low initial pressures. In some cases, acetylene–oxygen was diluted with 80% argon in order to render the mixture more “stable” (i.e., more regular detonation cell structure). The results show that prior to successful detonation initiation, a deflagration is formed that propagates at about half the CJ detonation velocity of the mixture. This “critical” deflagration (which propagates at a relatively constant velocity for a certain duration prior to the onset of detonation) is comprised of a leading shock wave followed by an extended turbulent reaction zone. The critical deflagration speed is not dependent on the turbulence characteristics of the perforated plate but rather on the energetics of the mixture like a CJ detonation (i.e., the deflagration front is driven by the expansion of the combustion products). Hence, the critical deflagration is identified as a CJ deflagration. The high intensity turbulence that is required to sustain its propagation is maintained via chemical instabilities in the reaction zone due to the coupling of pressure fluctuations with the energy release. Therefore, in “unstable” mixtures, critical deflagrations can be supported for long durations, whereas in “stable” mixtures, deflagrations decay as the initial plate generated turbulence decays. The eventual onset of detonation is postulated to be a result of the amplification of pressure waves (i.e., turbulence) that leads to the formation of local explosion centers via the SWACER mechanism during the pre-detonation period.     

Influence of the initial pressure of polydisperse bubble media on characteristics of detonation waves

The influence of the initial pressure of polydisperse bubble media on the initiation conditions, structure, propagation velocity, and the pressure of detonation waves has been experimentally studied. It has been established that variations in the initial pressure of the bubble medium is an effective method of controlling the parameters of bubble detonation waves.     

Probability density functions of quantum mechanical observable uncertainties

We study the uncertainties of quantum mechanical observables, quantified by the standard deviation (square root of variance) in Haar-distributed random pure states. We derive analytically the probability density functions (PDFs) of the uncertainties of arbitrary qubit observables. Based on these PDFs, the uncertainty regions of the observables are characterized by the support of the PDFs. The state-independent uncertainty relations are then transformed into the optimization problems over uncertainty regions, which opens a new vista for studying state-independent uncertainty relations. Our results may be generalized to multiple observable cases in higher dimensional spaces.     

Uncertainty propagation of chemical kinetics parameters and binary diffusion coefficients in predicting extinction limits of hydrogen/oxygen/nitrogen non-premixed flames

A comprehensive investigation of the uncertainties associated with the experimental and numerical evaluation of the extinction strain rate in hydrogen/oxygen/nitrogen non-premixed flames is presented in this work. The reported new experimental uncertainties of the extinction strain rate include several sources of uncertainties that typically affect the characterisation of velocity and boundary conditions of counterflow flames via particle image velocimetry. The uncertainties associated with the numerical determination of the extinction strain rate not only depend upon the selected chemical kinetics parameters but also on the binary diffusion coefficients. In order to identify the major sources of uncertainties in the chemical and diffusion models, a Monte Carlo based high-dimensional model representation analysis of the extinction curve was performed. Independent and simultaneous perturbations of relevant chemical kinetics and diffusion parameters have shown that the uncertainties associated with the binary diffusion coefficients are about a factor of 10 smaller than the uncertainty due to chemical kinetics parameters. Since the experimentally well known binary diffusion coefficient for hydrogen and nitrogen, , accounts for most of the propagated uncertainty of the diffusion model, it is shown here that only a reduction of the uncertainty of chemical kinetics parameters will have a significant impact in improving the accuracy of the extinction strain rate predictions.