Adjoint-based Sensitivity Analysis of a Mesoscale Low on the Mei-yu Front and Its Implications for Adaptive Observation

An adjoint sensitivity analysis of one mesoscale low on the mei-yu Front is presented in this paper. The sensitivity gradient of simulation error dry energy with respect to initial analysis is calculated. And after verifying the ability of a tangent linear and adjoint model to describe small perturbations in the nonlinear model, the sensitivity gradient analysis is implemented in detail. The sensitivity gradient with respect to different physical fields are not uniform in intensity, simulation error is most sensitive to the vapor mixed ratio. The localization and consistency are obvious characters of horizontal distribution of the sensitivity gradient, which is useful for the practical implementation of adaptive observation. The sensitivity region tilts to the northwest with height increasing; the singular vector calculation proves that this tilting characterizes a quick-growing structure, which denotes that using the leading singular vectors to decide the adaptive observation region is proper. When connected with simulation of a mesoscale low on the mei-yu Front, the sensitivity gradient has the following physical characters： the obvious sensitive region is mesoscale, concentrated in the middle-upper troposphere, and locates around the key system; and the sensitivity gradient of different physical fields correlates dynamically.

Second-Order Adjoint Sensitivity Analysis Methodology for Computing Exactly Response Sensitivities to Uncertain Parameters and Boundaries of Linear Systems: Mathematical Framework

This work presents the “Second-Order Comprehensive Adjoint Sensitivity Analysis Methodology (2nd-CASAM)” for the efficient and exact computation of 1st- and 2nd-order response sensitivities to uncertain parameters and domain boundaries of linear systems. The model’s response (i.e., model result of interest) is a generic nonlinear function of the model’s forward and adjoint state functions, and also depends on the imprecisely known boundaries and model parameters. In the practically important particular case when the response is a scalar-valued functional of the forward and adjoint state functions characterizing a model comprising N parameters, the 2nd-CASAM requires a single large-scale computation using the First-Level Adjoint Sensitivity System (1st-LASS) for obtaining all of the first-order response sensitivities, and at most N large-scale computations using the Second-Level Adjoint Sensitivity System (2nd-LASS) for obtaining exactly all of the second-order response sensitivities. In contradistinction, forward other methods would require (N2/2 + 3 N/2) large-scale computations for obtaining all of the first- and second-order sensitivities. This work also shows that constructing and solving the 2nd-LASS requires very little additional effort beyond the construction of the 1st-LASS needed for computing the first-order sensitivities. Solving the equations underlying the 1st-LASS and 2nd-LASS requires the same computational solvers as needed for solving (i.e., “inverting”) either the forward or the adjoint linear operators underlying the initial model. Therefore, the same computer software and “solvers” used for solving the original system of equations can also be used for solving the 1st-LASS and the 2nd-LASS. Since neither the 1st-LASS nor the 2nd-LASS involves any differentials of the operators underlying the original system, the 1st-LASS is designated as a “first-level” (as opposed to a “first-order”) adjoint sensitivity system, while the 2nd-LASS is designated as a “second-level” (rather than a “second-order”) adjoint sensitivity system. Mixed second-order response sensitivities involving boundary parameters may arise from all source terms of the 2nd-LASS that involve the imprecisely known boundary parameters. Notably, the 2nd-LASS encompasses an automatic, inherent, and independent “solution verification” mechanism of the correctness and accuracy of the 2nd-level adjoint functions needed for the efficient and exact computation of the second-order sensitivities.

Third Order Adjoint Sensitivity and Uncertainty Analysis of an OECD/NEA Reactor Physics Benchmark: II. Computed Sensitivities

This work presents the results of the exact computation of (180)3 = 5,832,000 third-order mixed sensitivities of the leakage response of a polyethylene-reflected plutonium (PERP) experimental benchmark with respect to the benchmark’s 180 microscopic total cross sections. This computation was made possible by applying the Third-Order Adjoint Sensitivity Analysis Methodology developed by Cacuci. The numerical results obtained in this work revealed that many of the 3rd-order sensitivities are significantly larger than their corresponding 1st- and 2nd-order ones, which is contrary to the widely held belief that higher-order sensitivities are all much smaller and hence less important than the first-order ones, for reactor physics systems. In particular, the largest 3rd-order relative sensitivity is the mixed sensitivity of the PERP leakage response with respect to the lowest energy-group (30) total cross sections of 1H (“isotope 6”) and 239Pu (“isotope 1”). These two isotopes are shown in this work to be the two most important parameters affecting the PERP benchmark’s leakage response. By comparison, the largest 1st-order sensitivity is that of the PERP leakage response with respect to the lowest energy-group total cross section of isotope 1H, having the value , while the largest 2nd-order sensitivity is . The 3rd-order sensitivity analysis presented in this work is the first ever such analysis in the field of reactor physics. The consequences of the results presented in this work on the uncertainty analysis of the PERP benchmark’s leakage response will be presented in a subsequent work.

Third-Order Adjoint Sensitivity Analysis of an OECD/NEA Reactor Physics Benchmark: I. Mathematical Framework

This work extends to third-order previously published work on developing the adjoint sensitivity and uncertainty analysis of the numerical model of a polyethylene-reflected plutonium (acronym: PERP) OECD/NEA reactor physics benchmark. The PERP benchmark comprises 21,976 imprecisely known (uncertain) model parameters. Previous works have used the adjoint sensitivity analysis methodology to compute exactly and efficiently all of the 21,976 first-order and (21,976)2 second-order sensitivities of the PERP benchmark’s leakage response to all of the benchmark’s uncertain parameters, showing that the largest and most consequential 1st- and 2nd-order response sensitivities are with respect to the total microscopic cross sections. These results have motivated extending the previous adjoint-based derivations to third-order, leading to the derivation, in this work, of the exact mathematical expressions of the (180)3 third-order sensitivities of the PERP leakage response with respect to these total microscopic cross sections. The formulas derived in this work are valid not only for the PERP benchmark but can also be used for computing the 3rd-order sensitivities of the leakage response of any nuclear system involving fissionable material and internal or external neutron sources. Subsequent works will use the adjoint-based mathematical expressions obtained in this work to compute exactly and efficiently the numerical values of these (180)3 third-order sensitivities (which turned out to be very large and consequential) and use them for a third-order uncertainty analysis of the PERP benchmark’s leakage response.

Fourth-Order Adjoint Sensitivity Analysis of an OECD/NEA Reactor Physics Benchmark: II. Mathematical Expressions and CPU-Time Comparisons for Computing 4^th-Order Sensitivities

This work extends to fourth-order previously published work on developing the adjoint sensitivity and uncertainty analysis of the numerical model of a polyethylene-reflected plutonium (acronym: PERP) OECD/NEA reactor physics benchmark. Previous works showed that the third-order sensitivities of the PERP leakage response with respect to these total microscopic cross sections are far larger than the corresponding 1st-order and 2nd-order ones, thereby having the largest impact on the uncertainties induced in the PERP benchmark’s response. This finding has motivated the development of the original 4th-order formulas presented in this work, which are valid not only for the PERP benchmark but can also be used for computing the 4th-order sensitivities of response of any nuclear system involving fissionable material and internal or external neutron sources. Subsequent works will use the adjoint-based mathematical expressions obtained in this work to compute exactly and efficiently the numerical values of the largest fourth-order sensitivities of the PERP benchmark’s response to the total microscopic cross sections, and use them for a pioneering fourth-order uncertainty analysis of the PERP benchmark’s response.

Illustrative Application of the 2^nd-Order Adjoint Sensitivity Analysis Methodology to a Paradigm Linear Evolution/Transmission Model: Point-Detector Response

This work illustrates the application of the “Second Order Comprehensive Adjoint Sensitivity Analysis Methodology” (2nd-CASAM) to a mathematical model that can simulate the evolution and/or transmission of particles in a heterogeneous medium. The model response is the value of the model’s state function (particle concentration or particle flux) at a point in phase-space, which would simulate a pointwise measurement of the respective state function. This paradigm model admits exact closed-form expressions for all of the 1st- and 2nd-order response sensitivities to the model’s uncertain parameters and domain boundaries. These closed-form expressions can be used to verify the numerical results of production and/or commercial software, e.g., particle transport codes. Furthermore, this paradigm model comprises many uncertain parameters which have relative sensitivities of identical magnitudes. Therefore, this paradigm model could serve as a stringent benchmark for inter-comparing the performances of all deterministic and statistical sensitivity analysis methods, including the 2nd-CASAM.

Illustrative Application of the 2^nd-Order Adjoint Sensitivity Analysis Methodology to a Paradigm Linear Evolution/Transmission Model: Reaction-Rate Detector Response

This work continues the illustrative application of the “Second Order Comprehensive Adjoint Sensitivity Analysis Methodology” (2nd-CASAM) to a benchmark mathematical model that can simulate the evolution and/or transmission of particles in a heterogeneous medium. The model response considered in this work is a reaction-rate detector response, which provides the average interactions of particles with the respective detector or, alternatively, the time-average of the concentration of a mixture of substances in a medium. The definition of this model response includes both uncertain boundary points of the benchmark, thereby providing both direct and indirect contributions to the response sensitivities stemming from the boundaries. The exact expressions for the 1st- and 2nd-order response sensitivities to the boundary and model parameters obtained in this work can serve as stringent benchmarks for inter-comparing the performances of all (deterministic and statistical) sensitivity analysis methods.

The First-Order Comprehensive Sensitivity Analysis Methodology (1st-CASAM) for Scalar-Valued Responses: I. Theory

This work presents the first-order comprehensive adjoint sensitivity analysis methodology (1st-CASAM) for computing efficiently, exactly, and exhaustively, the first-order sensitivities of scalar-valued responses (results of interest) of coupled nonlinear physical systems characterized by imprecisely known model parameters, boundaries and interfaces between the coupled systems. The 1st-CASAM highlights the conclusion that response sensitivities to the imprecisely known domain boundaries and interfaces can arise both from the definition of the system’s response as well as from the equations, interfaces and boundary conditions defining the model and its imprecisely known domain. By enabling, in premiere, the exact computations of sensitivities to interface and boundary parameters and conditions, the 1st-CASAM enables the quantification of the effects of manufacturing tolerances on the responses of physical and engineering systems. Ongoing research will generalize the methodology presented in this work, aiming at computing exactly and efficiently higher-order response sensitivities for coupled systems involving imprecisely known interfaces, parameters, and boundaries.

The First-Order Comprehensive Sensitivity Analysis Methodology (1^st-CASAM) for Scalar-Valued Responses: II. Illustrative Application to a Heat Transport Benchmark Model

This work illustrates the application of the 1st-CASAM to a paradigm heat transport model which admits exact closed-form solutions. The closed-form expressions obtained in this work for the sensitivities of the temperature distributions within the model to the model’s parameters, internal interfaces and external boundaries can be used to benchmark commercial and production software packages for simulating heat transport. The 1st-CASAM highlights the novel finding that response sensitivities to the imprecisely known domain boundaries and interfaces can arise both from the definition of the system’s response as well as from the equations, interfaces and boundary conditions that characterize the model and its imprecisely known domain. By enabling, in premiere, the exact computations of sensitivities to interface and boundary parameters and conditions, the 1st-CASAM enables the quantification of the effects of manufacturing tolerances on the responses of physical and engineering systems.

Stress sensitivity analysis for a wide-chord fan blade using an adjoint method

High-performance compressor design is best achieved with a good trade-off between aerodynamic and structural considerations,which requires efficient and accurate multidisciplinary design and optimization tools.As advanced compressors are defined with a large design space,their optimization is most efficiently achieved using a gradient-based approach,where the gradient can be computed using an adjoint method,at a cost nearly independent of the dimension of the design space.While the adjoint method has been widely used for aerodynamic shape optimization,its use for structural shape optimizations of compressor blades has not been as well studied.This paper discussed a discrete adjoint solver for structural sensitivity analysis developed within the opensource Computational Structural Mechanics(CSM)software CalculiX,and proposed an efficient stress sensitivity analysis method based on the Finite Element Method(FEM)using adjoint.The proposed method is applied to compute the stress sensitivity of a wide-chord fan blade in a highbypass-ratio engine.The accuracy of the adjoint-based stress sensitivity is verified against central finite differences.In terms of computational efficiency,the adjoint approach is about 4.5 times more efficient than the conventional approach using finite differences.This works marks an important step towards fluid-structural coupled adjoint optimization of wide-chord fan blades.

Mesoscale Moist Adjoint Sensitivity Study of a Mei-yu Heavy Rainfall Event

The mesoscale moist adjoint sensitivities related to the initiation of mesoscale convective systems （MCSs） are evaluated for a mei-yu heavy rainfall event. The sensitivities were calculated on a realistic background gained from a four-dimensional variational data assimilation of precipitation experiment to make the sensitivity computation possible and reasonable within a strong moist convective event at the mesoscale. The results show that the computed sensitivities at the mesoscale were capable of capturing the factors affecting MCS initiation. The sensitivities to the initial temperature and moisture are enhanced greatly by diabatic processes, especially at lower levels, and these sensitivities are much larger than those stemming from the horizontal winds, which implies that initiation of MCSs is more sensitive to low-level temperature and moisture perturbations rather than the horizontal winds. Moreover, concentration of sensitivities at low levels reflects the characteristics of the mei-yu front. The results provide some hints about how to improve quantitative precipitation forecasts of mei-yu heavy rainfall, such as by conducting mesoscale targetted observations via the adjoint-based method to reduce the low-level errors in the initial temperature and moisture.

Adjoint Sensitivity Analyses on the Anomalous Circulation Features in East Asian Summer Monsoon

The concept of optimal sensitivity perturbation (OSP) is developed based on adjoint sensitivity analysis theory. The persistent anomalous features in East Asian summer monsoon system, including the Ural blocking, the Okhotsk Sea dipole blocking and the variations of subtropical high are analyzed and the OSP for each of them evaluated. The results provide us with some new insight into the most significant influential factors for these features. It also demonstrates the great potential for further applications of this method in diagnostics of atmospheric processes.

An Early-Stop Adjoint Transient Sensitivity Analysis Method for Objective Functions Associated with Many Time Points

Transient sensitivity analysis aims to obtain the gradients of objective functions(circuit performance)with respect to design or variation parameters in a simulator,which can be widely used in yield analysis and circuit optimization,among others.However,the traditional method has a computational complexity of O(N^(2))for objective functions containing circuit states at N time points.The computational complexity is too expensive for large N,especially in time-frequency transform.This paper proposes a many-time-point sensitivity method to reduce the computational complexity to O(N)in multiparameter many-time-point cases.The paper demonstrates a derivation process that improves efficiency by weighting the transfer chain and multiplexing the backpropagation process.We also proposed an early-stop method to improve efficiency further under the premise of ensuring accuracy.The algorithm enables sensitivity calculation of performances involving thousands of time points,such as signal-to-noise and distortion ratio and total harmonic distortion,with significant speed improvements.

大气化学传输模式CAMx的伴随模式:构建及应用

在大气化学传输模式CAMx的基础上,用人工编写代码的方法,构建其伴随模式,并通过数值试验,对伴随模式程序进行了检验。应用CAMx及其伴随模式,针对珠江三角洲地区空气污染进行数值模拟和敏感性分析,计算了地面二氧化硫和臭氧关于污染物排放源的敏感性,并用数值方法探讨了线性敏感系数的适用范围,可为深入研究该地区污染机理和控制策略提供重要依据。用伴随模式可以高效率地计算目标函数关于多个输入变量的敏感性,显著地扩展了原模式的功能,为大气环境优化控制和大气化学数据同化等科学问题提供了有力的研究工具。

微型柔性机构的多目标计算机辅助拓扑优化设计

提出了基于结构整体柔度最小化和结构输出位移最大化的多目标拓扑优化设计方法,建立了微型柔性机构的多目标拓扑优化设计模型·提出了适用于微型柔性机构多目标拓扑优化设计的伴随矩阵敏度分析方法,并将广义收敛移动渐进算法用于多目标多约束微型柔性机构拓扑优化问题的求解·最后通过数值计算验证了优化模型的有效性·

伴随同化技术在渤、黄海生态模式中的应用：控制变量的选取与孪生实验

在渤、黄海海域建立了物理海洋模型与NPZD生态模型的耦合模型，就伴随同化技术应用中如何从众多模型参数中选择控制变量的难题做了深入研究。研究发现，对于渤、黄海海区的NPZD模型，除了用传统的方法选取控制变量之外，代价函数关于模型参数的梯度信息也可以作为选取控制变量的标准之一，这从另一个角度解决了如何确定控制变量的问题。另外，通过孪生实验验证了在渤、黄海NPZD生态模式中使用伴随同化技术同化水色遥感数据的可行性，这为以后将水色卫星遥感数据同化到海洋生态模型中奠定了基础。

广义变分原理的结构形状优化伴随法灵敏度分析

提出了一种利用伴随变量进行结构形状优化灵敏度分析的新方法.基于广义变分原理,考虑了形状优化中位移边界条件的变化对结构响应的影响.新方法弥补了Arora等人所提出的形状优化灵敏度分析变分原理中的缺陷,为采用伴随法进行灵敏度分析提供了新的框架.

基于均匀化理论的微小型柔性结构拓扑优化的敏度分析

介绍微小型柔性结构在ＭＥＭＳ中的应用前景及连续体结构拓扑优化的一般方法。在此基础上探讨利用均匀化理论、有限元及伴随变量法计算连续体结构拓扑优化敏度响应的方法，并取得较为理想的数值计算结果。

抛物线型无损耗传输线的时域灵敏度分析

频域灵敏度分析只能适用于线性网络。为了解决含非线性的问题,提出了一种由频域灵敏度公式求线性元件时域灵敏度公式的方法。基于伴随网络法和已有的频域灵敏度公式,推导出了抛物线型无损耗传输线的时域灵敏度公式,较好地解决了这类非均匀线的灵敏度求解问题。

1991年夏季持续性异常环流的共轭敏感性分析

在共轭敏感性分析的基础上发展了最敏感扰动的概念。用共轭模式对江淮流域大水１９９１年东亚夏季环流的持续异常特征，包括乌拉尔阻塞高压、鄂霍次克海偶极子型阻塞以及副热带高压的变动过程进行了分析，分别得到了对这些过程影响最大的初始扰动。结果从新的角度揭示了这些系统最重要的影响因子，也显示了共轭敏感性分析方法在大气环流物理过程诊断中的有效性和应用前景。