A transfer function technique to describe odor causing VOCs transport in a ventilated airspace with mixing/adsorption heterogeneity

A model describing odor causing volatile organic compounds (VOC-odor) transport in a ventilated airspace influenced by heterogeneity of adsorption surface of ambient aerosol and air mixing pattern is proposed and analyzed based on a transfer function modeling technique. In this study an advection–reaction impulse/step response function for VOC-odor is assumed. The system process presented by an ensemble transfer function is solved analytically in the Laplace domain. The analytical results are then numerically inverted using a modified fast Fourier transform algorithm. The model requires the specification of probability density function for residence time of airflow and for both equilibrium linear partitioning and first-order mass transfer rate parameters to quantify the specific air mixing pattern and transport processes. The model predicts the ensemble mean VOC-odor concentrations for a variety of adsorption kinetics and mixing pattern combinations as a function of the boundary impulse/step response inputs as well as residence time and adsorption rate statistics. The general behavior of output VOC-odor profiles is analyzed through the effects of mean adsorption rate coefficient, mean linear partitioning constant, mixing efficiency, mean residence time and coefficient of variations of both linear partitioning and rate coefficients. It indicates that when mixing/adsorption heterogeneity exists, simple complete mixing assumption and simple distribution of rate constant is inherently not sufficient to represent a more generally distributed mixing/adsorption process of VOC-odor transport in a ventilated airspace.     

Modelling lumped-parameter sorption kinetics and diffusion dynamics of odour-causing VOCs to dust particles

An analytical algorithm is presented for fast simulation of the adsorption kinetics and diffusion dynamics of odour-causing volatile organic compounds (VOC-odour) which originate in the stored swine manure to airborne dust particles in a ventilated airspace. The model is an extension to the well-known lumped-parameter model (LPM) that incorporates a Langmuir–Hinshelwood (LH) kinetic concept dependent on VOC-odour concentration with diffusion limitation. The basic idea behind the model implementation is to couple the calculations of the two major processes in the VOC-odour/dust particle system: VOC-odour diffusion based on the homogeneous surface diffusion model (HSDM) and surface reaction based on the LH kinetics in an LPM scheme. The LPM employs Laplace transforms and gamma distributions of the rate coefficient to produce a lumped-parameter gamma model (LPGM) for kinetic equation of VOC-odour adsorption to airborne dust particles, whereas the HSDM incorporates the age and size distributions of airborne dust for evaluating the dust-borne VOC-odour dynamics. The integrate assessment of VOC-odour sorption kinetics and diffusion dynamics allows to relate the adsorption rate coefficient, reaction order, and surface effective diffusivity in a complex VOC-odour/dust particle system. The LPGM fitted well with the data obtained numerically from HSDM and successfully determined the adsorption rate coefficient and reaction order for each sorption process.     

脑内各向异性扩散传质与吸附反应过程数值分析

对脑组织内传质过程的机理及其影响因素进行了分析,建立了综合考虑脑内物质各向异性扩散、吸附和反应过程的数学模型,模型方程采用隐式控制容积法进行数值求解.计算结果表明:组织迂曲度越大,物质的扩散越慢,当某一方向迂曲度较小时,物质浓度明显增大,物质扩散变快,由于脑组织的非均质性,脑内物质的扩散传递存在着竞争现象;吸附与反应作用会抑制脑内物质传递,吸附速率越大,抑制现象越明显,对于脑内非线性的米氏反应过程,当反应速率常数增大时,稳定浓度会显著减小,同时米氏常数的增大则会使得稳定浓度值增大.相较于吸附过程,米氏过程的抑制性作用更为明显.     

Configuration of airspace sectors for balancing air traffic controller workload

In this paper, we consider the problem of reconfiguring a section of the national airspace into appropriate sectors from the viewpoint of balancing the predicted air traffic controller workload. The given section of the airspace is specified as a convex polygon in two-dimensions (or a union of such structures), and contains a discretized set of weighted grid points representing localized sub-regions, where the weights reflect the associated air traffic controller monitoring and conflict resolution workloads. We describe four variants of a mixed-integer programming-based algorithmic approach to recursively partition the specified airspace region so as to balance the total weight distribution within each resulting sector. In addition, we augment the proposed model to further accommodate inter-sector coordination workload within this partitioning process, which accounts for the number of flight hand-offs between adjacent sectors. Some illustrative examples are presented to assess the proposed methodology and to investigate the relative computational efficiency and the quality of solutions produced by each algorithmic variant. One competitive procedure is then used to configure a region of airspace over the U.S. using realistic flight data. The main purpose of this work is to provide some modeling concepts and insights to complement the rich body of existing literature on this topic.     

Numerical analysis of two ensemble eddy viscosity numerical regularizations of fluid motion

This report analyzes an efficient ensemble regularization algorithm for under‐resolved and convection dominated flows (including ones at higher Reynolds numbers). Computing an ensemble simultaneously allows each realization to access ensemble data. This allows use of means and fluctuations in regularizations used for each realization. The combined approach of ensemble time stepping and ensemble regularizations allows direct calculation of the turbulent viscosity coefficient and gives an unconditionally stable algorithm. It also suggests reconsidering an old but not as well‐developed definition of the mixing length. This mixing length vanishes at solid walls without van Driest damping, increases stability, and improves flow predictions in our preliminary tests. © 2014 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 31: 630–651, 2015     

Time series forecasting with neural network ensembles: an application for exchange rate prediction

This paper investigates the use of neural network combining methods to improve time series forecasting performance of the traditional single keep-the-best (KTB) model. The ensemble methods are applied to the difficult problem of exchange rate forecasting. Two general approaches to combining neural networks are proposed and examined in predicting the exchange rate between the British pound and US dollar. Specifically, we propose to use systematic and serial partitioning methods to build neural network ensembles for time series forecasting. It is found that the basic ensemble approach created with non-varying network architectures trained using different initial random weights is not effective in improving the accuracy of prediction while ensemble models consisting of different neural network structures can consistently outperform predictions of the single ‘best’ network. Results also show that neural ensembles based on different partitions of the data are more effective than those developed with the full training data in out-of-sample forecasting. Moreover, reducing correlation among forecasts made by the ensemble members by utilizing data partitioning techniques is the key to success for the neural ensemble models. Although our ensemble methods show considerable advantages over the traditional KTB approach, they do not have significant improvement compared to the widely used random walk model in exchange rate forecasting.     

Time relaxation algorithm for flow ensembles

Modeling for fast calculation of fluid flow ensembles based on time relaxation regularization is studied herein. At each time step, the proposed model requires the storage of a single coefficient matrix with multiple right‐hands sides, corresponding to each ensemble member. The time relaxation regularization penalizes the deviation of the fluctuations from the ensemble average. The algorithm is shown to be stable under a time step restriction, which holds provided fluctuations are small enough. Also, the numerical tests show that a grad‐div stabilization weakened the condition considerably. Finite element convergence results for the time relaxation ensemble algorithm are studied too. Then, 2D and 3D numerical experiments that support the theoretical results are presented. © 2015 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 32: 757–777, 2016     

多釜串联模型停留时间分布方差的推导

简要分析了理想反应器的特点,并指出现实反应器与理想反应器的区别,介绍了多釜串联模型描述实际反应器的思想.针对多釜串联模型的停留时间分布的计算函数进行逐步的推导,以阶跃法对模型进行分析,采用数学归纳法和分部积分法等方法推导出了多釜串联模型无因次停留时间分布函数表达式;根据停留时间分布密度函数定义,推导出了无因次停留时间分布密度函数的表达式;根据概率中方差的定义,推导出了无因次方差的表达式.     

Numerical predictions of three-dimensional flow in a ventilated room using turbulence models

A three-dimensional recirculation flow in a ventilated room was predicted by the numerical methods in which the turbulence models are applied. The predicted results are compared with the experimental results obtained in a model room in order to estimate the practical utilities of such methods from the viewpoint of engineering. Taking account of the practicability of prediction method which the engineers regard as important, two turbulence models were selected and they were incorporated into the numerical prediction methods respectively. One is the two-equation model, in which transport equations of turbulence energy and its rate of dissipation are adopted. The other is the Deardoff's model, in which the subgrid scale eddy coefficient is utilized. The prediction was made by each numerical method. Consequently, no noticeable difference is recognized between both predicted results. Each result is compared with the experimental results. Generally speaking, each agreement is good with regard to the mean velocity. Thus we can conclude that the numerical method using the two-equation model has more practical utility than that using Deardoff's model, because it can give the solutions in a shorter computer time.     

Numerical modeling of hydrodynamic and hydrothermal characteristics in subtropical alpine lake

A three-dimensional, time-dependent hydrodynamic and hydrothermal model was performed and applied to the subtropical alpine Yuan-Yang Lake (YYL) in northeastern region of Taiwan. The model was driven with discharge inflow, heat, and wind stress to simulate the hydrodynamic and hydrothermal in the lake. The model was validated with measured water surface elevation, current, and temperature in 2008. The overall model simulation results are in quantitative agreement with the available field data. The validated model was then used to investigate wind-driven current, mean circulation, and residence time in the YYL. The modeling results reveal that the velocity field along the wind axis present the variations over depth with return current where the velocity at the surface layer is along the wind direction while it is opposite near 1 m below water surface. The simulated mean current indicates that the surface currents flow towards the southwest direction and form a clock-wise rotation. The calculated residence time is strongly dependent on the inflows and wind effects. Regression analysis of model results reveals that an exponential regression equation can be employed to correlate the residence time to change of discharge input. The residence time without wind stress is higher than that with wind effect, indicating that wind plays an important role in lake mixing. The calculated residence time is approximately 2-2.5 days under low inflow with wind effect.     

α-混合序列下期望损失ES的两步核估计

期望损失(Expected Shortfall,ES)是当今最流行的金融资产风险管理的工具之一,是一个理想的一致性风险度量.本文在α-混合序列具有幂衰减混合系数条件下,用两步核估计估算风险度量ES的值,第一步是在险价值(Value at Risk,VaR)的核估计,第二步是ES的核估计.得到ES的核估计量的Bahadur表示,以及均方误差和渐近正态性的收敛速度.     

A light-propagation model for aircraft trajectory planning

Predicted air traffic growth is expected to double the number of flights over the next 20 years. If current means of air traffic control are maintained, airspace capacity will reach its limits. The need for increasing airspace capacity motivates improved aircraft trajectory planning in 4D (space+time). In order to generate sets of conflict-free 4D trajectories, we introduce a new nature-inspired algorithm: the light propagation algorithm (LPA). This algorithm is a wavefront propagation method that yields approximate geodesic solutions (minimal-in-time solutions) for the path planning problem, in the particular case of air-traffic congestion. In simulations, LPA yields encouraging results on real-world traffic over France while satisfying the specific constraints in air-traffic management.     

Heat and mass transfer in annular liquid jets: II. g-jitter

The effects of g-jitter on heat and mass transfer in underpressurized, annular liquid jets are analyzed numerically as a function of the amplitude and frequency of the gravitational modulation by means of a mapping technique that transforms the time-dependent geometry of these jets into a unit square and a conservative finite difference method. It is shown that the pressure coefficient, gas concentration at the jet's inner interface, heat fluxes at the jet's inner and outer interfaces and interfacial temperature are periodic functions of time whose amplitudes increase as the amplitude of the g-jitter is increased, but decrease as the jitter frequency is increased. The pressure coefficient is almost in phase with the heat flux at the jet's outer interface, and out of phase with the mass transfer rate at the jet's inner interface. It is also shown that the temperature field adapts itself rapidly to the imposed gravity modulation, and thermal equilibrium is reached quickly. However, mass transfer phenomena are very slow and require a very long time to become periodic.     

Models for single-sector stochastic air traffic flow management under reduced airspace capacity

Air traffic efficiency is heavily influenced by unanticipated factors that result in capacity reduction. Of these factors, weather is the most significant cause of delays in airport and airspace operations. Considering weather-related uncertainty, air traffic flow management involves controlling air traffic through allocation of available airspace capacity to flights. The corresponding decision process results in a stochastic dynamic problem where aircraft on the ground and in the air are controlled based on the evolution of weather uncertainty. We focus on the single-sector version of the problem that is applicable to a majority of cases where a volume of airspace has reduced capacity due to convective weather. We model the decision process through stochastic integer programming formulations and computationally analyse it for tractability. We then demonstrate through actual flight schedule data that a simplistic but practically implementable approximation procedure is a generally effective solution approach for these models.     

Numerical simulation for a long-range dispersion of a pollutant using Chernobyl data

A Lagrangian particle model has been developed and applied to a long-range atmospheric dispersion. The developed numerical model has been tested by comparing its predictions with the ¹³⁷Cs air concentrations recorded over European areas during the Chernobyl accident. Sensitivity studies were performed to investigate the numerical accuracy according to a variation of the parameters such as the mixing height and diffusion coefficient in the model. From a comparative study, the calculated concentration distributions were more sensitive to a variation of the mixing height than to the changes of the diffusion coefficient values. Also, the calculated concentrations agreed with the time series of the measured ones at some sampling points.     

Inverse problem for a class of one-dimensional wave equations with piecewise constant coefficients

We consider the problem of reconstructing the piecewise constant coefficient of a one-dimensional wave equation on the halfline from the knowledge of the displacement on the boundary caused by an impulse at time zero. This problem is formulated as a nonlinear optimization problem. The objective function of this optimization problem has several special features that have been exploited in building an ad hoc optimization method. The optimization method is based on the solution of a nonlinear system of equations by an algorithm consisting of the evaluation of the unknowns one by one.The research of the third author has been made possible through the support and sponsorship of the Italian Government through the Ministero Pubblica Istruzione under Contract M.P.I. 60% 1987 at the Università di Roma—La Sapienza.     

动态空域扇区划分管制员指派优化方法

以训练成本最小化为目标,构建了动态扇区划分管制员指派数学模型,通过引入虚拟扇区将模型设计成标准指派问题,为采用LINGO或MATLAB等工具求解奠定了基础.用空间集合抽象了管制员所管控扇区在扇区变动前后的位置关系,根据位置关系用代数式量化了指派成本.根据计算分析结果,提出了减少训练成本,缩短动态扇、区前置准备时间的建议措施.     

Free convection effects on the oscillatory flow of an incompressible viscous fluid past an infinite,vertical plate with variable suction

An analysis of a two-dimensional flow of an incompressible, viscous fluid past an infinite, vertical porous plate has been carried out under the following conditions: (i) the suction velocity normal to the plate varies periodically with time (ii) the free stream velocity oscillates in time about a constant mean (iii) the temperature difference between the constant plate temperature and the free stream temperature, causing the free convection currents in the boundary layer. Approximate solutions for the transient velocity, the transient temperature, the amplitude and the phase of the skin-friction and the rate of heat transfer are derived. The fluctuating parts of the velocity profiles, the transient velocity, the transient temperature are shown on graphs whereas the numerical values of the amplitude and the phase of the skin-friction and the rate of heat transfer are entered in tables. The results are discussed in a quantitative way.     

The influence of heat and mass transfer on MHD peristaltic flow through a porous space with compliant walls

The present study investigates the effects of heat and mass transfer on peristaltic transport in a porous space with compliant walls. The fluid is electrically conducting in the presence of a uniform magnetic field. Analytic solution is carried out under long-wavelength and low-Reynolds number approximations. The expressions for stream function, temperature, concentration and heat transfer coefficient are obtained. Numerical results are graphically discussed for various values of physical parameters of interest.