Time and cost securing in complex large-scale projects

Meeting time and cost objectives in complex projects involves specific problems and risks. An attempt is made to analyse the components of total cost increase of a project caused by time delay. An outline is given as to how these considerations can be used to estimate cost increases in investors' decision situations as well as to ascertain fair contractual penalties and claims for compensation and for the evaluation of justified project acceleration costs.     

Markov analysis of qualitative dynamics1

Common sense sometimes predicts events to be likely or unlikely rather than merely possible. We extend methods of qualitative reasoning to predict the relative likelihoods of possible qualitative behaviors by viewing the dynamics of a system as a Markov chain over its transition graph. This involves adding qualitative or quantitative estimates of transition probabilities to each of the transitions and applying the standard theory of Markov chains to distinguish persistent states from transient states and to calculate recurrence times, settling times, and probabilities for ending up in each state. Much of the analysis depends solely on qualitative estimates of transition probabilities, which follow directly from theoretical considerations and which lead to qualitative predictions about entire classes of systems. Quantitative estimates for specific systems are derived empirically and lead to qualitative and quantitative conclusions, most of which are insensitive to small perturbations in the estimated transition probabilities. The algorithms are straightforward and efficient.     

Issues in nonlinear stochastic grey box identification

Grey box identification refers to the practice of identifying dynamical systems in model structures exploiting partial prior information. This contribution reviews a method for stochastic grey box identification and surveys experiences and lessons of applying it to a number of industrial processes. Issues to be addressed include advantages and costs of introducing stochastics into the model, the question of what contribution must be expected from the model designer as opposed to what can be formalized in computer algorithms, and an outlook on future plans to resolve present shortcomings.     

Remarks on the mean square tracking error

The purpose of this paper is to extend recent results of Ljung and Priouret to a more general class of regressors.     

Drying Characteristics of Barley Grain Dried in a Spouted-Bed and Combined IR-Convection Dryers

A study was performed to determine the drying characteristics and quality of barley grain dried in a laboratory scale spouted-bed dryer at 30, 35, 40, and 45°C and an inlet air velocity of 23 m/s^-1, and in an IR-convection dryer under an infrared radiation intensity of 0.048, 0.061, 0.073, and 0.107 W cm^-2 at an air velocity of 0.5 m/s^-1. The results show that the first, relatively short, phase of a sharp decrease in the drying rate was followed by the phase of a slow decrease. The time of barley drying depended on temperature of inlet air in a spouted-bed dryer and on radiation intensities in an IR-convection dryer. Barley drying at 45°C in a spouted-bed dryer was accompanied by the lowest total energy consumption. The average specific energy consumption was lower and the average efficiency of drying was higher for drying in a spouted-bed dryer. The effective diffusivities were in the range 2.20-4.52 × 10^-11 m² s^-1 and 3.04-4.79 × 10^-11 m²/s^-1 for barley dried in a spouted-bed and in an IR-convection dryer, respectively. There were no significant differences in kernel germination energy and capacity between the two drying methods tested.     

Bioprocess applications of model-based estimation techniques

The last decade has seen the development of a number of approaches for estimating those variables which are difficult to measure on-line in industrial process situations. Whilst a range of techniques is available, a common element is the use of process knowledge in the form of a system model. In the case of bioprocess systems, although a large range of models has been presented in the literature, their use in estimation schemes on an industrial scale has been limited. A number of reasons can be identified for their low level of utilisation. Of particular significance is the uncertainty which exists in quantifying system performance and the process-model mismatch which inevitably results. The level of ‘pre-defined model’ uncertainty, together with the knowledge gained during the course of the fermentation, serves to dictate estimator structure. The paper considers a range of estimation strategies and contrasts, through industrial applications, their performance characteristics and utility.     

Retrieving ocean surface current by 4-D variational assimilation of sea surface temperature images

In this article we propose a new method to estimate ocean mesoscale structures of the surface current velocity by processing sea surface satellite images. Assuming that the intensity level can be described by a transport-diffusion equation, the proposed approach is based on variational assimilation of image observations within a simple transport-diffusion model. This approach permits to retrieve the current velocity field from a sequence of satellite images. Results of processing synthetic data and real NOAA-AVHRR satellite images are presented and commented.     

齐次等式约束线性回归模型条件根方估计的效率

对齐次等式约束线性回归模型回归系数的约束最小二乘估计提出改进,引入一种估计的相对效率,证明在一定条件下,狭义条件根方估计、广义条件根方估计的效率均高于约束最小二乘估计的效率．