On auto- and cross-interdependence in interval field finite element analysis

This paper discusses the concepts of auto- and cross-interdependence in interval field finite element analysis. In classic interval analysis, independent intervals are used to construct hyper-rectangular input spaces that correspond to the bounded uncertainty that is present on some model parameters. This is a direct result from the inability of modeling interdependence. Such assumption of complete independence might prove in some cases to be highly over-conservative. A first example is the modeling of spatial uncertainty, where the interdependence is governed by allowable spatial gradients of field realizations. Secondly, interdependence can also occur in case uncertainty in several structural quantities has the same root cause (eg, the manufacturing process). Recent work by the authors introduced concepts for modeling dependence between intervals in a spatial and multivariate context. However, it is unclear how an analyst has to deal with multiple quantities that have a spatial uncertainty component and are furthermore interdependent. This paper presents an approach to link multiple interval fields using recently introduced convex hull pair constructions and inverse distance weighting interpolation. Two case studies to illustrate the new methodology are included, proving the flexibility of the methodology in the modeling of auto- and cross-interdependence between multiple interval scalars and/or interval fields.     

Supply chain network design under the risk of uncertain disruptions

Facility disruptions in the supply chain often lead to catastrophic consequences, although they occur rarely. The low frequency and non-repeatability of disruptive events also make it impossible to estimate the disruption probability accurately. Therefore, we construct an uncertain programming model to design the three-echelon supply chain network with the disruption risk, in which disruptions are considered as uncertain events. Under the constraint of satisfying customer demands, the model optimises the selection of retailers with uncertain disruptions and the assignment of customers and retailers, in order to minimise the expected total cost of network design. In addition, we simplify the proposed model by analysing its properties and further linearise the simplified model. A Lagrangian relaxation algorithm for the linearised model and a genetic algorithm for the simplified model are developed to solve medium-scale problems and large-scale problems, respectively. Finally, we illustrate the effectiveness of proposed models and algorithms through several numerical examples.     

基于集合卡尔曼滤波的岩土力学参数动态估计

 针对非确定性过程，引入集合卡尔曼滤波(EnKF)理论，视岩土变形体为一个随机动态系统，将位移观测值作为系统的输出，用集合卡尔曼滤波模型来描述系统的状态；进一步耦合数值分析方法实现岩土力学参数的随机动态估计，在有效地获得待估参数的同时还给出估计值的不确定性。通过数值算例表明，集合卡尔曼滤波可以有效地对含噪声的量测数据进行处理，能够跟踪岩土力学行为的动态变化。对比于常用最优化算法，集合卡尔曼滤波同时给出反演结果和先验知识的后验分布，显示出更好的实时性和可靠性。     

Risk and its risks: discussion of ‘Risk – a commentary’ by D.G. Carmichael

The nature of risk needs to be more clearly understood. Risk management could be tightened as a discipline, particularly by adopting an underlying foundation of systems thinking. Risk management, even when well done, has inherent limitations, and these should be well understood, particularly those arising from modelling, completeness, correlation effects, and the often-great uncertainties in estimates of both likelihood and consequence. Modelling is centrally important: both this and risk must be intimately related to decision-making. A clear understanding of this connection is essential to sound work in the discipline.     

Partial factors for imposed loads in areas for storage and industrial use

The procedures for reliability verification of new or existing buildings are calibrated to account for uncertainties and variability of resistance and load parameters. However, present standards often provide a single approach to specification of design values of all imposed loads on buildings without particular distinction between loads associated with considerable uncertainties and well-defined loads. While the former are represented by common loads in office and residential buildings, the latter, including loads due to storage of materials, material handling equipment, machinery or tanks, require different approaches for estimating design values. This contribution identifies the characteristics of well-defined imposed loads and proposes a methodology for calibrating partial factors. Key steps of the methodology consist of assessing static load effect, dynamic amplification if relevant, model uncertainty, sensitivity factors and target reliability. Careful consideration of these influences then yields partial factors that reflect reduced uncertainties in estimating the effects of well-defined imposed loads. It appears that the commonly accepted partial factor of 1.5 in Eurocodes may be reduced. When multiple crossings are considered, the partial factor can be taken independent of the number of crossings while the characteristic value is adjusted. Further studies should be particularly focused on advanced probabilistic modelling of dynamic amplification and of model uncertainties.     

Robust guaranteed cost ILC with dynamic feedforward and disturbance compensation for accurate PMSM position control

This contribution presents a robust ILC control design based on guaranteed costs. By combining this ILC design with dynamic feedforward control and an observer-based disturbance compensation, the initial tracking errors in an early learning stage can be reduced. The benefits of the proposed design approach are pointed out at the example of a robust position control of a Permanent Magnet Synchronous Motor (PMSM), which is subject to uncertain model parameters. The paper is concluded with convincing experimental results from a dedicated test rig. Moreover, a comparison with a classical observer-based tracking control is provided.     

Distance-dependent depth-duration analysis in high-resolution hydro-meteorological ensemble forecasting: A case study in Malmö City,Sweden

In 2014, a cloudburst hit Malmö City and parts of the city were severely flooded. In this study, we assess the possibility to forecast this event by high-resolution ensemble rainfall-runoff modelling. Meteorological reforecasts are generated by the convection-permitting HarmonEPS model and the hydrological response is simulated by the HYPE model. Although the meteorological forecasts manage to reproduce the observed extreme rainfall intensities, due to location errors only a weak, low-probability signal of a high runoff in Malmö City is obtained in direct forecasts. To describe and visualize the spatial uncertainty of local rainfall extremes in forecasts, and construct hydrological model forcing representing “worst-case ensembles”, an approach called Distance-Dependent Depth-Duration in Forecasts (4DF) is proposed. In this approach, a depth-duration analysis is combined with a neighborhood approach to describe rainfall severity as a function of distance from the basin. The results demonstrated the applicability of the approach for improved situation awareness.     

Adjustable Robust Optimisation approach to optimise discounts for multi-period supply chain coordination under demand uncertainty

In this research, a problem of supply chain coordination with discounts under demand uncertainty is studied. To solve the problem, an Affinely Adjustable Robust Optimisation model is developed. At the time when decisions about order periods, ordering quantities and discounts to offer are made, only a forecasted value of demand is available to a decision-maker. The proposed model produces a discount schedule, which is robust against the demand uncertainty. The model is also able to utilise the information about the realised demand from the previous periods in order to make decisions for future stages in an adjustable way. We consider both box and budget uncertainty sets. Computational results show the necessity of accounting for uncertainty, as the total costs of the nominal solution increase significantly even when only a small percentage of uncertainty is in place. It is testified that the affinely adjustable model produces solutions, which perform significantly better than the nominal solutions, not only on average, but also in the worst case. The trade-off between reduction of the conservatism of the model and the uncertainty protection is investigated as well.     

随钻自然伽马刻度装置及量值传递研究

文章提出随钻自然伽马测井仪刻度的必要性和特殊性，给出了刻度装置的设计和量值传递的流程，同时还导出测量及计算方法。     

300℃以上热电偶量传体系问题分析及对策

针对目前300℃以上热电偶量传体系存在不确定度过大、计量能力不满足要求等问题,分析了高温共晶点和实用型固定点温度复现、纯金属热电偶温度测量和1500℃以上高温热电偶校准等技术的最新进展,提出基于固定点温度复现方法的新的量值传递体系设想,可大大减小热电偶量值传递的不确定度,使各级计量标准装置不确定度分布更为合理,能保证热电偶量值的逐级量传,满足科研生产对热电偶的溯源要求。