Multivariate Interactive Visualization of Data in Generative Design

We describe our work on providing support for design decision making in generative design systems producing large quantities of data, motivated by the continuing challenge of making sense of large design and simulation result datasets. Our approach provides methods and tools for multivariate interactive data visualization of the generated...

Parameter Identification of Consolidation Settlement Based on Multi-objective Optimization

Due to the complexity of natural ground condition, consolidation settlement is usually difficult to predict. In this study, a Pareto multi-objective optimization based back analysis method for consolidation settlement is presented in this study. The model is a coupled flow and deformation model for unsaturated soil foundation which is...

Multi-Objective Optimization for Urban Drainage Rehabilitation

Flooding in urbanized areas has become a very important issue around the world. The level of service (or performance) of urban drainage systems (UDS) degrades in time for a number of reasons. In order to maintain an acceptable performance of UDS, early rehabilitation plans must be developed and implemented. In developing countries the situation...

Learning from model improvement: On the contribution of complementary data to process understanding

A priori determined model structures are common in catchment rainfall-runoff modeling. While this has resulted in many ready-to-use modeling tools, there are several shortcomings of a one-size-fits-all model structure. The uniqueness of catchments with respect to their hydrological behavior and the need to adapt model complexity to data...

Understanding catchment behavior through stepwise model concept improvement

Lack of data is one of the main limitations for hydrological modeling. However, it is often used as a justification for over simplifying, poorly performing models. If we want to enhance our understanding of hydrological systems, it is important to fully exploit the information contained in the available data, and to learn from model deficiencies...