Bøger udgivet af Karlsruher Institut Fur Technologie

This work provides novel robust and regularized algorithms for parameter estimation with applications in vehicle tractive force prediction and mass estimation. Given a large record of real world data from test runs on public roads, recursive algorithms adjusted the unknown vehicle parameters under a broad variation of statistical assumptions for two linear gray-box models.

Experiments to characterize the effects of moisture content and temperature on the mechanical properties of concrete were conducted. Based on these experiments, a new overall material model capable of predicting the mechanical behaviour of concrete subject to elevated temperatures up to 100 °C was developed. The material model estimates the time, temperature and moisture dependency of the compressive and tensile strength, creep and shrinkage of concrete.

Lean management describes a set of methods combined with a management philosophy which aims at eliminating waste in logistics processes. In production logistics, lean is already widespread and applied successfully. Research has shown that lean also works in a warehousing environment. In transport logistics, lean is still at a low level of maturity in both research and practice. This work contributes to closing this gap by introducing Heijunka leveling to transport logistics.

A general analytical travel time model for the quadruple command cycle in double deep storage systems with a dual capacity load handling device is formulated and validated by means of a simulation model. Various routing and sequencing strategies are composed. A simulation model is used to compare strategies for differnt AS/RS configurations and settings to assess them in consideration of real-world cases. For selected strategies, analytical formulations are derived.

This book presents, validates and applies a fast, accurate and general measurement and modeling technique to obtain spectral near field data of LED systems for optical simulations in order to address the steadily increasing requirements of modern high quality LED systems. It requires only a minimum of goniophotometric near field measurements and no time-consuming angularly resolved spectral measurements. The obtained results can be used directly in state-of-the-art ray tracers.

Previously, software architects were unable to effectively and efficiently apply reusable knowledge (e.g., architectural styles and patterns) to architectural analyses. This work tackles this problem with a novel method to create and apply templates for reusable knowledge. These templates capture reusable knowledge formally and can efficiently be integrated in architectural analyses.

In this book, we introduce an automatic, experiment-based approach for performance problem diagnostics in enterprise software systems. The proposed approach systematically searches for root causes of detected performance problems by executing series of systematic performance tests. The presented approach is evaluated by various case studies showing that the presented approach is applicable to a wide range of contexts.

Based on physiological data, intelligent algorithms can assist with the classification and recognition of the most severely impaired victims. This book presents a new sensorbased triage platform with the main proposal to join different sensor and communications technologies into a portable device. This new device must be able to assist the rescue units along with the tactical planning of the operation. This work discusses the implementation and the evaluation of the platform.

The characteristic vortex formation in the ventricles is believed to be affected at an early stage of heart diseases. First, post-processing of patient-specific data has to be standardised. The chosen methods, a combination of Eulerian and Lagrangian techniques, are characterised by means of necessary spatial and temporal resolutions. Second, the goal is to find the best cost-benefit approach for modelling of the mitral valve, as it affects vortex formation and progression in the left ventricle.

Equipping robots with complex capabilities still requires a great amount of effort. In this work, a novel approach is proposed to understand, to represent and to execute object manipulation tasks learned from observation by combining methods of data analysis, graphical modeling and artificial intelligence. Employing this approach enables robots to reason about how to solve tasks in dynamic environments and to adapt to unseen situations.

Shuttle-based storage and retrieval systems (SBS/RSs) are an important part of today's warehouses. In this work, a new approach is developed that can be applied to model different configurations of SBS/RSs. The approach is based on the modeling of SBS/RSs as discrete-time open queueing networks and yields the complete probability distributions of the performance measures.

The technologies currently employed for modeling complex systems, such as aircraft, spacecraft, or infrastructures, are sufficient for system description, but do not allow deriving knowledge about the modeled systems. This work provides the means to describe space systems in a way that allows automating activities such as deriving knowledge about critical parts of the system's design, evaluation of test success, and identification of single points of failure.

This work develops and shows up methods to tackle multi-scale challenges in particle formation during precipitation crystallization. Firstly, molecular, micro- and meso-scale interactions in confined impinging jet mixers are investigated and simulatively predicted. Secondly, to build up on developed methods, macroscale as present for instance in stirred tank reactors is added to the considerations.