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This thesis deals with the redesign of manufacturing systems by simulation and optimization. Material flow simulation is a common tool for solving problems in system design. Limitations are the high requirements in time and knowledge to execute simulation studies, evaluate results and solve design problems. New chances arrives with the technologies of industry 4.0 and the digital shadow, providing data for simulation. However, the methods to use production data for the redesign of production systems are not available yet. Purpose of this work is providing the methods to automate simulation from digital shadow, use simulation to optimize and solve problems in system design. Two case studies are used to support the action research approach of this work. The result of this work is a framework for the application of the digital shadow in optimization and problem-solving.
We tested the MOF framework Cu-BTC for natural gas (NG) storage. Adsorption isotherms of C1–C4 alkanes were simulated applying the Grand Canonical ensemble and the Monte Carlo algorithm in a classical molecular mechanics approach. Experimental monocomponent isotherm of the alkanes was used to validate the force field. We performed multicomponent adsorptions calculations for three different quaternary mixtures of C1–C4 alkanes, matching typical NG streams composition, and predicted theoretical storage capacities, efficiency and accumulation of the NG within that composition. Despite being one of the frameworks with greatest storage capacity of methane, we found that Cu-BTC presented great sensitivity to the variation of the heavier alkanes in NG composition. When we increase the percentage of butane from 0.1% to 0.7% in the mixture, the mass of components retained in the discharge pressure (1 bar) increases from 35 to 60%. We also perform siting and interaction energy investigations and compare the NG storage performance of the Cu-BTC with that of activated carbons. To our knowledge, this is the first study regarding the efficiency of the NG storage in Cu-BTC.
We present an electrochemical model of a lithium iron phosphate/graphite (LFP/C6) cell that includes combined aging mechanisms: (i) Electrochemical formation of the solid electrolyte interphase (SEI) at the anode, leading to loss of lithium inventory, (ii) breaking of the SEI due to volume changes of the graphite particles, causing accelerated SEI growth, and (iii) loss of active material due to of loss percolation of the liquid electrolyte resulting from electrode dry-out. The latter requires the introduction of an activity-saturation relationship. A time-upscaling methodology is developed that allows to simulate large time spans (thousands of operating hours). The combined modeling and simulation framework is able to predict calendaric and cyclic aging up to the end of life of the battery cells. The aging parameters are adjusted to match literature calendaric and cyclic aging experiments, resulting in quantitative agreement of simulated nonlinear capacity loss with experimental data. The model predicts and provides an interpretation for the dependence of capacity loss on temperature, cycling depth, and average SOC. The introduction of a percolation threshold in the activity-saturation relationship allows to capture the strong nonlinearity of aging toward end of life (“sudden death”).
The durability of polymer electrolyte membrane fuel cells (PEMFC) is governed by a nonlinear coupling between system demand, component behavior, and physicochemical degradation mechanisms, occurring on timescales from the sub-second to the thousand-hour. We present a simulation methodology for assessing performance and durability of a PEMFC under automotive driving cycles. The simulation framework consists of (a) a fuel cell car model converting velocity to cell power demand, (b) a 2D multiphysics cell model, (c) a flexible degradation library template that can accommodate physically-based component-wise degradation mechanisms, and (d) a time-upscaling methodology for extrapolating degradation during a representative load cycle to multiple cycles. The computational framework describes three different time scales, (1) sub-second timescale of electrochemistry, (2) minute-timescale of driving cycles, and (3) thousand-hour-timescale of cell ageing. We demonstrate an exemplary PEMFC durability analysis due to membrane degradation under a highly transient loading of the New European Driving Cycle (NEDC).
Institute of Reliable Embedded Systems and Communication Electronics, Offenburg University of Applied Sciences, Germany has developed an automated testing environment, Automated Physical TestBeds (APTB), for analyzing the performance of wireless systems and its supporting protocols. Wireless physical networking nodes can connect to this APTB and the antenna output of this attaches with the RF waveguides. To model the RF environment this RF waveguides then establish wired connection among RF elements like splitters, attenuators and switches. In such kind of set up it’s well possible to vary the path characteristics by altering the attenuators and switches. The major advantage of using APTB is the possibility of isolated, well controlled, repeatable test environment in various conditions to run statistical analysis and even to execute regression tests. This paper provides an overview of the design and implementation of APTB, demonstrates its ability to automate test cases, and its efficiency.
Cast iron materials are used as materials for cylinder heads for heavy duty internal combustion engines. These components must withstand severe cyclic mechanical and thermal loads throughout their service life. While high-cycle fatigue (HCF) is dominant for the material in the water jacket region, the combination of thermal transients with mechanical load cycles results in thermomechanical fatigue (TMF) of the material in the fire deck region, even including superimposed TMF and HCF loads. Increasing the efficiency of the engines directly leads to increasing combustion pressure and temperature and, thus, lower safety margins for the currently used cast iron materials or alternatively the need for superior cast iron materials. In this paper (Part I), the TMF properties of the lamellar graphite cast iron GJL250 and the vermicular graphite cast iron GJV450 are characterized in uniaxial tests and a mechanism-based model for TMF life prediction is developed for both materials. The model can be used to estimate the fatigue life of components by means of finite-element calculations (Part II of the paper) and supports engineers in finding the appropriate material and design. Furthermore, the effect of the elastic, plastic and creep properties of the materials on the fatigue life can be evaluated with the model. However, for a material selection also the thermophysical properties, controlling to a high level the thermal stresses in the component, must be considered. Hence, the need for integral concepts for material characterization and selection from a multitude of existing and soon-to-be developed cast iron materials is discussed.
A complete thermomechanical fatigue (TMF) life prediction methodology is developed for predicting the TMF life of cast iron cylinder heads for efficient heavy duty internal combustion engines. The methodology uses transient temperature fields as thermal loads for the non-linear structural finite-element analysis (FEA). To obtain reliable stress and strain histories in the FEA for cast iron materials, a time and temperature dependent plasticity model which accounts for viscous effects, non-linear kinematic hardening and tensioncompression asymmetry is required. For this purpose a unified elasto-viscoplastic Chaboche model coupled with damage is developed and implemented as a user material model (USERMAT) in the general purpose FEA program ANSYS. In addition, the mechanismbased DTMF model for TMF life prediction developed in Part I of the paper is extended to three-dimensional stress states under transient non-proportional loading conditions. The material properties of the plasticity model are determined for lamellar graphite cast iron GJL250 and vermicular graphite cast iron GJV450 from isothermal and non-isothermal uniaxial tests. The methodology is applied to obtain a TMF life prediction on two cast iron cylinder heads for heavy duty diesel engine applications made from both cast iron materials. It is shown that the life predictions using the developed methodology correlate very well with observed lives from two bench tests in terms of location as well as number of cycles to failure.
Practical exercises are a crucial part of many curricula. Even simple exercises can improve the understanding of the underlying subject. Most experimental setups require special hardware. To carry out e. g. a lens experiments the students need access to an optical bench, various lenses, light sources, apertures and a screen. In our previous publication we demonstrated the use of augmented reality visualization techniques in order to let the students prepare with a simulated experimental setup. Within the context of our intended blended learning concept we want to utilize augmented or virtual reality techniques for stationary laboratory exercises. Unlike applications running on mobile devices, stationary setups can be extended more easily with additional interfaces and thus allow for more complex interactions and simulations in virtual reality (VR) and augmented reality (AR). The most significant difference is the possibility to allow interactions beyond touching a screen. The LEAP Motion controller is a small inexpensive device that allows for the tracking of the user’s hands and fingers in three dimensions. It is conceivable to allow the user to interact with the simulation’s virtual elements by the user’s very hand position, movement and gesture. In this paper we evaluate possible applications of the LEAP Motion controller for simulated experiments in augmented and virtual reality. We pay particular attention to the devices strengths and weaknesses and want to point out useful and less useful application scenarios. © (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.