Process Simulations and Experimental Studies of CO2 Capture

Carbon dioxide, whose global emissions into the atmosphere have reached a maximum of about 36 billion tons per year (compared to the 6 billion tons emitted in 1950), is considered by far the main greenhouse gas (GHG) [...]

New support roller profile design for railway wheel re-profiling process by under-floor lathes with a single cutting tool

The wheel re-profiling is an important part of railway wheelset maintenance. Researchers and railway operators have been very concerned about how to minimize the loss of time during wheel re-profiling without decreasing safety. Avoiding wheelset disassembly means considerable time savings, while reducing wheel damage during operation. Underfloor wheel lathes are the most appropriate tool to achieve this double objective, and therefore the most used nowadays. Multi-cut tool lathes have the disadvantage of being extremely expensive. On the other hand, with single tool lathes, re-profiling is not smooth or safe enough when current convex profile support rollers are used. It is well known by the companies that during reprofiling the wheel suffers impacts/damaged. In this article, a methodology to optimize the profile of the support rollers used in underfloor single tool lathes for railway wheel re-profiling is proposed. This novel profile design will minimize damage and increase the safety of such lathes, since it proposes a greater smoothness in the process. Simulations of re-profiling process have been carried out by the finite element method showing that the designed roller profile reduces drastically the impact/damage during the operation. The impact generated between the re-profiling wheel and the rollers is avoided. Profile-optimized support rollers have been used in a real underfloor wheel lathe, showing good results.

Important Key Process Simulations in the Field of Steel Metallurgy

During the last decade, the chair for ‘Simulation and Modelling of Metallurgical Processes’ (SMMP) has worked on different metallurgical processes with the highlights of the following five industrial relevant topics: (i) modelling the as-cast structures of large steel castings; (ii) exploring the formation mechanisms of macrosegregation; (iii) describing magnetohydrodynamic and electrochemical phenomena in remelting processes, (iv) understanding how solidification and flow can be influenced by magnetohydrodynamics during steel continuous casting; and (v) describing nozzle clogging in steelmaking processes. In this contribution, the main achievements from the group on the above five topics are briefly described.

Neural Networks Applications to Combustion Process Simulation

Моделирование горения является ключевым аспектом полномасштабного трехмерного моделирования современных и перспективных двигателей для авиационно-космических силовых установок. В данной работе изучается возможность решения задач химической кинетики с использованием искусственных нейронных сетей. С помощью классических численных методов были построены наборы обучающих данных. Выбирая среди различных архитектур многослойных нейронных сетей и настраивая их параметры, мы разработали достаточно простую модель, способную решить эту проблему. Полученная нейронная сеть работает в рекурсивном режиме и может предсказывать поведение химической многовидовой динамической системы за много шагов. Combustion process simulations are the key aspect enabling full-scale 3D simulations of advanced aerospace engines. This work studies solving chemical kinetics problems with artificial neural networks. The training datasets were generated by classical numerical methods. Choosing a multi-layer neural network architecture and fine-tuning its parameters, we developed a simple model that can solve the problem. The neural network obtained works is recursive, and by running many iterations it can predict the behavior of a chemical multimodal dynamic system.  

Design of SRAM-based 8T-Cell for Memory Alias Table

Memory Alias Table exploits a major role in Register Renaming Unit (RRU) for maintaining the translation between logical registers to physical registers for the given instruction(s). This work presents the design of the memory Alias Table based on the 8TCell with multiport write, read, and content-addressable operation for 2-WAY three operands machine cycle. Results show that four read ports operate simultaneously within a half-cycle, while two-write ports operate simultaneously within the other half-cycle. The operation of content-addressable with two parallel ports is managed during the half-cycle of the read phase; thus, the three operations occur within a single cycle without latency. HSPICE simulations conduct 32-rows x 6-bit with 21T-Cell memory Alias Table that has 4- read ports, 2-write ports, and 2-content-addressable ports using a standard 65 nm/1V CMOS process. Simulations reveal that the proposed design operates within a one-cycle of 1 GHz consuming an average power of 0.87 mW

How biased are our models? – a case study of the alpine region

Geophysical process simulations play a crucial role in the understanding of the subsurface. This understanding is required to provide, for instance, clean energy sources such as geothermal energy. However, the calibration and validation of the physical models heavily rely on state measurements such as temperature. In this work, we demonstrate that focusing analyses purely on measurements introduces a high bias. This is illustrated through global sensitivity studies. The extensive exploration of the parameter space becomes feasible through the construction of suitable surrogate models via the reduced basis method, where the bias is found to result from very unequal data distribution. We propose schemes to compensate for parts of this bias. However, the bias cannot be entirely compensated. Therefore, we demonstrate the consequences of this bias with the example of a model calibration.

Dynamic Simulations of Manufacturing Processes: Hybrid-Evolving Technique

Hybrid physical-data-driven modeling techniques have steadily been developed to address the multi-scale and multi-physical aspects of dynamic process simulations. The analytical and computational features of a new hybrid-evolving technique for these processes are elaborated herein and its industrial applications are highlighted. The authentication of this multi-physical and multi-scale framework is carried out by developing an integrated simulation environment where multiple solver technologies are employed to create a reliable industrial-oriented simulation framework. The goal of this integrated simulation framework is to increase the predictive power of material and process simulations at the industrial scale.