Automated simulation-based verification of power requirements for Systems-on-Chips

Author(s):  
Christoph Trummer ◽  
Christoph M. Kirchsteiger ◽  
Christian Steger ◽  
Reinhold Weiss ◽  
Markus Pistauer ◽  
...  

Author(s):  
Christoph Trummer ◽  
Christoph M. Kirchsteiger ◽  
Christian Steger ◽  
Reinhold Weiss ◽  
Markus Pistauer ◽  
...  


2004 ◽  
Author(s):  
Saghir Munir ◽  
Daniel J. Bald ◽  
Vikram Tolani ◽  
Firoz Ghadiali ◽  
Barry Lieberman


2017 ◽  
Vol 16 (1) ◽  
pp. 5-18 ◽  
Author(s):  
Y. Harari ◽  
A. Bechar ◽  
U. Raschke ◽  
R. Riemer


Author(s):  
Daniel Hofmann ◽  
Hongrong Huang ◽  
Gunther Reinhart

Orienting devices for vibratory bowl feeders are still the most widely used system for the automated sorting and feeding of small parts. The design process of these orienting devices has recently been supported by simulation methods. However, this merely shifts the well-known trial-and-error-based adaption of the orienting device's geometry into virtual world. Yet, this does not provide optimal design and, furthermore, requires strong involvement of the developer due to manual shape variation. This paper proposes an optimization algorithm for the automated simulation-based shape optimization of orienting devices for vibratory bowl feeders. First, general formalisms to state the multiobjective optimization problem for arbitrary types of orienting devices and feeding parts are provided. Then, the implementation of the algorithm is described based on Bullet Physics Engine and random search optimization technique. Finally, comparison of simulation results with experimental data point out good accuracy and, thus, great potential of the developed shape optimization software.





Author(s):  
Neil Winchester ◽  
Steve Hall

The activity of Life-Cycle Cost (LCC) forecasting using Reliability, Availability, and Maintainability (RAM) modeling techniques is not new, but there have been recent developments which have resulted in a fundamental change in the usefulness of LCC forecasting to designers, owners, operators, and maintainers of power plants. These changes provide the means for optimizing Operation and Maintenance (O&M) activities many years in advance with a high degree of accuracy. The primary changes have been advances in technology and the introduction of Monte Carlo-based discrete event simulation technology to perform RAM forecasting. Simulation based LCC forecasting can be used to determine the optimum operating and maintenance support scenarios. Main areas of optimization include the initial and through life cost, spares inventory holding, maintenance scheduling, logistics, etc. By allowing various scenarios to be explored in a simulation environment, LCC forecasting provides an accurate and cost effective method for optimizing costs — an activity with a very high Return On Investment (ROI) value proposition. This paper describes the methodology undertaken and the results that can be obtained from the application of automated, simulation-based LCC forecasting technology to the analysis of gas turbine based generating units.



Author(s):  
Jordan Gowanlock

AbstractThis chapter investigates the way engineering principles have transformed cinematic visual effects and animation production since the 1980s, noting the growing influence of “agile” software development. Film industry training manuals, trade press articles, and interviews with workers show that the flexible, reprogrammable nature of production “workflows” requires constant work to maintain the technical connective tissue of “pipelines.” This emphasis on making and re-making custom tools for every production serves post-Fordist demands of flexibility. Automated simulation-based forms of animation offer a paradigmatic case for these trends, where a spectrum of technical work spans basic research done by lead scientists, through to the scripts written and plug-ins installed by simulation artists.







2021 ◽  
Vol 120 (3) ◽  
pp. 173a
Author(s):  
Linnea S. Axelsson ◽  
Urska Rovsnik ◽  
Christian Blau ◽  
Marie Lycksell ◽  
Victoria Lim ◽  
...  


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