Abstract
Analysis and optimization of simulation-generated data have myriads of scientific and industrial applications. Fuel consumption and emissions over the entire drive cycle of a large fleet of vehicles is an example of such an application and the focus of this study. Temporal variation of fuel consumption and emissions in an automotive engine are functions of over twenty variables. Determining relationships between fuel consumption or emissions and the dependent variables plays a crucial role in designing an automotive engine. This paper describes the development of ACCOLADES (Advanced Concurrent COmputing for LArge-scale Dynamic Engine Simulations), a scalable workflow framework that exploits the task parallelism inherent in such analyses by using large-scale computing. Excellent weak scaling is observed on 4,096 cores of both an Intel Sandy Bridge-based cluster and a Blue-Gene/Q supercomputer.
Keywords
This material is based upon work supported by the U.S. Department of Energy, Office of Science, under Contract DE-AC02-06CH11357.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Aithal, S.M.: Analysis of the current signature in a constant-volume combustion chamber. Combust. Sci. Technol. 185, 336–349 (2013)
Aithal, S. M.: Development of an integrated design tool for real-time analyses of performance and emissions in engines powered by alternative fuels. In: Proceedings of the SAE 11th International Conference on Engines and Vehicles (2013). SAE Paper 2013–24-0134
Aithal, S.M.: Prediction of voltage signature in a homogeneous charge compression ignition (HCCI) engine fueled with propane and acetylene. Combust. Sci. Technol. 185, 1184–1201 (2013)
Aithal, S.M., Wild, S.M.: Development of a fast, robust numerical tool for the design, optimization, and control of IC engines. In: Proceedings of the SAE 11th International Conference on Engines and Vehicles (2013). SAE Paper 2013–24-0141
Belludi, N., Receveur, J., Raymond, J.: High-performance grid computing for cummins vehicle mission simulation: architecture and applications. In: Proceedings of the SAE 2011 Commercial Vehicle Engineering Congress (2011). SAE Paper 2011–01-2268
Ehrgott, M.: Multicriteria Optimization, 2nd edn. Springer-Verlag, Heidelberg (2005)
Fu, T.-C.: A review on time series data mining. Eng. Appl. Artif. Intell. 24, 164–181 (2011)
Homem-de-Mello, T., Bayraksan, G.: Monte Carlo sampling-based methods for stochastic optimization. Surv. Oper. Res. Man. Sci. 19, 56–85 (2014)
Kieckhafer, K., Walther, G., Axmann, J., Spengler, T.: Integrating agent-based simulation and system dynamics to support product strategy decisions in the automotive industry. In: Proceedings of the Winter Simulation Conference (2009), pp. 1433–1443
Lamb, D.A., Gorsich, D., Krayterman, D., Choi, K.K., Hardee, E., Du, L., Youn, B.D., Bettig, B., Ghiocel, D.: System level RBDO for military ground vehicles using high performance computing. In: Proceedings of the SAE 2008 World Congress and Exhibition. SAE Technical Paper 2008–01-0543 (2008)
Liu, Y., Wang, Z., Liang, J., Liu, X.: Synchronization and state estimation for discrete-time complex networks with distributed delays. IEEE Trans. Syst. Man Cybern. B 38, 1314–1325 (2008)
Moawad, A., Balaprakash, P., Rousseau, A., Wild, S.M.: Novel large scale simulation process to support DOT’s CAFE modeling system. In: Proceedings of the International Electric Vehicle Symposium and Exhibition, May 2015
Thornton, P.E., Running, S.W.: An improved algorithm for estimating incident daily solar radiation from measurements of temperature, humidity, and precipitation. Agric. For. Meteorol. 93, 211–228 (1999)
Vijayagopal, R., Sharer, P., Wild, S.M., Rousseau, A., Chen, R., Bhide, S., Dongarkar, G., Zhang, M., Meier, R.: Using multi-objective optimization for HEV component sizing. In: Proceedings of the International Electric Vehicle Symposium and Exhibition, no. EVS28_0153, May 2015
Acknowledgments
We gratefully acknowledge the computing resources provided by the Argonne Leadership Computing Facility and the Laboratory Computing Resource Center at Argonne National Laboratory.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Aithal, S.M., Wild, S.M. (2015). ACCOLADES: A Scalable Workflow Framework for Large-Scale Simulation and Analyses of Automotive Engines. In: Kunkel, J., Ludwig, T. (eds) High Performance Computing. ISC High Performance 2015. Lecture Notes in Computer Science(), vol 9137. Springer, Cham. https://doi.org/10.1007/978-3-319-20119-1_7
Download citation
DOI: https://doi.org/10.1007/978-3-319-20119-1_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-20118-4
Online ISBN: 978-3-319-20119-1
eBook Packages: Computer ScienceComputer Science (R0)