Digital filters for Hot-Mix Asphalt Complex Modulus Test Data Using Genetic Algorithm Strategies

Authors: Madhav V. Chitturi, Anshu Manik, Kasthurirangan Gopalakrishnan

Abstract:

The dynamic or complex modulus test is considered to be a mechanistically based laboratory test to reliably characterize the strength and load-resistance of Hot-Mix Asphalt (HMA) mixes used in the construction of roads. The most common observation is that the data collected from these tests are often noisy and somewhat non-sinusoidal. This hampers accurate analysis of the data to obtain engineering insight. The goal of the work presented in this paper is to develop and compare automated evolutionary computational techniques to filter test noise in the collection of data for the HMA complex modulus test. The results showed that the Covariance Matrix Adaptation-Evolutionary Strategy (CMA-ES) approach is computationally efficient for filtering data obtained from the HMA complex modulus test.

Keywords: HMA, dynamic modulus, GA, evolutionarycomputation.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1330257

References:

[1] T. Harman, "Using the Dynamic Modulus Test to Assess the Mix Strength of HMA," Public Roads 64 (6), 2001
[2] NCHRP, "Guide for Mechanistic-Empirical Design of New and Rehabilitated Pavement Structures," NCHRP Project 1-37A, Transportation Research Board, Washington, D.C., 2004.
[3] C.E. Dougan, J.E. Stephens, J. Mahoney, and G. Hansen. "E* - Dynamic Modulus. Test Protocol - Problems and Solutions," Report No. CT-SPR- 0003084-F-03-3, Connecticut Department of Transportation, Rocky Hill, Connecticut, 2003.
[4] C.W. Schwartz, "ENCE 447: Pavement Engineering." Unpublished Course Material - Spring 2005, Department of Civil Engineering. University of Maryland, College Park, Maryland, 2005.
[5] NCHRP 1-37, "A Draft Test Method A1. Standard test method for dynamic modulus of asphalt concrete mixtures and master curves," Arizona State University, Tempe, AZ, 2000.
[6] J.S. Daniel, G.R. Chehab, and Y.R. Kim. "Issues Affecting Measurement of the Complex Modulus of Asphalt Concrete," Journal of Materials in Civil Engineering 16(5): 469-476, 2004.
[7] T. Pellinen, "Comparison of analysis techniques to obtain modulus and phase angle from sinusoidal test data," Proc. 6th International RILEM Symposium on Performance Testing and Evaluation of Bituminous Material, PTEBM -03, Zurich, Switzerland, 2003.
[8] R. Levy and S.B. Cohn, "A History of Microwave Filter Research, Design, and Development," IEEE Transactions on Microwave Theory and Techniques, Vol. MIT-32, No. 9, 1984.
[9] D.E. Goldberg, Genetic Algorithms in search, optimization and machine learning, Addison-Wesley, 1989.
[10] K.S. Tang, K.F. Man, S. Kwong and Q. He, "Genetic Algorithms and their applications," IEEE Signal Processing Magazine, 13(6), 1996.
[11] J.H. McClellan and T.W. Parks, "A unified approach to the design of optimum FIR linear-phase digital filters," IEEE Tran. Circuit theory, CT-20: 697-701, 1973.
[12] J.W. Adams and A.N. Jr. Wilson, "A new approach to FIR digital filters with fewer multipliers and reduced sensitivity," IEEE Trans. Circuits and Systems, CAS-30: 277-283, 1983.
[13] J.W. Adams and A.N. Jr. Wilson, "Some efficient digital pre-filter structures," IEEE Tran., CAS-31: 260-265, 1984.
[14] Y. Neuvo, D. Cheng-Yu, and S.K. Mitra, "Interpolated finite impulse response filters," IEEE Trans. Acoustics, Speech, and Signal Processing, ASSP-32: 563-570, 1984.
[15] G. Wade, P. Van-Eetvelt, and H. Darwen, "Synthesis of efficient loworder FIR filters from primitive sections," IEE Proc. G, 137: 70-87, 1984.
[16] D. Suckley, "Genetic algorithm in the design of FIR," IEE Proceedings, Part G: Electronic Circuits & Systems, 138(2): 234-238, 1991.
[17] A. Roberts and G. Wade, "A structured GA for FIR filter design," Proc. workshop on Natural Algorithms in Signal Processing, Vol. 1, Chelmsford, UK, 1993.
[18] X.J. Dexiang and M.L. Delay, "Design of Finite Word Length digital filters using a parallel genetic algorithm," Proc. IEEE Conference, pp. 834-837, 1992.
[19] P. Gentili, F. Piazza, and A. Uncini, "Improved power-of-two sharpening filter design by genetic algorithm," ICASSP, Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing, Vol. 3, Piscataway, NJ, pp. 1375-1377, 1996.
[20] MATLAB. MATLAB® online help. MathWorks, Inc., 2004.
[21] H.P. Schwefel, Evolution and Optimum Seeking, Sixth Generation Computer Technology Series, New York: John Wiley and Sons Inc., 1995.
[22] N. Hansen and A. Ostermeier, "Completely Derandomized Self- Adaptation in Evolution Strategies," Evolutionary Computation, 9(2): 159-195, 2001.
[23] N. Hansen, S. D. M├╝ller, and P. Koumoutsakos, "Reducing the Time Complexity of the Derandomized Evolution Strategy with Covariance Matrix Adaptation (CMA-ES)," Evolutionary Computation, 11(1): 1-18, 2003.