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Quasi-Static Failure Criteria for Concrete / Quasi-Statyczne Kryteria Zniszczenia Betonu

Abstract

The behaviour of concrete under quasi-static loadings for uniaxial compression, tension and plane stress conditions is studied. The failure criteria of concrete are discussed as well as the methods of constitutive parameters identification are elaborated. The attention is focus on an energetic interpretation of selected failure criteria. The numerical example with concrete damage plasticity material model is shown

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Modal Parameter Identification Of Cable Stayed Bridge Based On Exploratory Data Analysis

R eferences 1. I.U. Khan, D.S. Shan, and A.Q. Bhatti, “Temperature Effect Analysis of Viscoelastic Damper and Magnetorheological Damper for Vibration Control of Stayed-Cable”, IABMAS2014, Shanghai, China, 2014. 2. I.U. Khan, D.S. Shan, and K. Malik, “Covariance Driven Subspace Identification Technique for Continuous Modal Parameters Identification of Sutong Bridge”, IABSE Madrid Symposium: Engineering for Progress, Nature and People, pp 2666-2673(8), 2014. 3. E.J. Cross, K.Y. Koo, J. Brownjohn, and K. Worden, “Long-term monitoring and data

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A Comparative and Experimental Study on Gradient and Genetic Optimization Algorithms for Parameter Identification of Linear MIMO Models of a Drilling Vessel

, Frequency, and Spatio-temporal Domains , Wiley, Chichester. Bredmose, H., Larsen, S., Matha, D., Rettenmeier, A., Marino, E. and Seattran, L. (2012). Collation of offshore wind-wave dynamics, Technical report , Marine Renewables Infrastructure Network. Chen, W., Yan, K., Shi, G. and Lu, H. (2008). A new swarm intelligence and parameter identification of hydrodynamic forces acting on axis-symmetric body exiting water obliquely, Journal of Ship Mechanics 12 (2): 204–210. Dai, Y., Li, Y. and Song, J. (2012). Parameter identification of ship lateral

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Parameter Identification and Estimation For Stage–Structured Population Models

References Baliarsingh, P. and Dutta, S. (2015). On an explicit formula for inverse of triangular matrices, Journal of the Egyptian Mathematical Society 23 (1): 297–302. Berman, A. and Plemmons, R. (1994). Nonnegative Matrices in the Mathematical Sciences , SIAM, Philadelphia, PA. Boyadjiev, C. and Dimitrova, E. (2005). An iterative method for model parameter identification, Computers and Chemical Engineering 29 (1): 941–948. Cantó, B., Coll, C. and Sánchez, E. (2014). On stability and reachability of perturbed positive systems

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Postural Response Signal Characteristics Identified by Method of Developed Statokinesigram

Abstract

Human postural system is taken as complex biological system with specific input and output time characteristics, in this study. Evaluation of measured output characteristics is useful in medical diagnostics or in describing postural system disorders. System theory principle provide suitable basis for postural signals analysis. Participating volunteers were instructed to maintain quiet upright stance posture on firm support surface of stabilometric platform for 60s. Postural system actuation was realized by vibration stimuli applied bilaterally on Achilles tendons for 20s. Postural reaction signal, its time profile and static and dynamic characteristics were evaluated by Method of Developed Statokinesigram Trajectory (MDST).

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Modeling And Parameter Identification Of Vibrations Of A Double Torsion Pendulum With Friction

Abstract

The purpose of this paper is to investigate a double torsion pendulum with planar frictional contact. The single torsion pendulum with one-degree-of-freedom is an angular equivalent of the linear harmonic oscillator. The second degree of freedom has been obtained by adding a free body to the inverted single torsion pendulum. The free body’s angular displacement is caused by frictional forces appearing in the interface (contact zone) between the free body and the pendulum column’s head kinematically excited at its base by a mechanism with torsion spiral spring. An experimental station has been set up and run to find most unknown parameters of the pendulum from the time series of state variables taken as inputs to the Nelder-Mead method of identification. The obtained results proved significant usability of the identification method in the case of numerical simulation of the pendulum’s dynamical model. It has not been satisfactorily proved in the case of time characteristics coming from a real system that exhibits also some unrecognized physical effects.

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Identification of Nonlinear Cascade Systems with Noninvertible Piecewise Linear Input and Backlash Output Nonlinearities

. DING F. Least Squares Based and Gradient Based Iterative Identification for Wiener Nonlinear Systems Signal Processing 91 2011 1182 1189 [14] ZHOU, L.—LI, X.—PAN, F. : Gradient Based Iterative Parameter Identification for Wiener Nonlinear Systems, Applied Mathematical Modelling 37 (2013), 8203–8209. ZHOU L. LI X. PAN F. Gradient Based Iterative Parameter Identification for Wiener Nonlinear Systems Applied Mathematical Modelling 37 2013 8203 8209 [15] KALAŠ, V.—JURIŠICA, L.—ŽALMAN, M.—ALMÁSSY, S.—SIVIČEK, P

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The Valve Gear Systems Timing Parameters Identification for Marine Diesel Engines Diagnostics / Identyfikacja Parametrów Układów Rozrządu Silników Okrętowych Dla Potrzeb Diagnostyki

Abstract

In the paper results of studies that aim was to develop a diagnostic method for high-speed marine diesel engines are presented. Polish Navy is operating significant number of engines of this type also on board of submarines. Engines of this type do not have indicator valves, which complicates the assessment of combustion process and their technical condition. Polish Naval Academy in Gdynia for years has been developing methods of diagnosing marine internal combustion engines. In recent years, a diagnostic method for high-speed marine diesel engines based on the analysis of envelope of vibration accelerations generated by the valve gear mechanism and fuel system has been developed. Some tests results made on Mercedes-Maybach MB820 engines used on Kobben class submarines are presented in the paper.

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Adaptive Control and Synchronization of Sprott J System With Estimation Of Fully Unknown Parameters

Parameter Identification. Chaos, Soltions and Fractals, 26 (2005), 1163-1169. [20] Sun, M., L. Tian, S. Jiang, J. Xun. Feedback Control and Adaptive Control of the Energy Resource Chaotic System. Chaos, Solitons and Fractals, 32 (2007), 168-180. [21] Astrom, K. J., B. Wittenmark. Adaptive Control, 2nd edition, USA, New Jersey, Prentice Hall, 1994. [22] Pecora, L. M., T. L. Caroll. Synchronization in Chaotic Systems. Phys. Rev. Letters, 64 (1990), 821-824. [23] Feki, M. An Adaptive Chaos Synchronization Scheme

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Residual generator fuzzy identification for automotive diesel engine fault diagnosis

for sensor faults of industrial processes, IEEE Transactions on Control Systems Technology 8 (5): 848-855. Simani, S., Fantuzzi, C. and Patton, R.J. (2003). Modelbased Fault Diagnosis in Dynamic Systems Using Identification Techniques , Advances in Industrial Control, Vol. 1, Springer-Verlag, London. Simani, S., Fantuzzi, C., Rovatti, R. and Beghelli, S. (1999). Parameter identification for piecewise linear fuzzy models in noisy environment, International Journal of Approximate Reasoning 1 (22): 149-167. Stamatis

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