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Michael T. Todinov

Michael T. TodinovProf. Todinov’s background is Engineering, Mathematics and Computer Science. He holds a PhD and a higher doctorate (DEng) from the University of Birmingham. His name is associated with key results in the areas: Reliability and Risk, Flow networks, Prbability, Statistics of inhomogeneous media, Theory of phase transformations, Residual stresses and Probabilistic fatigue and fracture.M.Todinov pioneered research on: the theory of repairable flow networks and networks with disturbed flows, risk-based reliability analysis - driven by the cost of system failure, fracture initiated by flaws in components with complex shape, reliability dependent on the relative configurations of random variables and optimal allocation of a fixed budget to achieve a maximal risk reduction.A sample of M.Todinov’s results include: introducing the hazard stress function for modelling the probability of failure of materials and deriving the correct alternative of the Weibull model; stating a theorem regarding the exact upper bound of properties from multiple sources and a theorem regarding variance of a distribution mixture; the formulation and proof of the necessary and sufficient conditions of the Palmgren-Miner rule and Scheil’s additivity rule; deriving the correct alternative of the Johnson-Mehl-Avrami-Kolmogorov equation and stating the dual network theorems for static flows networks and networks with disturbed flows. Read More Read Less

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Risk and Uncertainty Reduction by Using Algebraic Inequalities33 %
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Reverse Engineering of Algebraic Inequalities34 %
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Risk and Uncertainty Reduction by Using Algebraic Inequalities48 %
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Risk-Based Reliability Analysis and Generic Principles for Risk Reduction45 %
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Flow Networks
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01 Feb 2013
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Flow Networks22 % NR
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14 May 2014
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Designing Out Failure
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Designing Out Failure
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Designing Out Failure
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Reverse Engineering of Algebraic Inequalities
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Reverse Engineering of Algebraic Inequalities
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Interpretation of Algebraic Inequalities29 %
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Interpretation of Algebraic Inequalities
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Interpretation of Algebraic Inequalities33 %
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Interpretation of Algebraic Inequalities
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Risk and Uncertainty Reduction by Using Algebraic Inequalities
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Risk and Uncertainty Reduction by Using Algebraic Inequalities
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Risk and Uncertainty Reduction by Using Algebraic Inequalities
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Risk-Based Reliability Analysis and Generic Principles for Risk Reduction
Publisher: Elsevier Science
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01 Jan 2006
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Flow NetworksNR
Publisher: Elsevier
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