This formula is widely used in neutron diffusion or neutron transport codes. It must be noted the reactivity can also be calculated according to another formula. The reactivity may be used as a measure of a reactor’s relative departure from criticality. The larger the absolute reactivity value in the reactor core, the further the reactor is from criticality. For critical conditions, the reactivity is equal to zero. The reactivity describes the deviation of an effective multiplication factor from unity. A – a supercritical state B – a critical state C – a subcritical stateįrom this equation, it may be seen that ρ may be positive, zero, or negative. The reactivity ( ρ or ΔK/K) is defined in terms of k eff by the following equation: But sometimes, it is convenient to define the change in the k eff alone, the change in the state, from the criticality point of view.įor these purposes, reactor physics uses a term called reactivity rather than k eff to describe the change in the state of the reactor core. The effective multiplication factor – k eff is a measure of the change in the fission neutron population from one neutron generation to the subsequent generation. In the preceding chapters, the classification of states of a reactor according to the effective multiplication factor – k eff was introduced. It is a very substantial amount of reactivity because if the core’s reactivity is one dollar, the reactor is prompt critical. For reactor core with β eff = 0.006 (0.6%), one dollar is equal to about 600 pcm. The most common units for power reactors are units of pcm or %ΔK/K. Mathematically, reactivity is a dimensionless number, but various units can express it. 38, W138-W143 (2010).The reactivity describes the deviation of an effective multiplication factor from unity. PathPred: an enzyme-catalyzed metabolic pathway prediction server. Moriya, Y., Shigemizu, D., Hattori, M., Tokimatsu, T., Kotera, M., Goto, S., and Kanehisa, M.Systematic analysis of enzyme-catalyzed reaction patterns and prediction of microbial biodegradation pathways. Oh, M., Yamada, T., Hattori, M., Goto, S., and Kanehisa, M.E-zyme: predicting potential EC numbers from the chemical transformation pattern of substrate-product pairs. Yamanishi, Y., Hattori, M., Kotera, M., Goto, S., and Kanehisa, M.Modular architecture of metabolic pathways revealed by conserved sequences of reactions. Muto, A., Kotera, M., Tokimatsu, T., Nakagawa, Z., Goto, S., and Kanehisa, M. Computational assignment of the EC numbers for genomic-scale analysis of enzymatic reactions. Kotera, M., Okuno, Y., Hattori, M., Goto, S., and Kanehisa, M.Development of a chemical structure comparison method for integrated analysis of chemical and genomic information in the metabolic pathways. Hattori, M., Okuno, Y., Goto, S., and Kanehisa, M.PathPred: prediction of biodegradation/biosynthetic pathways.E-zyme: automatic assignment of EC numbersįurthermore, based on the observation that specific RDM patterns are uniquely or preferentially found in specific categories of KEGG metabolic pathways, the following tool was developed for predicting metabolic fate of a given chemical compound.The RDM patterns are the basis for predicting reaction types given a pair (or pairs) of chemical compound structures as implemented in the following tool. PathSearch: search for similar reaction pathways.For any sequence of reactions or reaction classes, the following tools may be used to search similar reaction sequences.
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