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Context: It is thought likely that vast numbers of nanoflares are responsiblefor the corona having a temperature of millions of degrees. Currentobservational technologies lack the resolving power to confirm the nanoflarehypothesis. An alternative approach is to construct a magnetohydrodynamiccoronal loop model that has the ability to predict nanoflare energydistributions.  Aims: This paper presents the initial results generated by such a model. Itpredicts heating events with a range of sizes, depending on where theinstability threshold for linear kink modes is encountered. The aims are tocalculate the distribution of event energies and to investigate whether kinkinstability can be predicted from a single parameter.  Methods: The loop is represented as a straight line-tied cylinder. Thetwisting caused by random photospheric motions is captured by two parameters,representing the ratio of current density to field strength for specificregions of the loop. Dissipation of the loop's magnetic energy begins duringthe nonlinear stage of the instability, which develops as a consequence ofcurrent sheet reconnection. After flaring, the loop evolves to the state oflowest energy where, in accordance with relaxation theory, the ratio of currentto field is constant throughout the loop and helicity is conserved.  Results: The results suggest that instability cannot be predicted by anysimple twist-derived property reaching a critical value. The model is appliedsuch that the loop undergoes repeated episodes of instability followed byenergy-releasing relaxation. Hence, an energy distribution of the nanoflaresproduced is collated.  Conclusions: The final energy distribution features two nanoflare populationsthat follow different power laws. The power law index for the higher energypopulation is more than sufficient for coronal heating.

A Nanoflare Distribution Generated by Repeated Relaxations Triggered by Kink Instability