The Perturbation-Persistence-Reconfiguration Framework (PPRF)

This manuscript proposes the Perturbation-Persistence-Reconfiguration Framework(PPRF), a general, domain-adaptable architecture for analyzing how systems respond toperturbations, retain or lose the effects of prior interactions, recover after perturbationremoval, and undergo persistent state changes or structural reconfiguration. The frame-work separates instantaneous response, cumulative exposure, history-dependent memory,recovery dynamics, structural change, and regime transition rather than treating these phe-nomena as interchangeable. Its formal foundation is a state-space representation whosestate, memory, configuration, inputs, outputs, model parameters, contextual variables, anduncertainty terms are explicitly distinguished. Operational measures are introduced forreference-relative perturbation, normalized cumulative exposure, memory-weighted exposure,structural distance, persistence, and recovery. A conditional transition boundary is permittedonly when the corresponding model and evidence support it. The framework is organized intotwelve theoretical layers, seven candidate mechanisms, six outcome classes, eight proposedvalidation domains, and a twenty-two-stage research workflow. Repeated-Load ResidualReconfiguration (RLRR) is specified as the canonical primary case for developing and testingthe framework. Six falsifiable propositions, model-comparison requirements, uncertaintycontrols, and cross-domain validation criteria are stated. The manuscript is a theoreticaland methodological proposal, not a report of completed empirical validation. It does notclaim that one equation, threshold, timescale, or mechanism applies to every system. Itscentral contribution is a proposed common analytical architecture in which domain-specificmechanisms can be formally specified, empirically evaluated, compared, and rejected whenthe evidence does not support them.