Emergent technologies and threats prompt for more robust, nimble, adaptable, and stakeholder-friendly modeling and simulation (M&S) systems-engineering support of simulation-based training and experimentation in the US military. Arbitrary architectural paradigms, inconsistent interoperability protocols and database formats, and proprietary restrictions, among other reasons have given way to models and simulation systems incapable of being reused or used across multidisciplinary domains or communities of interest―severely hampering their return on investment. To be responsive and serve as a unifying and widely-accepted transdisciplinary discipline, the M&S community must provide coherent M&S know-how, leadership, and guidance grounded in tried-and-true science and engineering formalisms that garner multidisciplinary acceptance. We conducted a feasibility study to explore the specification of Reusable Modeling Primitives (RMPs) building on Dimensional Analysis (DA), Design Structure Matrix (DSM) for Complexity Management, and Bond/Causal Graph formal methods. The RMP paradigm underlies a Dimensional Analysis Conceptual Modeling (DACM) framework, conducive to objective specification of model elements and interdependencies. It conduces to methodical reverse engineering, restructure, and reengineering (RE3) processes to facilitate, respectively, harvesting codified simuland referents from legacy models, packaging referent information into configurable DA-based primitives amenable to objective fidelity specifications, and conceptual modeling for alternative intended uses leveraging RMPs. DACM facilitates the contextual decomposition of problem spaces mapped to corresponding solution spaces captured in “finger print� DSM matrixes that facilitate the enumeration of required codified simuland referent components―which facilitate validation of problem spaces and of corresponding fidelity requirement specifications underlying M&S solutions. DSM specification matrixes can help reveal not only problem space knowledge gaps but also which knowledge gaps may be resolved with simulation-based analytics and which require further empirical measures―enabling program managers to target their limited research resources. We present the progression and non-trivial realities of model reuse from a demonstration exemplar involving conversion of a rudimentary ship legacy model to a corresponding torpedo alternative model.