Component-based models are commonly employed to simulate discrete dynamicalsystems. These models lend themselves to formalizing the structures of systems at multiple levels of granularity. Visual development of component-based models serves to simplify the iterative and incremental model specification activities. The Parallel Discrete Events System Specification (DEVS) formalism offers a flexible yet rigorous approach for decomposing a whole model into its components or alternatively, composing a whole model from components. While different concepts, frameworks, and tools offer a variety of visual modeling capabilities, most pose limitations, such as visualizing multiple model hierarchies at any level with arbitrary depths. The visual and persistent layout of any number of hierarchy levels of models can be maintained and navigated seamlessly. Persistence storage is another capability needed for the modeling, simulating, verifying, and validating lifecycle. These are important features to improve the demanding task of creating and changing modular, hierarchical simulation models. This thesis proposes a new approach and develops a tool for the visual development of models. This tool supports storing and reconstructing graphical models using a NoSQL database. It offers unique capabilities important for developing increasingly larger and more complex models essential for analyzing, designing, and building Digital Twins.

Water, energy, and food are essential resources to sustain the development of the society. The Food-Energy-Water Nexus (FEW-Nexus) must account for synergies and trade-offs among these resources. The nexus concept highlights the importance of integrative solutions that secure supplies to meet demands sustainably. The existing frameworks and tools do not focus on formal model composability, a key capability for creating simulations created from separately developed models. The Knowledge Interchange Broker (KIB) approach is used to model the interactions among models to achieve composition flexibility for the FEW-Nexus.Domain experts generally use the Water Evaluation and Planning (WEAP) and Low Emissions Analysis Platform (LEAP) systems to study water and energy systems, respectively. The food part of FEW systems can be modeled inside the WEAP system. An internal linkage mechanism is available for combining and simulating WEAP and LEAP models. This mechanism is used for the validation and performance evaluation of independent modeling and simulation proposed in this research. The Componentized WEAP and LEAP RESTful frameworks are component-based representations for the legacy and closed-source WEAP and LEAP systems. These modularized systems simplify their use with other simulation frameworks. This research proposes two interaction model frameworks based on the Knowledge Interchange Broker approach. First, an Algorithmic Interaction Model (Algorithmic-IM) was developed to integrate the WEAP and LEAP models. The Algorithmic-IM model can be defined via programming language and has a fixed cyclic execution protocol. However, this approach has tightly interwoven the interaction model with its execution and has limited support for flexibly creating model hierarchies. To overcome these restrictions, the system-theoretic Parallel DEVS formalism is used to develop a DEVS-Based Interaction Model (DEVS-IM). As in the Algorithmic-IM, the DEVS-IM is implemented as a RESTful framework, uses MongoDB for defining structural DEVS models, and supports automatic code generation for the DEVSSuite simulator. The DEVS-IM offers modular, hierarchical structural modeling, reusability, flexibility, and maintainability for integrating disparate systems. The Phoenix Active Management Area (AMA) is used to demonstrate the real-world application of the proposed research. Furthermore, the correctness and performance of the presented frameworks in this research are evaluated using the Phoenix-AMA model.

The concept of multi-scale, heterogeneous modeling is well-known to be central in the complexities of natural and built systems. Therefore, whole models that have parts with different spatiotemporal scales are preferred to those specified using a monolithic modeling approach and tightly integrated. To build simulation frameworks that are expressive and flexible, model composability is crucial where a whole model's structure and behavior traits must be concisely specified according to those of its parts and their interactions. To undertake the spatiotemporal model composability, a breast cancer cells chemotaxis exemplar is used. In breast cancer biology, the receptors CXCR4+ and CXCR7+ and the secreting CXCL12+ cells are implicated in spreading normal and malignant cells. As discrete entities, these can be modeled using Agent-Based Modeling (ABM). The receptors and ligand bindings with chemokine diffusion regulate the cells' movement gradient. These continuous processes can be modeled as Ordinary Differential Equations (ODE) and Partial Differential Equations (PDE). A customized, text-based BrSimulator exists to model and simulate this kind of breast cancer phenomenon. To build a multi-scale, spatiotemporal simulation framework supporting model composability, this research proposes using composable cellular automata (CCA) modeling. Toward this goal, the Cellular Automata DEVS (CA-DEVS) model is used, and the novel Composable Cellular Automata DEVS (CCA-DEVS) modeling is proposed. The DEVS-Suite simulator is extended to support CA and CCA Parallel DEVS models. This simulator introduces new capabilities for controlled and modular run-time animation and superdense time trajectory visualization. Furthermore, this research proposes using the Knowledge Interchange Broker (KIB) approach to model and simulate the interactions between separate geo-referenced CCA models developed using the DEVS and Modelica modeling languages. To demonstrate the proposed model composability approach and its use in the extended DEVS-Suite simulator, the breast cancer cells chemotaxis and others have been studied. The BrSimulator is used as a proxy for evaluating the proposed model composability approach using an integrated DEVS-Suite and OpenModelica simulator. Simulation experiments are developed that show the composition of spatiotemporal ABM, ODE, and PDE models reproduce the behaviors of the same model developed in the BrSimulator.

Cyber-Physical Systems (CPS) are becoming increasingly prevalent around the world. Co-simulation of cyber and physical components has shown to be an effective way towards the development of time-sensitive and reliable CPS. Correctly combining continuous models with discrete models for co-simulation can often be challenging. In this thesis, the Functional Markup Interface (FMI) is used to develop an adapter called DEVS-FMI for the DEVS-Suite simulator. The adapter, implemented using JavaFMI 2.0, allows any Functional Mock-Up Unit (FMU) to be co-simulated with a Discrete Event System Specification (DEVS) model. This approach enables taking advantage of the parallel DEVS formalism to model cyber systems and using Modelica to model physical systems. An FMU serves as a slave simulator while the DEVS-Suite serves as a master simulator. The Four-Variable model is used as a guide to define the requirements for the inputs and outputs of actuator and sensor devices used in cyber and physical systems. The input and output data as non-functional abstractions of the sensor and actuator devices. Select cyber and physical parts of an electric scooter are chosen, modeled, simulated, and evaluated using the integrated OpenModelica and the DEVS-Suite simulators. Closely related research is briefly examined and expanding this work with support for implicit state-changes for continuous models and distributed co-simulation is noted.