Publications

Journal Articles

• ConstraintHg: A Kernel for Systems Modeling and Simulation

  John Morris
  Jan 2026 | Journal of Open-Source Software
  

  ConstraintHg is a systems modeling kernel used for parsing constraint hypergraphs. Constraint hypergraphs are a mathematical formalism embodying the constraint-based approach to representing behavior. Any executable model--whether database schema, plant controller, or ecological forecaster--can be represented as a constraint hypergraph. Once combined, the unified structure shows how all elements in the system are related to each other. In addition to representing constraint hypergraphs, ConstraintHg provides methods for traversing them, equivalent to simulating the system. While most system simulations must be imperatively defined, ConstraintHg enables simulations to be constructed declaratively. As a result, knowledge about a system can be discovered autonomously, transforming a general system representation into an agentic information provider.
  

      @article{morrisConstraintHgJOSS,
      title = {{{ConstraintHg}}: {{A Kernel}} for {{Systems Modeling}} and {{Simulation}}},
      author = {Morris, John},
      date = {2026-01-19},
      journaltitle = {Journal of Open-Source Software},
      volume = {11},
      number = {117},
      pages = {9131},
      publisher = {Open Journals},
      issn = {2475-9066},
      doi = {10.21105/joss.09131},
      }
      
  

  
  

• Effects of Functional and Declarative Modeling Frameworks on System Simulation

  John Morris, Gregory Mocko, John Wagner
  Jan 2026 | Journal of Dynamic Systems, Measurement, and Control
  

  System modeling frameworks can be categorized into imperative and declarative paradigms. Which paradigm a model is expressed in effects how the model may be utilized; imperative models allow simple execution, while declarative models capture the behavior of the underlying system. This paper compares these paradigms, as well as functional and object-oriented frameworks, in light of physics-based systems. This is done by exploring the principles of systems modeling and simulation. Simulation is shown to be the composition of functions representing system behavior. Simulatable frameworks can be differentiated by their ability to identify and compose these functions for a specific input and output pairing. The various frameworks are explored, applying concepts more typically studied in computer science to general systems engineering. The frameworks are investigated by comparing simulations of a driven double pendulum in various modeling languages. Observations include that functional, declarative models allow for greater reusability and holistic system simulation.
  

      @article{morrisEffectsFunctionalDeclarative2026,
      title = {Effects of {{Functional}} and {{Declarative Modeling Frameworks}} on {{System Simulation}}},
      author = {Morris, John and Mocko, Gregory and Wagner, John},
      date = {2026-01},
      journaltitle = {Journal of Dynamic Systems, Measurement, and Control},
      shortjournal = {J. Dyn. Sys., Meas., Control},
      volume = {148},
      number = {4},
      pages = {041012},
      publisher = {ASME},
      doi = {10.1115/1.4070883},
      }
      
  

• Unified System Modeling and Simulation via Constraint Hypergraphs

  John Morris, Gregory Mocko, John Wagner
  Apr 2025 | Journal of Computing and Information Science in Engineering
  

  This paper describes the theory behind constraint hypergraphs: a novel modeling framework that can be used to universally represent and simulate complex systems. Multi-domain system models are traditionally compiled from many diverse frameworks, each based in a single domain. Incompatibilities between these frameworks prevent information from being shared resulting in data silos, duplicate work, and knowledge gaps. A constraint hypergraph addresses these problems by providing a universal modeling framework within which all model prescriptions can be expressed. This methodology expands mathematical structures previously explored in abstract mathematics and systems theory into a new executable framework. Each hypergraph expresses the holistic behavior of a system in a declarative paradigm that describes the relationships between system properties. In addition to modeling, it is shown how constraint hypergraphs can be used for universal, cross-cutting simulation through principles of function composition. The theoretical framework of a constraint hypergraph is demonstrated with a practical representation of a hybrid system, combining a discrete-event simulation and continuous PID controller into a single model of an elevator lift system.
  

      @article{morrisUnifiedSystemModeling2025,
      title = {Unified {{System Modeling}} and {{Simulation}} via {{Constraint Hypergraphs}}},
      author = {Morris, John and Mocko, Gregory and Wagner, John},
      date = {2025-04-04},
      journaltitle = {Journal of Computing and Information Science in Engineering},
      shortjournal = {J. Comput. Inf. Sci. Eng.},
      volume = {25},
      number = {6},
      pages = {061005},
      doi = {10.1115/1.4068375},
      langid = {english},
      Special Issue on Networks and Graphs for Engineering Systems and Design}
      }
  

  
  

  
  

Submitted Journal Articles

• Declarative, Multi-physics Simulation Between Applications via Constraint Hypergraphs

  John Morris, Abhishek Indupally, Satchit Ramnath, Gregory Mocko, John Wagner
  Oct 2025 | Under review with J. Comput. Inf. Sci. Eng.
  

  To avoid the blind spots and brittleness of imperatively simulating a physical system, modelers often turn to declarative methods that can autonomously execute a model. Such solvers rely on a model structure that allows procedures for transforming inputs to outputs to be automatically discovered. However, the model structures used for traditional declarative solvers are insular, in that they are often isolated to specific modeling domain. Furthermore, these specific model types are unable to be understood by the advanced computing applications required to simulate complex systems. Here we provide a general purpose modeling framework that can integrate software functionalities into the declarative simulation of a model, offering for the first time the ability to define a multi-physics, multi-scale system independent of its eventual simulation. This is accomplished by representing a system as a constraint hypergraph. System models are deconstructed into state variables and relationships in the graph. The APIs of external tools are integrated into the model as inter-variable functions. By encoding these functionalities in the graph, a solver is able to autonomously arrange these relations into executable simulation processes, enabling fully declarative simulation. This is demonstrated by integrating the capabilities of three software platforms together into a single model of a crankshaft from a piston engine: solid geometry (Onshape), structural mechanics (Ansys Mechanical), and kinematic analysis (MATLAB). The result is a holistic modeling framework that allows for flexible simulation of a complex system, integrates directly with otherwise sequestered platforms, and reveals cross-cutting interactions between system elements.
  

      @article{morrisDeclarativeIntegrationEngineering2025,
      title = {Declarative, {{Multi-physics Simulation Between Applications}} via {{Constraint Hypergraphs}}},
      author = {Morris, John and Indupally, Abhishek and Ramnath, Satchit and Mocko, Gregory and Wagner, John},
      date = {2025-10},
      journaltitle = {Under review with J. Comput. Inf. Sci. Eng.},
      publisher = {ASME},
      }
      
  

  
  

• Constraint Hypergraphs as a Unifying Framework for Digital Twins

  John Morris, Edward Louis, Douglas L. Van Bossuyt, Gregory Mocko, John Wagner
  Jul 2025 | Under review with Systems Journal
  

  Digital twins, used to represent physical systems, have been lauded as tools for understanding reality. Complex system behavior is typically captured in domain-specific models crafted by subject experts. Contemporary methods for employing models in a digital twin require prescriptive interfaces, resulting in twins that are difficult to connect, redeploy, and modify. The limited interoperability of these twins has prompted calls for a universal framework enabling observability across model aggregations. Here we show how a new mathematical formalism called a constraint hypergraph serves as such a framework by representing system behavior as the composition of set-based functions. A digital twin is shown to be the second of two coupled systems where both adhere to the same constraint hypergraph, permitting the properties of the first to be observable from the second. Interoperability is given by deconstructing models into a structure enabling autonomous, white-box simulation of system properties. The resulting digital twins can interact immediately with both human and autonomous agents. This is demonstrated in a case study of a microgrid, showing how both measured and simulated data from the aggregated twins can be provided regardless of the operating environment. By connecting models, constraint hypergraphs supply scientists and modelers robust means to capture, communicate, and combine digital twins across all fields of study. We expect this framework to expand the use of digital twins, enriching scientific insights and collaborations by providing a structure for characterizing complex systems.
  

      @article{morrisConstraintHypergraphsUnifying2025,
      title = {Constraint {{Hypergraphs}} as a {{Unifying Framework}} for {{Digital Twins}}},
      author = {Morris, John and Louis, Edward and Van Bossuyt, Douglas L. and Mocko, Gregory and Wagner, John},
      date = {2025-07},
      journaltitle = {Under review with Systems Journal},
      publisher = {IEEE},
      doi = {10.48550/arXiv.2507.05494},
      langid = {english},
      https://doi.org/10.48550/arXiv.2507.05494}
      }
      
  

  
  

Conference Articles

• From Knowledge Graphs to Constraint Hypergraphs

  Joe Gregory, John Morris
  Jun 2026 | IS 2026
  

  As systems engineering increasingly depends on digital models and integrated data environments, the graph representation of engineering knowledge has become a key enabler of semantic consistency, traceability, and automation. To implement this, we may use ontology languages such as the Web Ontology Language (OWL2DL) and the Ontological Modeling Language (OML) to define the concepts and relations within our domain, and then use logical reasoners to infer new information and detect inconsistent, incomplete or incorrect information. However, a limitation of purely logical representations is their inability to perform mathematical reasoning. Logical inference can identify missing or inconsistent facts, but it cannot compute or optimize quantitative parameters that drive engineering analyses. This paper presents the development of an approach that bridges this gap by generating solvable constraint hypergraphs (CHGs) in an executable format from knowledge graphs (KGs) that capture systems engineering knowledge. Ontologies provide the formal semantics of the relevant domains, while data instances populate those models with project-specific information. From this structured knowledge, mathematical relations among parameters are automatically identified and transformed into a CHG representation in which nodes represent quantities and hyperedges represent the mathematical relations between them. In this paper, we describe an end-to-end workflow from ontological modeling and data integration to constraint extraction and solution, and we demonstrate its application through a spacecraft design example. In this example, a KG describing a spacecraft and its environment is used to automatically generate the mathematical relations that describe power, mass, and communication performance. The resulting constraint hypergraph is then solved to derive consistent parameter values across the system model. By translating logical relations into executable constraint structures, this approach enables automated numerical reasoning without compromising semantic rigor. It reduces the risk of inconsistencies when defining equations manually and strengthens the integration between logical and analytical representations within digital engineering enviroinments.
  

      @inproceedings{gregoryIS2026_paper_3922026,
      title = {From {{Knowledge Graphs}} to {{Constraint Hypergraphs}}},
      booktitle = {36th {{Annual INCOSE International Symposium}}},
      author = {Gregory, Joe and Morris, John},
      date = {2026-06-13},
      publisher = {INCOSE},
      eventtitle = {{{IS}} 2026},
      venue = {Yokohoma, Japan},
      }
      
  

• Technical Strategies for Semantic Aggregation of Interoperable Digital Twins

  John Morris, Duncan Gibbons, Joe Gregory, Gregory Mocko
  Apr 2026 | CSER26
  

  Digital twin aggregates are a synchronized representation of a real system formed by the composition of multiple subsystem models. When formed in an interoperable manner, the integrated models should reveal the emergent behavior of the greater system. The ability to combine independently developed digital twins is a critical aspect of democratized modeling, however, no methods currently enable universal aggregation. In this paper, we propose a two-pronged approach to solving model interoperability that addresses both behavioral and interpretive aspects of describing supersystems. The first prong employs a constraint hypergraph to capture the relationships between system information; we show that these hypergraphs can be autonomously extended given the satisfaction of certain properties. Extended relationships between the joined hypergraphs reveal emergent behaviors, while non-modeled phenomena are contraindicated. The interpretation of the twin aggregate is given descriptively using SysML, which uses external frames of reference to contextualize the system properties. Limitations include having to trade generality in representing the specific aggregated system. Exploring strategies such as these permit models to be connected autonomously even without a prespecified context, allowing modeling experts to focus on specific subdomains of a problem with guaranteed model compatibility.
  

      @inproceedings{morrisInteroperabilityCSER2026,
      title = {Technical {{Strategies}} for {{Semantic Aggregation}} of {{Interoperable Digital Twins}}},
      booktitle = {Conference on {{Systems Engineering Research}}},
      author = {Morris, John and Gibbons, Duncan and Gregory, Joe and Mocko, Gregory},
      date = {2026-04-06},
      publisher = {INCOSE},
      eventtitle = {{{CSER26}}},
      venue = {Arlington, VA, USA},
      }
      
  

  
  

  
  

• Effects of Functional and Declarative Modeling Frameworks on System Simulation

  John Morris, Gregory Mocko, John Wagner
  Oct 2025 | The 5th Modeling, Estimation and Control Conference (MECC 2025)
  

  System modeling frameworks can be categorized into imperative and declarative paradigms. Which paradigm a model is expressed in effects how the model may be utilized; imperative models allow simple execution, while declarative models capture the behavior of the underlying system. This paper compares these paradigms, as well as functional and object-oriented frameworks, in light of physics-based systems. This is done by exploring the principles of systems modeling and simulation. Simulation is shown to be the composition of functions representing system behavior. Simulatable frameworks can be differentiated by their ability to identify and compose these functions for a specific input and output pairing. The various frameworks are explored, applying concepts more typically studied in computer science to general systems engineering. The frameworks are investigated by comparing simulations of a driven double pendulum in various modeling languages. Observations include that functional, declarative models allow for greater reusability and holistic system simulation.
  

      @inproceedings{morrisEffectsFunctionalDeclarative2025,
      title = {Effects of {{Functional}} and {{Declarative Modeling Frameworks}} on {{System Simulation}}},
      author = {Morris, John and Mocko, Gregory and Wagner, John},
      date = {2025-10-07},
      publisher = {IFAC},
      location = {Pittsburgh, PA},
      eventtitle = {The 5th {{Modeling}}, {{Estimation}} and {{Control Conference}} ({{MECC}} 2025)},
      }
      
  

  
  

  
  

• Declarative Integration of CAD Software into Multi-Physics Simulation via Constraint Hypergraphs

  John Morris, Gregory Mocko, John Wagner, Satchit Ramnath
  Aug 2025 | ASME IDETC-CIE 2025
  

  Declarative modeling frameworks, such as Modelica, are often used to represent systems that require reusable and interoperable models. Simulation in such a framework requires a solver that is capable of transforming the model into an executable process. However, most declarative solvers are insular, in that they are unable to integrate with software applications needed for simulating complex systems, limiting their usability for simulating multi-domain models. This paper describes a process for creating declarative models that can integrate with an external tool by deconstructing its Application Programmer Interface (API) into a set of functions arranged into a constraint hypergraph. The constraint hypergraph's solver is shown to be capable of automatically parsing these functions to simulate arbitrary pairs of inputs and outputs. The result is a holistic modeling framework that allows for flexible simulation of a complex system, integrates directly with otherwise sequestered platforms, and reveals cross-cutting interactions between system elements. This is demonstrated by integrating the solid modeling capabilities of Onshape with a dynamic model of a crankshaft from a piston engine, showing how a geometric model can be integrated with independently-defined dynamic models. This validates the framework on a limited scale, setting the foundation for work for fully integrating disparate tools into multi-domain, multi-physics modeling and simulation.
  

      @inproceedings{morrisDeclarativeIntegrationCAD2025,
      title = {Declarative {{Integration}} of {{CAD Software}} into {{Multi-Physics Simulation}} via {{Constraint Hypergraphs}}},
      booktitle = {Proceedings of the {{ASME}} 2025 {{International Design Engineering Technical Conferences}} and {{Computers}} and {{Information}} in {{Engineering Conference}}},
      author = {Morris, John and Mocko, Gregory and Wagner, John and Ramnath, Satchit},
      date = {2025-08-17/2025-08-20},
      volume = {2A: 45th Computers and Information in Engineering Conference (CIE)},
      publisher = {ASME},
      doi = {10.1115/DETC2025-168376},
      eventtitle = {{{ASME IDETC-CIE}} 2025},
      isbn = {978-0-7918-8920-6},
      venue = {Anaheim, CA},
      }
      
  

  
  

  
  

  
  

Presentations

• Unified System Modeling and Simulation via Constraint Hypergraphs

  Apr 2026 | JMD-JCISE Joint Webinar: Networks and Graphs for Engineering Systems Design
  

      @unpublished{morrisASMEJMDJCISEwebinar2026,
      type = {Invited Presentation},
      title = {Unified {{System Modeling}} and {{Simulation}} via {{Constraint Hypergraphs}}},
      author = {Morris, John},
      date = {2026-04-17},
      journaltitle = {Networks and Graphs for Engineering Systems Design},
      series = {{{JMD-JCISE}} Webinar},
      url = {https://youtu.be/Nw68gA9lMt8?si=oXKHY1GGOyANV8RE&t=4025},
      eventtitle = {{{JMD-JCISE Joint Webinar}}: {{Networks}} and {{Graphs}} for {{Engineering Systems Design}}},
      venue = {ASME},
      }
      
  

  
  

  
  

• Strategies for Aggregating Digital Twins

  Apr 2026 | Conference on Systems Engineering Research 2026
  

      @unpublished{morrisCSER26Presentation2026,
      type = {Conference},
      title = {Strategies for {{Aggregating Digital Twins}}},
      author = {Morris, John},
      date = {2026-04-08},
      journaltitle = {Digital Twins},
      eventtitle = {Conference on {{Systems Engineering Research}} 2026},
      venue = {Fairfax, VA, USA},
      }
      
  

  
  

• Universal System Simulation via Hypergraphs  Graduate Travel Grant Awardee 

  Jun 2025 | Applied Category Theory Conference (ACT 2025)
  

      @unpublished{morrisACT2025,
      title = {Universal {{System Simulation}} via {{Hypergraphs}}},
      author = {Morris, John},
      date = {2025-06-02},
      eventtitle = {Applied {{Category Theory Conference}} ({{ACT}} 2025)},
      venue = {Gainesville, FL},
      }
      
  

  
  

  
  

• Representing Digital Twins  Buzz Award Finalist 

  Aug 2024 | ASME IDETC-CIE: SciTechBuzz Summit 2024
  

      @unpublished{morrisRepresentingDigitalTwins2024,
      title = {Representing {{Digital Twins}}},
      author = {Morris, John},
      date = {2024-08-26},
      eventtitle = {{{ASME IDETC-CIE}}: {{SciTechBuzz Summit}} 2024},
      venue = {Washington DC},
      }
      
  

  
  

Reports and Theses

• Universal Systems Simulation via Constraint Hypergraphs with Applications to Digital Twins

  John Morris
  Dec 2025 | Clemson University
  

  The characterization of systems encompasses a variety of modeling frameworks designed to capture specific behaviors and components of various system domains. Whatever the framework, the core elements of a system representation are the information of the system and a description of how that information is related. The relations in deterministic systems are functions, which, when composed to form executable processes, can be used to simulate system data. A declarative modeling framework is one that encodes mechanisms for preparing these simulations within the model structure, allowing an external agent to form the execution processes required for a given context. To date, no declarative modeling framework has been proposed that allows for these processes to be discovered for any system across any domain. In this dissertation, a new framework called a constraint hypergraph is proposed that provides universal, declarative modeling. System behavior is embedded in this framework as paths through the hypergraph. Simulating a system represented with a constraint hypergraph can be accomplished by an autonomous agent capable of discovering these paths. This, combined with the graphical nature of the framework, allows system information to be interrogated autonomously across domains, enabling multiphysics, multiscale modeling and simulation of complex systems. Applications of this framework are shown to model-based engineering platforms and digital twins. The former is given by showing how updatable digital threads can be traced throughout a data ecosystem, including across analysis software platforms such as CAD and FEA tools. Constraint hypergraphs are also shown to provide a robust foundation for creating digital twins, leading to twins that are usable, interoperable, maintainable, and verifiable. These applications are demonstrated using custom algorithms published in the open-source package ConstraintHg.
  

      @thesis{morrisDissertation,
      type = {phdthesis},
      title = {Universal {{Systems Simulation}} via {{Constraint Hypergraphs}} with {{Applications}} to {{Digital Twins}}},
      author = {Morris, John},
      date = {2025-12-12},
      series = {All {{Dissertations}}},
      number = {4127},
      institution = {Clemson University},
      location = {Clemson, SC, USA},
      url = {https://open.clemson.edu/all_dissertations/4127},
      urldate = {2026-01-20},
      }
      
  

  
  

  
  

  
  

Tools

• MicrogridHg

  May 2025 | Clemson, Naval Postgraduate School
  

  This model describes the behavior of a microgrid, formalized in a constraint hypergraph. Flexible for various configurations, the microgrid is universally simulatable, allowing a modeler to simulate any piece of the model by a single call. The default configuration of the microgrid consists of 12 actors of 5 different types: batteries (2), buildings (5), generators (2), photovoltaic arrays (1), all connected to each other and the greater utility grid along 2 busses. Different configurations are also possible, allowing for quick descriptions of microgrid behavior.
  

      @software{morrisMicrogridHg2025,
      title = {{{MicrogridHg}}},
      author = {Morris, John},
      namea = {Van Bossuyt, Douglas L.},
      nameatype = {collaborator},
      date = {2025-05-16},
      doi = {10.5281/zenodo.15447062},
      organization = {Clemson, Naval Postgraduate School},
      version = {v1.0},
      }
      
  

• ConstraintHg

  Nov 2024 |
  

  Python package providing a kernel for model-based engineering with constraint hypergraphs.
  

      @software{morrisConstraintHg2024,
      title = {{{ConstraintHg}}},
      author = {Morris, John},
      date = {2024-11-23},
      doi = {10.5281/zenodo.15278018},
      version = {0.2.2},
      }