MODELING & SIMULATION

The 18th Modeling and Simulation Subcommittee (MSS) provides an overarching focus on M&S across all disciplines related to JANNAF Interagency simulation-based acquisition of propulsion systems for aerospace plane, hypersonic aircraft, rocket-based space-access systems, high-speed missiles, and in-space propulsion systems, and gun propulsion systems. The MSS pursues this focus through Model-Based Engineering, Integrated Health Management, Simulation Credibility: Verification, Validation, and Risk, and Modeling and Simulation of System Autonomy. At the 18th MSS Meeting, papers are sought to address specifics of these mission areas as described below.

MSS Mission Areas

Areas of interest included in the Call for Papers are:

Mission Area I: Model-Based Engineering

Model-Based Engineering (MBE) encompasses the development of methodologies, codes, and model simulations to quantitatively evaluate and optimize propulsion technologies across propulsion component, propulsion system, and vehicle system levels. The MBE mission area includes the specific discipline of Model-Based System Engineering (MBSE). MBSE is the formalized application of modeling to support system requirements, design, analysis, and verification/validation activities from conceptual design through later life cycle phases. The use of models complements traditional experimentation during technology development with a goal of reducing the development time and schedule. Development and usage of physics-based models allows exploration of domains and behaviors that may be particularly difficult or impossible to examine experimentally. Statistical models provide an estimation of system sensitivities and uncertainties. Publications in the MBE area fall under two topic headings: Modeling Methodologies/Approaches/Tools and System Analysis Results.

Examples of topics of interest for the MBE mission area include the following:
  • Modeling Methods/Approaches
    • Proposed performance/loss models for rotating detonation rocket engines
    • Ignition Modeling
    • Accommodating multidisciplinary modeling at multiple hetergeneous levels of fidelity
    • Engineering decision support, including facilitating optimization, scheduling, and knowledge-based tool integration into the engineering process
    • Advances in the development of models and methods for component modeling and simulations to aid propulsion design
    • Improvements in commercial software which enable advanced MBE
    • Challenges/Boosts to using MBE under a more commercial/less centralized propulsion technology development paradigm and shifts from horizontal to vertical integration in the launch industry
  • System Analysis Results
    • M&S of vehicle system technology trades for space launch systems, prompt strike platforms, long-range ballistic missiles, cruise missiles, and hypersonic cruise vehicles
    • Simulations, methods, and models to evaluate performance capabilities, cost, and reliability of systems
    • Vehicle and launch facility, weapon and weapons platform, propulsion system and test facility simulations, interactions, and integration


Mission Area II: Integrated Health Management

Integrated Health Management (IHM) promotes advancement and development of best practices of health management of propulsion systems within a “system of systems” environment. IHM technologies are focused on reducing maintenance and logistics costs, and increasing reliability of propulsion systems. IHM includes methods and tools for a variety of technologies: data management and mining; integrated communications, command and control; diagnostics; prognostics, and integrated sensors and sensing systems. These tools enable making redline and contingency decisions using knowledge-based expert systems, model-based diagnostic and reasoning using physics-based or advanced empirical models such as first-principles, fault models, machine learning and artificial intelligence (AI), neural networks, fuzzy logic, genetic and evolutionary algorithms, and life-cycle analysis. The advancement of the internet of things (IoT), digital twin and augmented reality (AR) technologies are key enablers for implementing IHM systems in propulsion systems.

Seeking papers on the following, with the intent to establish a valuable interchange of technical solutions:

  • Condition evaluation of Propulsion Systems relevant IoT and AR implementation challenges, successes, lessons learned and business case impact
  • Digital Twin application examples and practices for propulsion systems supporting reliability or readiness
  • Data Management and Mining: Advances in data mining, data fusion, machine learning, and statistics with applications to verification and validation of data, prognosis and diagnosis of system health
  • Integrated Communications, Command and Control: architecture, theory, test beds, and demonstrations focused on vehicle health or reusability
  • Diagnostic Systems: architecture, theory, simulations, and demonstrations of diagnosis of current state of health of propulsion and vehicle system, including in-place and depot-level non-destructive inspection methodologies
  • Prognostic Systems: architecture, theory, simulations, and demonstrations of prognosis of future state of health of propulsion and vehicle systems; mitigation of, and recovery from, degraded system health to enable condition-based repairs and successful missions
  • Integrated Sensors and Sensing Systems: diverse sensors and integrated sensing systems with broad applications to health and status monitoring of all vehicle types and methods for integrated sensing systems across multiple disciplines and end-use applications with an emphasis on measurement technology, smart sensors, test beds, application considerations, lessons learned, and sensor fidelity for condition-base maintenance (CBM+) of propulsion systems


Mission Area III: Simulation Credibility: Verification, Validation, and Risk

The credibility of digital and analog simulations is a major issue for incorporating simulation tools and data into a technology-development program, for conducting simulation-based acquisition, for assessing system reliability to assure human safety and/or mission success, and for identifying and assessing risks in complex, technological systems. Simulation credibility includes assessment and management of computer simulation uncertainty, experimental uncertainty, verification and validation (V and V) of simulation models and of simulations, and risk assessment. Abstracts are solicited on technological advances in the following areas:

  • Uncertainty quantification for experiments and simulations
  • Validation of models and verification of simulations
  • Propagation of uncertainty
  • Risk assessment and management
  • Recommendations for guidelines, procedures, or standards

Mission Area IV: Modeling and Simulation of System Autonomy

Modeling and Simulation of System Autonomy encompasses the development of methodologies, codes, and models, and simulations to evaluate, analyze, and optimize autonomous system capabilities. This includes the modeling and simulation of artificial intelligence (AI) algorithms, the integration of AI algorithms, simulation environments including the interaction of algorithms with system hardware, verification and validation of non-deterministic algorithms, and determination of operational bounds. The use of modeling and simulations of autonomous systems to determine their responses and operational bounds is also a crucial technology area. Various autonomous systems are included in this mission area including air launched systems, ground vehicle launched systems, hypersonic vehicles, launch vehicles, spacecraft, and water launched systems. Specific topics of interest include impact of autonomous system responses to propulsion system performance, autonomous algorithm test and characterization methodology and test sets, integration of sensors suites with autonomous algorithms, and autonomous launch system interaction with launch vehicles and missiles.

JHU WSE ERG Technical Representative

Mr. Michael "Miki" Fedun, JHU WSU ERG / Columbia, MD
Telephone:  (540) 273-5501
Email:          mfedun@erg.jhu.edu