Systems Architecture Commons^™

Real-Time Immersive Wildfire Simulation: A Game Engine Approach, Jake Bova

Graduate Student Theses, Dissertations, & Professional Papers

Wildfires are growing in frequency, size, and severity, placing escalating demands on firefighting resources and putting lives, property, and ecosystems at risk. Accurate prediction of fire behavior is critical to suppression planning, evacuation decisions, and firefighter training, yet the operational models that fire managers rely upon face a persistent tradeoff. High-fidelity physics-based models capture fire–atmosphere interactions faithfully but are computationally expensive, often running far slower than real time on CPU hardware, while faster empirical models sacrifice the dynamic coupling between a fire and the wind field it generates. Furthermore, most existing tools produce abstract, two-dimensional outputs that offer limited visual …

Universal Systems Simulation Via Constraint Hypergraphs With Applications To Digital Twins, John Morris

All Dissertations

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, …

Predicting Simulation Times For Multiphase Thermal-Hydraulic Models, Andrew Yule, Andrew Taylor

SMU Data Science Review

Addressing the challenge of computationally intensive OLGA

simulations in the oil and gas industry, a machine learning framework is

developed for accurate runtime prediction. A specialized feature extraction

pipeline identifies key parameters—such as simulation time, time step,

number of branches, and section count—from OLGA input files that serve as

high-impact predictors. Multiple predictive models, including regression,

tree-based ensembles, and neural networks, are implemented to validate

accuracy and robustness. Results reveal that prioritizing simulations based on

predicted runtimes optimizes licensing resources and reduces operational

costs, making real-time scheduling more efficient. This research demonstrates

the effectiveness of data-driven runtime prediction in enhancing …

System Dynamics With Insight Maker, Steven D'Alessandro, Fons Wijnhoven

Research outputs 2022 to 2026

This book offers a practical, model-driven pathway for reasoning about uncertain futures in business and public policy using system dynamics with Insight Maker. It begins by motivating why historical data alone often fail to predict social change, and it introduces the core language of system dynamics—stocks, flows, feedbacks, delays, and auxiliary variables—alongside the complementary use of agent-based modeling. Through business-relevant cases (e.g., park management trade-offs, epidemic–economy interactions, and industry competition), the book demonstrates how non-linear structure generates counter-intuitive dynamics, why scenario analysis is essential, and how to translate causal loop diagrams into stock-and-flow simulations. Readers are guided step-by-step to build, …

A Virtual Time Driven Simulator For Devs Models, Ronald R. Stempien

Dissertations, Master's Theses and Master's Reports

When simulating a system that includes some software component, simulation authors are faced with the problem of how to appropriately model the software within the simulation. While many formal methods for modeling software exist, in some contexts these may not be appropriate or viable for a given simulation. Instead, simulation authors may model a computer within the simulation, and run the software in question “as is” on the modeled machine. In this work, we introduce a theoretical framework to allow for the use of hardware virtualization technologies as a hardware accelerator for CPU models in Discrete Event System Specification (DEVS) …

Exploring Blockchain Adoption Supply Chains: Opportunities And Challenges, Adrian V. Gheorghe, Omer F. Keskin, Farinaz Sabz Ali Pour

Engineering Management & Systems Engineering Faculty Publications

In modern supply chains, acquisition often occurs with the involvement of a network of organizations. The resilience, efficiency, and effectiveness of supply networks are crucial for the viability of acquisition. Disruptions in the supply chain require adequate communication infrastructure to ensure resilience. However, supply networks do not have a shared information technology infrastructure that ensures effective communication. Therefore decision-makers seek new methodologies for supply chain management resilience. Blockchain technology offers new decentralization and service delegation methods that can transform supply chains and result in a more flexible, efficient, and effective supply chain. This report presents a framework for the application …

Design And Implementation Of A Stand-Alone Tool For Metabolic Simulations, Milad Ghiasi Rad

School of Computing: Dissertations, Theses, and Student Research

In this thesis, we present the design and implementation of a stand-alone tool for metabolic simulations. This system is able to integrate custom-built SBML models along with external user’s input information and produces the estimation of any reactants participating in the chain of the reactions in the provided model, e.g., ATP, Glucose, Insulin, for the given duration using numerical analysis and simulations. This tool offers the food intake arguments in the calculations to consider the personalized metabolic characteristics in the simulations. The tool has also been generalized to take into consideration of temporal genomic information and be flexible for simulation …

Characterizing And Improving Power And Performance In Hpc Networks, Taylor L. Groves

Computer Science ETDs

Networks are the backbone of modern HPC systems. They serve as a critical piece of infrastructure, tying together applications, analytics, storage and visualization. Despite this importance, we have not fully explored how evolving communication paradigms and network design will impact scientific workloads. As networks expand in the race towards Exascale (1×10^18 floating point operations a second), we need to reexamine this relationship so that the HPC community better understands (1) characteristics and trends in HPC communication; (2) how to best design HPC networks to save power or enhance the performance; (3) how to facilitate scalable, informed, and dynamic decisions within …

Design Of Cpu Simulation Software For Armv7 Instruction Set Architecture, Dillon Tellier

Computer Engineering

Simulations have long been a part of the engineering process in both the professional and academic domain. From a pedagogic standpoint, simulations allow students to explore the dynamics of engineering scenarios by controlling variables, taking measurements, and observing behavior which would be difficult or impossible without simulation. One such tool is a CPU simulator used in Cal Poly’s Computer Architecture classes; this software simulates an instruction accurate operation of a computer processor and reports statistics regarding the execution of the supplied compiled machine code. For the last several years Cal Poly’s computer architecture classes have used a previous version of …