Digital Commons Network^™

Hybrid Threats And Deterrence Effectiveness In Europe, Chick Edmond

Political Science & Geography Faculty Publications

Objectives:
The current European security landscape is characterized by the growing intersection of historical security challenges (i.e., "traditional" security issues) and new forms of hybrid threats. These changes call for a significant re-evaluation of the role of deterrence in today's world. Traditional deterrence approaches have focused on the use of military capability as well as credible retaliatory threats. However, the recent development of hybrid warfare, including cyber-attacks, disinformation campaigns, economic coercion, and clandestine sabotage has made it increasingly difficult to distinguish between times of war and times of peace. This research argues that existing frameworks for deterring adversaries will increasingly …

The Evolving Beijing Consensus: Chinese Communist Party Political Control And Economic Trade Offs, Ian Murphy

Political Science & Geography Faculty Publications

China’s rapid economic rise and unique development trajectory have long been the subject of scholarly debate, often framed through the concept of the “Beijing Consensus” as an alternative to the Washington Consensus. While initial conceptualizations highlight innovation, sustainability, and national sovereignty, later analyses highlighted elements like state capitalism and authoritarianism, particularly in the wake of the 2008 Global Financial Crisis. This paper argues that the Beijing Consensus is undergoing a significant evolution under Chairman Xi Jinping, increasingly prioritizing the Chinese Communist Party’s political security, regime stability, and ideological control at the expense of economic growth. This marks a notable departure …

Nuclear Deterrence And The Security Dilemma In A Complex Multipolar World, Chick Edmond

Political Science & Geography Faculty Publications

Objectives: The purpose of this research project is to examine how nuclear deterrence intersects with the concept of security dilemma, i.e., when a state takes an action intended to increase its own security it may inadvertently create a risk or threat to another state and contribute to increased levels of tension. Fourth, how nuclear and conventional systems are becoming increasingly interconnected, which will serve to potentially amplify risks associated with these systems.

Methods: Utilizing a qualitative analytical approach of documents such as national strategy documents, defense policy statements and historical records of crises dating from 1945-2025, the study identifies four …

Autonomous Weapons And Strategic Stability, Chick Edmond

Political Science & Geography Faculty Publications

The increasing number of artificial intelligence (AI) elements within military systems has introduced new forms of security dilemmas related to speed, level of secrecy, and transfer of responsibility from humans to machines. This article addresses the question of whether or how AI enabled autonomous weapons can lead to greater levels of strategic instability. Three causal mechanisms were determined by this study to potentially create destabilizing effects due to the introduction of autonomy; the first mechanism is a reduction in time available for decision making. The second mechanism involves the creation of multiple pathways of escalation. The third mechanism is the …

Global Evidence On Scaling Nature-Based Solutions For Compound Hazards, Sina Razzaghi Asl, Anahita Azadgar

Political Science & Geography Faculty Publications

Nature-based solutions (NbS) are increasingly promoted for climate adaptation to compound hazards, but systematic evidence of their effectiveness is still scarce. We address this gap with a systematic review of 38 studies. Each study was sorted by what its measurement design can support, not by what its authors claim. This produced four groups. Direct studies attribute a measured hazard reduction to the intervention, proxy studies infer protection from ecosystem condition, prioritization studies map suitable locations without estimating performance, and qualitative studies describe effectiveness without measuring it. We detect trends in geographic distribution, hazard combinations, intervention types, methodological approaches, and strength …

The Contested Kinmen Model, Ian Murphy

Political Science & Geography Faculty Publications

[Introduction] Kinmen County, Taiwan, stands as an anomaly in East Asia- it is an archipelago administered by Taipei but visually and geographically tethered to the coastline of the People's Republic of China (PRC). For over seven decades, these islands have served as the physical frontline of the unfinished Chinese Civil War, functioning first as a kinetic battleground and later as a laboratory for cross-strait engagement. Yet, to view Kinmen as a relic of the Cold War is to miss it's contemporary strategic significance. The region has now become the primary theater for the PRC's "Kinmen Model" (Jinmen Moshi, symbols redacted), …

Small-𝑥 Asmptomatics Of The Leading-Twist Flavor Singlet Quark Tmds, Daniel Adamiak, M. Gabriel Santiago, Yossathorn Tawabutr

Physics Faculty Publications

In this paper, we investigate the small-𝑥 behavior of the flavor-singlet, leading-twist quark transverse-momentum-dependent parton distribution functions (TMDs) using the light-cone operator treatment. This formalism allows us to express TMD operators at small 𝑥 in terms of polarized dipole amplitudes, enabling a systematic approach to their small-𝑥 evolution. We derive the evolution equations for these TMDs and solve them within the large-𝑁𝑐 approximation under the linearized, double-logarithmic approximation, where 𝑁𝑐 represents the number of quark colors. Expanding on previous work on unpolarized and helicity TMDs, we present the small-𝑥 asymptotics for a comprehensive set of TMDs, including the Sivers function, …

Trigonometric Continuous-Variable Gates And Hybrid Quantum Simulations Of The Sine-Gordon Model, Tommaso Rainaldi, Victor Ale, Matt Grau, Dmitri Kharzeev, Enrique Rico, Felix Ringer, Pubasha Shome, George Siopsis

Physics Faculty Publications

Hybrid qubit-qumode quantum computing platforms provide a natural setting for simulating interacting bosonic quantum field theories. However, existing continuous-variable gate constructions rely predominantly on polynomial functions of canonical quadratures. In this work, we introduce a complementary universality paradigm based on trigonometric continuous-variable gates, which enable a Fourier-like representation of bosonic operators and are particularly well suited for periodic and non-perturbative interactions. We present an ancilla-based framework for implementing trigonometric gates with arguments given by arbitrary Hermitian functions of qumode quadratures. The protocol yields unitary gates deterministically, and non-unitary gates through probabilistic post-selection. As a concrete application, we develop a hybrid …

Geometry Of Almost-Conserved Quantities In Symplectic Maps: Approximate Invariants In Nonlinear Accelerator Systems, T. Zolkin, S. Nagaitsev, I. Morozov, S. Kladov

Physics Faculty Publications

We present a perturbative method for constructing approximate invariants of motion directly from the equations of discrete-time symplectic systems. This framework offers a natural nonlinear extension of the classic Courant-Snyder (CS) theory for systems with 1 degree of freedom—a foundational cornerstone in accelerator physics now spanning seven decades and historically focused on linear phenomena. The original CS formalism emerged under conditions where nonlinearities were weak, design goals favored linear motion, and analytical tools—such as the Kolmogorov-Arnold-Moser theory—had not yet been fully developed. While various normal-form methods have been proposed to treat near-integrable dynamics, the approach introduced here stands out for …

Rf Design Progress Of The 197 Mhz Crab Cavity For Eic, B. Xiao, J. C. Brutus, A. Blednykh, Z. Conway, J. Cox, J. R. Delayen, S. U. De Silva, R. Fernandes, J. Guo, D. Holmes, N. Huque, G. Li, Z. Li, J. B. Mandel, S. Verdú-Andrés, G. Wang, Q. Wu, W. Xu

Physics Faculty Publications

The interaction region (IR) crab cavity system is a special RF system designed to compensate for the luminosity loss caused by the 25 mrad crossing angle at the interaction point (IP) of the Electron-Ion collider (EIC). The configuration includes six crab cavities in the Hadron (proton or ion) Storage Ring (HSR) - four operating at 197 MHz and two at 394 MHz - installed on each side of the IP, along with one 394 MHz crab cavity on each side of the IP in the Electron Storage Ring (ESR). This paper presents the recent progress in the RF design of …

Mtl_Tx: A Multi-Task Transformer Model For Improved Radiation Time-Series Estimation, Hongfang Zhang, Adam Stavola, Hal Ferguson, Bence Budavari, Hongyi Wu, Chiman Kwan, Jiang Li

Electrical & Computer Engineering Faculty Publications

Controlling radiation doses at potential radioactive facilities is critical to ensuring the safety of both personnel and the public. At the Thomas Jefferson National Accelerator Facility (JLab), multiple sensors are deployed around the three experimental halls to monitor key parameters, including single-beam current, energy levels, current leakage, and radiation values during accelerator operations. In this study, we developed a Multi-task Transformer model, MTL_TX, to accurately estimate radiation doses at sensor locations based on historical data, with the aim of enhancing safety in accelerator facilities and surrounding public areas. To improve estimation accuracy, we integrated two innovative components into the proposed …

Digital Twin Technologies For Battery Systems: Advancements, Applications, And Future Directions, Seyed Saeed Madani, Yasmin Shabeer, Michael Fowler, Satyam Panchal, Carlos Ziebert, Hicham Chaoui, François Allard

Electrical & Computer Engineering Faculty Publications

The relationships among deep learning, edge computing, artificial intelligence (AI), and the most recent advancements in digital twin (DT) technology for battery energy storage systems are discussed in this paper. The study highlights the need for improved cloud-edge coordination, AI model development, and stronger cybersecurity features by demonstrating real-world applications of digital twin technology in electric vehicles (EVs), aircraft, and grid storage. It also described DT-based structures for fault detection, real-time monitoring, and optimization through standardization and battery management system (BMS) fusion. Because DT-based solutions for distributed energy resources (DERs) offer improved energy management systems, various studies have been conducted …

Qubit Lattice Algorithm Simulations Of The Scattering Of A Bounded Two Dimensional Electromagnetic Pulse From The Infinite Planar Dielectric Interface, Min Soe, George Vahala, Linda Vahala, Efstratios Koukoutsis, Abhay K. Ram, Kyriakos Hizanidis

Electrical & Computer Engineering Faculty Publications

Qubit lattice algorithm (QLA) simulations are performed for a two-dimensional spatially bounded pulse propagating onto a plane interface between two dielectric slabs. QLA is an initial value scheme that consists of a sequence of unitary collision and streaming operators, with appropriate potential operators, that recover Maxwell equations in inhomogeneous dielectric media to the second order in the lattice discreteness. For the case of total internal reflection, there is transient energy transfer into the second medium due to the evanescent fields as the Poynting unit vector of the pulse is rotated from its incident to reflected direction. Because of the finite …

Recent Insight And Perspective Of Marine-Inspired Biopolymers For Wound Healing Applications - A Review, Muhammad Umar Aslam Khan, Saiqa Yousaf, Abdalla Abdal-Hay, Mohd Faizal Bin Abdullah, Sahar Madani, Muhammad Shahzad Zafar, Goran M. Stojanović, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

There is an increasing necessity for advanced, sustainable, and biocompatible materials for wound healing as therapeutic and diagnostic products. Marine environments, characterized by high biodiversity, offer an underutilized source of natural resources with enormous potential for creating novel materials for dressings. This review highlights the revolutionary nature of polymeric biomaterials of marine origin, with a focus on polysaccharides, like alginate, chitosan, and carrageenan; proteins, such as collagen and gelatin. These biopolymers are outstanding in their physicochemical properties, such as biodegradability, bioactivity, and modifiable mechanical strength, which enable their use in wound-healing systems. Besides, these biomaterials may be easily chemically and …

Multimodal Machine Learning For Alzheimer's Disease Classification Using Adni Biomarker Fusion, Hesameddin Mostaghimi, Hamid R. Okhravi, Bahar Niknejad, Daniel A. Cohen, Michel A. Audette, Alzheimer's Disease Neuroimaging Initiative

Electrical & Computer Engineering Faculty Publications

Despite ongoing advances, accurate diagnosis of Alzheimer’s disease (AD) remains challenging due to its multifactorial nature, comorbidities, and clinical heterogeneity. Accordingly, approaches that combine multimodal data may improve AD classification by integrating complementary information. To investigate this, we evaluated classification performance using a preprocessed ADNI-3 dataset comprising a shared set of clinical/cognitive features along with four imaging modality-based cohorts: trimodal (MRI + amyloid PET + tau PET), MRI + amyloid PET, MRI + tau PET, and MRI-only. We trained a range of supervised machine learning (ML) and deep learning (DL) classifiers using stratified five-fold cross-validation and evaluated performance using accuracy, …

Pin-Plane Electrical Discharge Driven By A Mosfet Dc Current Source, Myles Perry, Sidmar Holoman, Daniel Wozniak, Shirshak Kumar Dhali

Electrical & Computer Engineering Faculty Publications

The generation of atmospheric pressure nonequilibrium plasma using electrical discharges is an active area of research due to its significance in a wide spectrum of applications including medicine, combustion, and manufacturing. In our attempt to create a helium plasma jet in a pin-plane discharge with a constant current source, we observed self-pulsating behavior. We present the results of the electrical, optical, and spectroscopic measurements carried out to characterize the discharge. The duration of the discharge is a few tens of nanoseconds, and the repetition rate is in the few tens of kHz. The effect of the gap distance and gas …

An Explainable Cs-Mitigation Triangular (Ecsmt) Framework To Secure Graph Neural Networks, Sabah Ettahri, Sergio Pallas Enguita, Chung-Hao Chen, Wen-Chao Yang

Electrical & Computer Engineering Faculty Publications

This research addresses cyber risk by defending against backdoor attacks on Graph Neural Networks (GNNs). We propose the Explainable Complex System-Mitigation Triangular (ECSMT) Framework, which integrates Robust Training, Graph Regularization, and Data Sanitization into a lightweight, hardware-efficient defense layer. To evaluate structural generalizability, we conducted empirical evaluations across three distinct benchmark domains (AIDS, MUTAG, and PROTEINS) using a Graph Isomorphism Network (GIN) backbone. Under a baseline 5% backdoor subgraph trigger injection ratio, ECSMT achieves excellent utility retention, securing a Clean Accuracy (CA) of 97.33% (±0.62%) while reducing the Attack Success Rate (ASR) from 97.00% down to 69.45% on the primary …

Generalized Inverter Fault Detection Using Normalized Current Features And A Lightweight Bilstm Network, Mohammad Zamani Khaneghah, Mohamad Alzayed, Hicham Chaoui

Electrical & Computer Engineering Faculty Publications

Fault detection and diagnosis of three-phase inverter-fed motor drives is essential for ensuring system reliability, safety, and continuous operation in applications such as electric vehicles and industrial automation. This paper proposes a data-driven fault detection framework based on normalized current features and a lightweight bidirectional long short-term memory (BiLSTM) network which can be generalized to different motor power rating in the same controller system. A compact set of six time-domain features, consisting of the mean and root-mean-square (RMS) values of the phase currents, is extracted and normalized with respect to the average RMS value. This normalization effectively removes dependency on …

Dynamic Direct Voltage Control Under Maximum Torque Per Ampere For Interior Pmsms, Mohamad Alzayed, Hicham Chaoui, Alaref Elhaj

Electrical & Computer Engineering Faculty Publications

A novel method for controlling the speed of interior permanent magnet synchronous motors (IPMSMs), known as the current-sensing-based dynamic direct voltage control method under the maximum torque per ampere (MTPA) concept, is introduced. This technique achieves precise tracking of machine velocity by determining the optimal combination of voltage amplitude and angle for each specific motor velocity and current/load condition. Unlike previous studies, this approach takes into account the transient model of the machine, resulting in improved accuracy during dynamic operating conditions compared with existing methods in the literature. Moreover, a comparative analysis is conducted involving different direct voltage MTPA speed …

Fault Tolerance Of Accelerated Asynchronous Fixed-Point Iterations On Flexible Computing Infrastructure, Evan Coleman, Masha Sosonkina

Electrical & Computer Engineering Faculty Publications

Asynchronous iterative methods tolerate straggling processors by allowing workers to proceed with stale data, but at a cost: the iterates become inconsistent, potentially degrading convergence. We investigate whether convergence accelerators such as Anderson acceleration compensate for this degradation. We experimentally study three fixed-point iterations: the Jacobi method for sparse linear systems, value iteration for the Bellman equation, and the Hartree–Fock self-consistent field (SCF) iteration. The experiments are conducted using a high-performance execution framework, Ray, which abstracts the complexity of distributed systems and enables code parallelization and fault injection with minimal changes.

We establish two main results. First, straggler tolerance is …

Affordable Course Content And Open Education Resources For Undergraduate Courses Teaching Fundamentals Of Wireless Communications And Networking, Dimitrie C. Popescu, Otilia Popescu

Electrical & Computer Engineering Faculty Publications

Wireless communication systems and networks along with the services they provide have become an essential component of the modern 21st century society, fueling job growth in the wireless industry and increasing the need for engineers specialized in wireless communication systems. As a consequence, over the past two decades, undergraduate courses teaching fundamentals of wireless communication systems and networks have become common in electrical and computer engineering and technology programs. At the same time, the number of textbooks dedicated to wireless systems and networks published by mainstream publishers has also grown, with availability in various formats and offerings and a significant …

Automated Writer And Acquisition-Condition Classification Of Digitally Captured Handwriting Using Statistical Dynamic Features And Support Vector Machines, Long-Huang Tsai, Hsiang-Ju Lai, Wen-Chao Yang, Jiajun Jiang, Chung-Hao Chen

Electrical & Computer Engineering Faculty Publications

Digitally captured handwriting preserves pen trajectories and dynamic signals, but it also records hardware- and input-dependent properties that can confound forensic interpretation. This study revises a support vector machine (SVM) screening framework using 16,500 samples from 30 writers, 11 writing-content categories, and five acquisition conditions spanning three tablets and stylus or finger input. Twenty-four raw and derived time-series variables were summarized by maximum, minimum, mean, median, and standard deviation, yielding 120 features; the mode statistic was removed. Writing direction and angular velocity were recalculated with atan2-based vector formulas. Unavailable device/API channels were encoded as zero, and Z-score parameters were estimated …

Injectable Hydrogels For Bone Regeneration: Mechanical Reinforcement Strategies Using Nanoparticles And Nanofibers: Review Paper, Fariba Ganji, Morteza Mirzagoli, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

Background and Purpose: The growing demand for bone regeneration following severe injuries highlights the importance of scaffolds in bone tissue engineering (BTE). Injectable hydrogels have emerged as promising candidates because their properties closely mimic the native extracellular matrix (ECM). However, their limited mechanical strength and structural instability restrict their practical application. Approach: This review summarizes recent strategies for reinforcing in situ-forming injectable hydrogels to improve their mechanical performance for bone regeneration. Particular emphasis is placed on nanomaterial-based strategies, including the incorporation of nanoparticles and nanofibers, and their ability to enhance the physical properties of polymeric networks. Key Results: Evidence from …

Physics-Informed Temperature Prediction Of Lithium-Ion Batteries Using Decomposition-Enhanced Lstm And Bilstm Models, Seyed Saeed Madani, Yasmin Shabeer, Michael Fowler, Satyam Panchal, Carlos Ziebert, Hicham Chaoui, François Allard

Electrical & Computer Engineering Faculty Publications

Accurately forecasting the operating temperature of lithium-ion batteries (LIBs) is essential for preventing thermal runaway, extending service life, and ensuring the safe operation of electric vehicles and stationary energy-storage systems. This work introduces a unified, physics-informed, and data-driven temperature-prediction framework that integrates mathematically governed preprocessing, electrothermal decomposition, and sequential deep learning architectures. The methodology systematically applies the governing relations to convert raw temperature measurements into trend, seasonal, and residual components, thereby isolating long-term thermal accumulation, reversible entropy-driven oscillations, and irreversible resistive heating. These physically interpretable signatures serve as structured inputs to machine learning and deep learning models trained on temporally …

Microfluidic Encapsulation Of Sorafenib-Loaded Zif-8 Nanoparticles In Ph-Responsive Alginate Microparticles For Oral Chemotherapy Of Hepatocellular Carcinoma, Mojdeh Mirshafiei, Zahra Mahmoudi, Mehdi Mehrpouya, Mahdi Mahmoudi, Masoud Rezaeian, Mona Navaei-Nigjeh, Zahra Katoli, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

Hepatocellular carcinoma (HCC) remains one of the leading causes of cancer-related mortality. Sorafenib is the current first-line oral therapy; however, its therapeutic efficacy is limited by poor aqueous solubility, low bioavailability, and gastrointestinal instability. This study aimed to develop a pH-responsive nano-in-microparticle delivery system using a single-step droplet-based microfluidic process to protect sorafenib in the gastric environment and achieve controlled release for enhanced oral chemotherapy. Sorafenib-loaded ZIF-8 nanoparticles (SZ NPs) were synthesized and characterized by scanning electron microscopy (SEM), Fourier-transform infrared (FTIR) spectroscopy, Energy-dispersive X-ray (EDX) spectroscopy, and X-ray diffraction (XRD), exhibiting a mean diameter of about 72 nm and …

Comparative Assessment Of Energy And Emission Costs For Geothermal Heat Pumps And Fossil-Fuel Heating Systems Across U.S. Climatic Zones, Md Shahin Alam, Shima Afshar, Seyed Ali Arefifar, Mohammad Haq

Electrical & Computer Engineering Faculty Publications

In response to growing concerns over global warming and energy sustainability, transitioning from fossil-fuel-based heating systems to renewable alternatives is essential. This study evaluates the economic and environmental performance of geothermal heat pumps for building heating and compares it with conventional coal-fired boilers, natural-gas boilers, and diesel furnaces. Using the heating degree-day (HDD) method, heating energy demand was analyzed for four U.S. cities—Anchorage (AK), San Francisco (CA), Salt Lake City (UT), and Las Vegas (NV)—representing diverse climatic zones. The analysis integrates thermodynamic and economic parameters, including the coefficient of performance (COP = 2–5) and annual fuel-utilization efficiency (AFUE = 80–97%), …

Leveraging Virtual Reality And Haptics To Teach Surgical Skills: A Usability Study On Retropubic Midurethral Slings, Lauren Siff, Ginger S. Watson, Jerome Dixon, Moshe Feldman, Franklin Bost, Philippe J. Giabbanelli

VMASC Publications

Traditional methods to learn soft-tissue surgical procedures rely on cadaver labs or patient-based learning, which are costly and geographically limited, and raise ethical questions. Virtual reality (VR) with haptic feedback offers a scalable alternative, but most current platforms emphasize bone-based rather than soft-tissue procedures learned by feel. We developed a VR+haptic simulation for preoperative training of retropubic midurethral sling (MUS) surgery. This study examines the usability of this platform with thirteen expert urogynecologic surgeons and subsequently makes improvements (e.g., in haptics) to evaluate the platform with twelve trainees based on the NASA Task Load Index for workload and a UTAUT-informed …

Modeling Rank Distribution And The Relative Importance Factor Index In Discrete Power-Law Models: Application To Social Resilience Using The Scopus Database, Brian Llinas, Jose Padilla, Humberto Llinas, Erika Frydenlund, Katherine Palacio

VMASC Publications

Prior research on power-law distributions has primarily focused on modeling frequency patterns, with less attention given to rank distributions and how ranked positions reflect relative importance among elements. In discrete power-law distributions, frequency-based metrics often provide limited discrimination in the tail, where elements may exhibit similar counts but differ in relative dominance. These patterns are especially evident, for instance, in academic publishing, where keywords, affiliations, and citations commonly exhibit power-law behavior. To address this limitation, we introduce the Relative Importance Factor (RIF) Index, a statistical measure derived from the estimated discrete power-law rank distribution rather than an additional independent parameter. …

Standardization Of Neuromuscular Reflex Analysis—Role Of Fine-Tuned Vision-Language Model Consortium And Openai Gpt-Oss Reasoning Llm-Enabled Decision Support System, Eranga Bandara, Ross Gore, Sachin Shetty, Ravi Mukkamala, Christopher K. Rhea, Brittany S. Samulski, Amin Hass, Atmaram Yarlagadda, Shaifali Kaushik, Malith De Silva, Andriy Maznychenko, Inna Sokolowska, Kasun De Zoysa

VMASC Publications

Background/Objectives: Accurate assessment of neuromuscular reflexes, such as the Hoffmann reflex (H-reflex), plays a critical role in sports science, rehabilitation, and clinical neurology. Conventional interpretation of H-reflex electromyography (EMG) waveforms is subject to inter-rater variability and interpretive bias, limiting reliability and standardization. This study aims to develop an automated, interpretable, and robust agentic AI–driven framework for H-reflex waveform analysis. Methods: We propose a fine-tuned Vision–Language Model (VLM) consortium combined with a reasoning Large Language Model (LLM)–enabled decision support system for automated H-reflex interpretation. Multiple VLMs were fine-tuned on curated datasets of H-reflex EMG waveform images annotated with expert clinical observations, …

Distilling The Complexity Of Agent-Based Simulations Into Textual Explanations Via Large Language Models, Noé Y. Flandre, Philippe J. Giabbanelli

VMASC Publications

Communicating the design and results of agent-based models (ABMs) to subject matter experts is challenging, which hinders participation and limits trust in simulation-based decision support. Large language models (LLMs) can communicate ABMs as textual summaries, thus complementing traditional disclosure through statistical and visualization techniques. While prior work translated the structure of conceptual models into narratives via LLMs, our extension covers the dynamics of simulation models via an automated simulation-to-text method that extracts contextual information from NetLogo ABMs, performs repeated simulations, and generates narrative descriptions (including the model’s purpose, parameters, and simulation dynamics) using mutimodal LLMs. Furthermore, four summarization algorithms spanning …