Engineering Commons^™

Lrq-Solver: A Transformer-Based Neural Operator For Fast And Accurate Solving Of Large-Scale 3d Pdes, Peijian Zeng, Guan Wang, Haohao Gu, Xiaoguang Hu, Tiezhu Gao, Zhuowei Wang, Aimin Yang, Xiaoyu Song

Electrical and Computer Engineering Faculty Publications and Presentations

Solving large-scale PDEs on complex three-dimensional geometries remains a central challenge in scientific and engineering computing, often due to expensive pre-processing stages and high computational overhead. We present Low-Rank Query-based PDE Solver (LRQ-Solver), a physics-integrated deep learning framework for efficient CAE simulations of complex three-dimensional geometries in CAD-driven design analysis. Built upon the Parameter-Conditioned Lagrangian Modeling (PCLM) that embeds physical consistency into the learning process and the Low-Rank Query Attention (LR-QA) module that reduces attention complexity from O(N2) to O(NC2+C3) via covariance decomposition, LRQ-Solver supports multi-configuration analysis within iterative design workflows. On two benchmark datasets, it achieves a 28.6% error …

Machine Learning Local Potentials For Accelerated Electron-Phonon Interactions Calculations Within The Projector Augmented-Wave Framework, Yi Xia

Mechanical and Materials Engineering Faculty Publications and Presentations

Electron–phonon interactions govern carrier dynamics, transport, and many optical and quantum phenomena in solids, but finite-displacement calculations within the projector augmented-wave (PAW) framework require up to 6N self-consistent supercell calculations for an N-atom system, making them costly for large, low-symmetry, and disordered materials. We introduce MLLocP, a machine learning (ML) strategy that learns the self-consistent local potential (LocP) on real-space grids and supplies its displacement derivatives to the evaluation of all-electron PAW electron–phonon matrix elements. Analysis of the PAW decomposition identifies the local-potential contribution as a natural target for machine learning, while the remaining PAW quantities are retained within the …

A Philosophical Introduction To Elements And Relations: Aspects Of A Scientific Metaphysics, Martin Zwick

Complex Systems Faculty Publications and Presentations

My book, Elements and Relations*, amplifies Bunge’s characterization of the systems project as the construction an “exact and scientific metaphysics” (ESM) different from and broader than the reductionist and physicalist ontology of conventional science. This paper discusses the scientific theories constituting this project and the central notion of “system” as a structure-function dyad, where “structure” is the system’s internal order and “function” is its participation in the external order of its environment. The paper also discusses the book’s proposal of ontology and ethics as a structure-function dyad for the systems field, an ontology of problems that exemplifies the ESM idea.

Influence Of Particle Properties And Grain Size On Aggregation In Dry Particle-Laden Volcanic Jets, Md Miraz Hossain, Stephen A. Solovitz, Josef Dufek, Joshua S. Mendez Harper, Alexa R. Van Eaton, Mary C. Benage, Larry G. Mastin, Benjamin J. Andrews

Electrical and Computer Engineering Faculty Publications and Presentations

Explosive volcanic eruptions can inject large amounts of ash into the atmosphere. These suspended particles pose hazards to aircraft, so a better understanding of the ash residence time and transport distance is needed. Fine particles combine to form larger aggregates, altering their settling behavior. Ash aggregation is influenced by liquid bonding, electrostatic forces, and preferential concentration driven by turbulence. We examine particle aggregation through controlled, low-humidity experiments at similar particle-fluid scaling to conditions near a volcanic vent. Particle-laden jets used compressed air containing three types of particles at controlled mass loadings: hollow glass spheres (∼10 μm diameter), solid nickel spheres …

Factors Influencing Enterprise Adoption Of Ai-Enabled Computers: An Expert Judgment Quantification Approach Across Multiple Sectors, Yu Shan Su, Tugrul Daim, Chia-Hao Hung, Leong Chan, Dana Bakry

Engineering and Technology Management Faculty Publications and Presentations

This study examines the key factors influencing the adoption of Artificial Intelligence Personal Computers (AIPCs) by enterprises, exploring both the benefits and challenges of their business applications. As enterprises increasingly require real-time computing, autonomous decision-making, and improved cybersecurity, AIPC—combining artificial intelligence and edge computing—has become a strategic technology for boosting competitiveness. Particularly in scenarios with less reliance on cloud services, businesses are more likely to adopt devices with local processing and standalone AI capabilities to meet the dual needs of operational efficiency and data privacy. Through an extensive review of the literature, this study identifies four main dimensions and sixteen …

The Vegetated-Canopy Roughness Sublayer Through A Tke-Budget Lens, Giulia Salmaso, Raul Bayoan Cal, Marc Calaf

Mechanical and Materials Engineering Faculty Publications and Presentations

It is well understood that vegetated canopies perturb the atmospheric flow within and immediately above the canopy, deviating from the inertial sublayer (ISL) regime characteristic of non-vegetated rough surfaces. Only above a certain height, denoted as the roughness sublayer height (RSL, 𝑧∗), do these flows return to ISL-like behavior. This distinction is critical, as parameterizations in Earth System Models (ESMs) are typically developed for ISL flows. Yet, most 𝑧∗ estimates stem from studies over flat, homogeneous canopies and may be biased. In contrast, little is known about 𝑧∗ in non-homogeneous or heterogeneous canopies that are not of agricultural interest, with …

A Graph Attention Network-Based Framework For Reconstructing Missing Lidar Beams, Khalfalla Awedat, Mohamed Abidalrekab, Mohammad El-Yabroudi

Electrical and Computer Engineering Faculty Publications and Presentations

Vertical beam dropout in spinning LiDAR sensors -triggered by hardware aging, dust, snow, fog, or bright reflections - removes entire vertical slices from the point cloud and severely degrades 3D perception in autonomous vehicles. This paper proposes a Graph Attention Network (GAT)-based framework that reconstructs these missing vertical channels using only the current LiDAR frame, with no camera images or temporal information required. Each LiDAR sweep is represented as an unstructured spatial graph: points are nodes and edges connect nearby points while preserving the original beam-index ordering. A multi-layer GAT learns adaptive attention weights over local geometric neighborhoods and directly …

Surrogate-Guided Conditional Generative Adversarial Network For Generative Design Of 3d-Printable Terahertz Holographic Metasurfaces, Manxu Lv, Zhikai Hu, Zhichuan Xie, Huizhen Feng, Dongping Zhang, Manna Gu, Chee Leong Tan, Bo Fang, Yongxing Jin, Ying Tian, Xufeng Jing

Electrical and Computer Engineering Faculty Publications and Presentations

Terahertz metasurface holography requires unit cells with prescribed complex transmission responses and sufficient compatibility with practical fabrication processes. For elementary low-bit phase quantization at 0.1 THz, conventional parameter sweeping of simple geometries remains an effective and reliable approach. However, when the design objective is extended from a single phase state to simultaneous consideration of complex transmission matching, transmission amplitude, structural connectivity, and fabrication-related geometric constraints, the design problem becomes a constrained multi-objective inverse-design task. Here, we propose a generative-model-assisted inverse-design framework for 3D-printable terahertz metasurface unit cells. The framework combines a VGG-based surrogate model with a modified WGAN-GP generator. The …

Superiorgat: Graph Attention Networks For Sparse Lidar Point Cloud Reconstruction In Autonomous Systems, Khalfalla Awedat, Mohamed Abidalrekab, Gurcan Comert, Mustafa Ayad, Negash Begashaw

Electrical and Computer Engineering Faculty Publications and Presentations

LiDAR-based perception in autonomous systems is fundamentally limited by sparse vertical sampling and further degraded by structured beam dropout caused by occlusions, sensor faults, or reduced-cost LiDAR hardware. These degradations disrupt vertical geometric continuity and negatively affect downstream perception tasks such as object detection, localization, and scene understanding. Existing reconstruction approaches often struggle to balance reconstruction accuracy with the computational efficiency required for real-time autonomous operation. This paper presents SuperiorGAT, a graph attention–based framework for reconstructing missing elevation information in sparse LiDAR point clouds under structured beam loss. The proposed method models LiDAR scans as beam-aware graphs and enhances standard …

Multi-Solution Ternary Grover’S Algorithm For Logic-Based Quantum Machine Learning With Pseudo-Kronecker Reed–Muller Form Minimization, Sophia Lee, Ali Al-Bayaty, Marek Perkowski

Electrical and Computer Engineering Faculty Publications and Presentations

Optimization problems in machine-learning (ML) applications can be computationally challenging for classical methods, particularly when they involve large, unstructured search spaces. Quantum computing offers a promising approach to combinatorial optimization by utilizing quantum superposition and amplitude amplification. This paper presents a new methodology using logic-based quantum machine learning (QML) as a complete framework for employing a multi-solution ternary Grover’s algorithm to minimize incomplete binary functions represented by Pseudo-Kronecker Reed–Muller (PKRO) expansions, consistent with Occam’s razor principle. Unlike previous quantum approaches based on Kronecker Reed–Muller (KRO) or fixed-polarity Reed–Muller (FPRM) representations, our work introduces the first Grover-based optimization framework for PKRO …

Fault Recovery For A Class Of Unmanned Autonomous Vehicles Using Gaussian Process Regression, Garrison Greenwood

Electrical and Computer Engineering Faculty Publications and Presentations

Unmanned autonomous vehicles (UAVs) must often operate reliably in remote, hostile environments for extended periods. Fault tolerance is essential, enabling continued operation despite system faults. Fault recovery is challenging due to unknown fault characteristics and no possibility of on-site human intervention. Replacing faulty hardware with operating spares is an effective recovery method, but impractical because UAVs have limited space. Reconfiguration may be the only practical option. This paper discusses correcting faulty behavior in robot arm DC servos, guided by a PID controller, by modifying the controller’s gain values. Although simple in principle, finding new gain values is difficult and time-consuming, …

Degree Assortativity And Estimation Of Degree Distribution In A Contact Network Of People Who Inject Drugs, Peter Geissert

Dissertations and Theses

This dissertation analyzes data from a respondent driven sampling (RDS) study of people who inject drugs in Portland, OR.  The objective was to assess assumptions for the use of weighted estimators to estimate a population physical contact (syringe sharing) network degree distribution.

Visualization of degree distribution for social and physical networks, Kolmogorov-Smirnov tests of difference, and kernel tests of equivalence were used for comparison of distributions. Spearman's rho and GAM non-parametric regression models were used to test for association and assess non-monotonic relationship. The validity of Markov chain assumptions for RDS was assessed using a transition matrix, Markov chain graphs, …

Research Priorities For Robust Climate Assessments In The United States, Melissa A. Kenney, Robert E. Kopp, Constantine Samaras, Marina Alberti, Sonia Y. Angell, Jennifer Burney, Colin Cunliff, Elliott T. Gall, J. T. Duffy-Anderson, Multiple Additional Authors

Mechanical and Materials Engineering Faculty Publications and Presentations

Scientific assessments play a critical role in synthesizing evidence to support evidence-based decision-making in many sectors and topics. For climate change, large-scale assessments like the Intergovernmental Panel on Climate Change (IPCC) and the United States (U.S.) National Climate Assessment (NCA) reports help many different users—from national government to local governments, Indigenous Peoples and communities, the private sector, the social sector, and the scientific community itself—navigate the complex field of climate risks, impacts, and integrated solutions. While co-creation with users is essential to developing actionable assessments, this paper lays the groundwork for future processes by identifying many advancing and emerging areas …

Effects Of Infill Pattern And Infill Density On The Flexural Properties Of Markforged Onyx, Jonathon Tran, Rachel Shubella, Alexander Hunt

Mechanical and Materials Engineering Faculty Publications and Presentations

Fused Filament Fabrication (FFF) enables the production of lightweight polymer composite components with complex geometries; however, the effects of infill geometry on printing accuracy and mechanical behavior of unreinforced Markforged Onyx remains insufficiently understood. This parametric study investigates the influence of four infill patterns (gyroid, hexagonal, rectangular, and triangular) and three infill densities (30%, 40%, and 50%) on the post-print mass, dimensional accuracy, microstructure and flexural properties of Onyx specimens fabricated using a Markforged Mark Two printer. Experimental measurements were compared with Eiger slicing software predictions, and geometry- and mass-based area moment of inertia correction methods were evaluated. The results …

Spatial Reconstructability Analysis: Information-Theoretic Modeling Of Categorical Raster Data, David Percy

Dissertations and Theses

This research focuses on the application of Reconstructability Analysis (RA), an information-theoretic machine learning (ML) methodology, to categorical spatial data in Geographic Information Systems (GIS). RA was developed in the systems community with applications including classification, prediction, pattern recognition, and decision analysis. RA is implemented in OCCAM (Organizational Complexity Computation and Modeling), a software suite developed at Portland State University that analyzes discrete data in tabular form, with observations in rows and variables in columns. While RA has been successfully applied to a variety of domains, no systematic application to georeferenced raster data arranged in regular grids has been previously …

Developing Field And Spaceflight Microscopy, Nikki Johnston

Dissertations and Theses

Designing for spaceflight favors the reduction of unnecessary features and cost-cutting, whether thisbe computation, hardware, or procedure. Resources are spent toward fortification and mission success over convenience. Such design goals paired with the relatively smaller budgets of academia lead us to do as much as we can in-house and use open-source as much as we can without compromising mission success. We also believe that thoroughly testing technology in extreme environments on earth is necessary for the success of a flight instrument. We focus on microscopy for life detection. I have spent my time here learning methods of hand-building microscopes to …

Advancing The Oresat Adcs: Design & Implementation Of An Open-Source Reaction Wheel System, Chris Kane-Pardy

Dissertations and Theses

Reaction wheels provide the primary means of precision attitude control for many CubeSat attitude determination and control systems by exchanging angular momentum with the spacecraft body. As the Portland State Aerospace Society's OreSat spacecraft transitioned from a 2U to a 3U configuration, the increased spacecraft inertia reduced the attitude control authority available from the legacy reaction wheel system. This thesis addresses that challenge through the redesign of the reaction wheel system and the development of a deterministic embedded controller and experimental framework for evaluating brushless motor commutation strategies under identical operating conditions.

The redesigned system combines an analytically sized flywheel, …

Intrinsic Memory In Digital Snns: Enhancing Performance On The Cart-Pole Task With Fractional-Order Dynamics, Niklas Karl Anderson

Dissertations and Theses

Researchers working with Spiking Neural Networks (SNNs) are faced with the challenge of identifying useful biologically plausible features for inclusion in neuron models. Prior research indicates that dynamics of fractional-order calculus, which impart a form of intrinsic memory, are a key feature of biological neurons. In this work, we present the development and usage of neural networks with intrinsic memory in application to the cart-pole task, a common benchmark for neural network performance. We found that usage of fractional-order neurons may allow for up to a 37.5% reduction in neural network size as compared to networks using a standard Leaky …

The Influence Of Urban Form On The Distribution Of Air Pollutants, Takin Khosrownia

Dissertations and Theses

Urban form exerts strong control on how pollution from outside a city is transported through the urban canopy and experienced at street level. This study uses the prognostic microclimate model ENVI-met to simulate an active pollutant released from an upwind rural highway and advected through an urban region represented by ten Local Climate Zone (LCZ) types. The cases share identical inflow and are isothermal, dry, and non-vegetated, so that differences among them are attributable to building morphology alone. PM2.5 is the primary exposure diagnostic. Its transport and ejection are characterized through plan-view contours, vertical plume sections, and spatially averaged streamwise …

Functionality Risk Assessment And Risk-Based Management For Critical Infrastructure Systems, Anteneh Zewdu Deriba

Dissertations and Theses

Critical infrastructure systems such as transportation networks serve as the lifelines of modern society, supporting economic activity and ensuring access to critical services. Their disruption under extreme events can produce consequences extending far beyond physical damage to individual assets. In transportation networks for instance, failures of critical assets such as bridges and tunnels can reduce accessibility of communities, limit freight capabilities for commerce, and increase travel distance and travel time of road users. These consequences associated with the system functionality loss are tied not only to the physical vulnerability and failure of individual assets, but also to the system configuration …

Measurement Of Pollution Emissions From Natural Gas Stoves: Preparation For An Induction Cooktop Intervention Study, Jessica Zanella Lorensi

Dissertations and Theses

Humans spend ∼90% of their time enclosed in buildings. Indoors environments can be a source of pollutant which can affect health and productivity. Appliances that combust fossil fuels indoors, like stoves, are a critical source of a range of pollutants, like carbon monoxide (CO) and nitrogen dioxide (NO₂). In the US, the usual cooking fuel is natural gas (NG), presented in more than 30% of households in the country. Some studies in the literature linked cooking pollutants, including those specific to gas combustion, to various health conditions, including heart and respiratory diseases. Nitrogen dioxide, for example, can be …

What Drives Blockchain Technology Adoption? A Meta-Analysis Across Tam, Tpb, And Utaut Frameworks, Amir Rahmani, Roohollah Ahmadi, Tugrul Unsal Daim, Mehdi Zamani, Dilek Ozdemir

Engineering and Technology Management Faculty Publications and Presentations

Research on blockchain adoption has expanded rapidly, with most studies conceptualizing adoption as behavioural intention. Technology adoption models, such as the Technology Acceptance Model (TAM), the Theory of Planned Behavior (TPB), and the Unified Theory of Acceptance and Use of Technology (UTAUT), are commonly applied to explore blockchain technology adoption (BTA). However, empirical results from the 12 hypotheses associated with these models remain fragmented and, at times, inconsistent, with limited comprehensive quantitative integration. To address this gap, the present study performs a meta-analysis to evaluate the degree and direction of these hypotheses systematically. In accordance with PRISMA guidelines, 149 quantitative …

Book Review Of, Beyond Techno-Economic Diffusion: A Systematic Review And Socio-Technical Audit Of Agent-Based Models Of Rooftop Solar Pv Adoption, Yavuz Unal, Mehmet Kayalica, Denizhan Guven

Engineering and Technology Management Faculty Publications and Presentations

Agent-based modelling (ABM) is increasingly used to analyze rooftop solar photovoltaic (PV) diffusion, yet it remains unclear how existing models operationalize socio-technical mechanisms such as peer effects, grid constraints, policy uncertainty, and energy justice. This systematic review evaluates ABM architectures for rooftop PV diffusion through a three-layer evidence design: a mapping of 876 publications (2000–2025), a core set of 101 ABM-related studies, and structured coding of 50 focal ABMs using the Spatial–Economic–Mechanistic–Policy–Justice (S-E-M-P-J) framework, which tests whether mechanisms are formally implemented rather than narratively invoked. The coding reveals an uneven architecture: behavioural mechanisms are nearly universal (96%) and policy representations …

Storm Surge And Tides In Convergent Estuaries: The Case Of Extratropical Storm Merbok In Alaska, Steven Dykstra, Stefan Talke, David A. Jay, Matthew Lobo, Silvia Innocenti, Pascal Matte

Civil and Environmental Engineering Faculty Publications and Presentations

Coastal floods are composed of multiple drivers that interact with coastline geometries and are difficult to differentiate. To investigate the effects of basin shapes on storm surge and tides, we study the landfall of ex-Typhoon Merbok in the east Bering Sea, Alaska. Water levels at 34 stations are detided with a new tide wavelet tool, CWT_Multi (Lobo et al., 2024), and the spatial and temporal shifts in tides and surge are interpreted via long-wave theory. Results show nonstationary semiannual trends in tidal constituents due to ice effects and large interannual variability in mean-sea level (20-40 cm). After removing non-stationary tidal …

Spatial Structure And Energy Content Of Wakes Behind Single And Arrayed Undulated Cylinders, Taiga Naomi Drucker-Boisvert, OndˇRej FerˇCák, Jérémie Auzoux, Sarah E. Smith, Zein Sadek, Rowan Moore, Christain T. Murphy, Trevor Dunt, Jennifer A. Franck, Raul Bayoan Cal

Mechanical and Materials Engineering Faculty Publications and Presentations

Biologically inspired undulated cylinder geometries significantly influence wake structure and vortex-induced vibrations in turbulent flows, yet the underlying mechanisms are not fully understood. It is further unknown how these influences extend to multi-cylinder arrays, where interacting wakes accumulate and mix. This study examines the wake characteristics of an undulated cylinder and a smooth elliptic cylinder in single- and multi-cylinder array configurations, using particle image velocimetry and proper orthogonal decomposition (POD). Relative to the smooth elliptic cylinder, the undulated geometry induces pronounced spanwise-axial variability, characterized by enhanced near-wake mean momentum and weak far-wake signatures, consistent with reduced turbulent kinetic energy. While …

Improving The Fpga Radio Design Cycle: Implementing Dvb-S2 Modulation Using Verilator And Gnu Radio, Seth Pellegrino

Dissertations and Theses

In embedded digital radio systems, a central challenge is meeting the real-time throughput required to process the samples--especially for space-bound ultra-wideband SDRs which must handle more than 100 Gbps entirely onboard. An FPGA's programmable logic offers sufficient potential, but realizing a particular radio flow is a project usually fraught with defects and long turnaround times. We simulated Verilog modules in a custom harness that adapted a Verilated model to GNU Radio, which allowed for breaking down a complicated radio flow (here, DVB-S2 modulation) into a series of well-bounded problems each with clear criteria for success. The framework, built on open …

Theoretical Model To Predict The Flexural Response Of Concrete Beams Pre-Tensioned With Cfrp Rods Considering Cfrp Slippage Effects, Yasir Saeed, Karrar Al-Lami, Franz Rad

Civil and Environmental Engineering Faculty Publications and Presentations

The overwhelming costs of maintenance for reinforced concrete structures due to steel corrosion have motivated researchers to look for alternatives. One of the promising alternatives is Fiber Reinforced Polymer (FRP). Among FRP materials, Carbon FRP (CFRP) is the most attractive material for prestressed concrete members due to its high tensile strength and modulus of elasticity. Previous studies investigated the use of CFRP in prestressed concrete through experimental tests and theoretical analysis. However, there is a significant need for more experimental data to develop an accurate model that can accurately predict the behavior of CFRP prestressed concrete beams. In the current …

Understanding Structural Risk: Seismic Demand For Low-Fill Slender Fuel Tanks, David Yang, Sam Anderson

Civil and Environmental Engineering Faculty Publications and Presentations

Older fuel storage tanks, such as those in Oregon's CEI Hub, present significant seismic vulnerabilities, prompting proposals to limit storage capacity as a transitional risk mitigation measure before more permanent retrofitting actions. However, a critical knowledge gap exists regarding the applicability of standard analysis methods, like API 650, to low-fill conditions. This study utilizes the Veletsos-Yang iterative fluid-tank interaction procedure to evaluate the seismic demand of low-fill slender tanks. The analysis reveals that low-fill slender tanks exhibit slightly longer impulsive periods compared to fully-filled tanks with identical fill-height to radius ratios. Furthermore, the fixed roof mass of a low-fill tank …

Seasonal Changes In Sediment Sound Speed Profiles, Charles W. Holland, Chad Smith, Tim Sonnemann

Electrical and Computer Engineering Faculty Publications and Presentations

Marine sediment sound speed profiles in the upper ten meters are generally assumed to be constant with time. Models predict that substantive changes occur because of thermal conduction from seasonally varying bottom water temperature. However, definitive measurements have been lacking. In this work, sediment sound speed profiles obtained during different seasons show significant differences in the upper 9 m of mud at the New England Patch. Gradients in late March 2017 are 6.0 s−1 and in early October 2025, 2.6 s−1. This change is shown to have a significant impact on acoustic propagation.

Fuel Tank Seismic Stability Program-Informed Displacement Maps Of Portland's Critical Energy Infrastructure Hub, Ana Tijerina Esquino

Dissertations and Theses

Oregon's Critical Energy Infrastructure (CEI) Hub in northwest Portland contains a large portion of the state's liquid fuel storage and distribution capacity and is located in an area susceptible to liquefaction and earthquake-induced permanent ground deformation during a Cascadia Subduction Zone earthquake. Initial Seismic Vulnerability Assessments submitted under Oregon's Fuel Tank Seismic Stability program provide valuable facility-specific information, but the assessments vary in subsurface characterization, treatment of fine-grained soils, ground motion selection, and deformation estimation methods. This variability complicates interpretation of regional seismic risk and motivates a consistent corridor-scale analysis.

This thesis develops CPT-informed displacement estimates for representative cross sections …