Engineering Commons^™

Sensorless Control Of Pmsm Based On An Improved Super-Twisting Sliding-Mode Observer, Shiyu Chen, Xinmin Chen, Xionglong Hu, Heng Wang, Yepeng Han, Jiajie Chen

Journal of System Simulation

Abstract: To address the chattering in back electromotive force estimation and the gain mismatch across a wide speed range when using a conventional super-twisting sliding-mode observer in the sensorless control system of a permanent-magnet synchronous motor, this paper proposed an improved adaptive-gain super-twisting sliding-mode observer. A linear correction term was introduced into the super-twisting algorithm and integrated with a gain adaptation law based on speed feedback, enabling the system to achieve finite-time convergence and high-precision back electromotive force estimation over a wide speed range. A variable-gain adaptive complex-coefficient filter was constructed to effectively suppress the harmonic components in the observed …

Line Spectrum Enhancement Technology Based On Second-Order Vector Hydrophone, Zhengkai Wang, Yirong Yu, Qing Hu

Journal of System Simulation

Abstract: In view of the problem of limited detection of line spectrum signals in low signal-to-noise ratio underwater environments, a spatial-temporal cooperative line spectrum enhancement technology based on a two-dimensional second-order vector hydrophone was proposed. A receiving signal model of the two-dimensional second-order vector hydrophone was established to clarify the spatial characteristics of its output signals. For spatial signal processing, the signals from each channel of the vector hydrophone were fused to suppress noise, and a channel combination method with high spatial directivity gain was proposed to achieve spatial processing gain. For temporal signal processing, an adaptive line spectrum enhancer …

Dodaf-Opm-Sd Cross-Layer Automated Mapping Method Based On A Unified Semantic Bridge, Lei Cheng, Gang Xiao, Binbin Wang, Siming Peng, Haozhe Liang, Xiangwu Gong

Journal of System Simulation

Abstract: To address the problems of the inability of DoDAF views to directly drive simulations and the insufficient cross-layer semantic alignment and consistency verification, a DoDAF-OPM-SD cross-layer semantic automated/semi-automated mapping and verification method was proposed in this paper. Targeting tactical/operational-level problems dominated by "conservation+feedback+time delay", the proposed method reduced manual mapping under expert adjudication based on a "minimal executable view set". The object-process methodology served as a semantic bridge to map architectural elements into the stock-flow-feedback structures of system dynamics; semantic embedding disambiguation, integer programming harmonization, and K-nearest neighbor parameter completion were integrated; end-to-end traceability was connected through traceability identifiers, …

Three-Dimensional Gaussian Reconstruction Of Large-Scale Scenes Under Multi-View Geometry Constraints, Haohao Cui, Yanqiang Di, Qing Liu, Xianguo Meng

Journal of System Simulation

Abstract: To enhance the geometry reconstruction quality of the GS algorithm in large-scale scene reconstruction, an optimization method constrained by multi-view geometry reconstruction results was proposed. 2D Gaussian planes were used as geometric primitives to overcome depth anisotropy, and dense depth maps generated by DUSt3R and aligned by sparse point clouds were introduced as constraints. By designing a multi-stage optimization strategy that decouples geometry and rendering, the gradient conflict problem in multi-objective training was solved. Experiments on the MatrixCity dataset indicate that the method surpasses comparison methods in related indicators of geometry reconstruction quality and rendering quality in large-scale scenes. …

Design And Implementation Of Hdrt Real-Time Simulation System, Huiji Zheng, Guangsen Wang, Qing Liu, Kang Wang, Zhiwei Wang, Zhenyu Zhang, Shuo Wang, Zhu Liu

Journal of System Simulation

Abstract: In view of the real-time simulation requirements of large-scale complex systems such as power electronics, a hidden dragon real-time(HDRT) simulation system was developed. The strict time constraints of simulation tasks were guaranteed based on a resource-dedicated real-time scheme, supporting fixed-step and multi-rate simulations from the second level to the hundred-nanosecond level. A hybrid CPU-field programmable gate array(FPGA) architecture was adopted to accelerate computation. The system could utilize multiple simulators for parallel simulation and realized microsecond-level real-time data interaction between simulators through a dedicated PCIe switch. A single simulator could be expanded through I/O interface equipment, supporting a maximum input …

Numerical Simulation Of Water Tank Solidification In A Firefighting Aircraft Under High-Altitude Cold-Soak Conditions, Guanmian Liu, Zhihang Cheng, Hejun Qin, Kangzhi Yang, Qing Wen, Kun Gao

Journal of System Simulation

Abstract: A systematic numerical simulation study was conducted to address the issue of internal water tank solidification in firefighting aircraft under high-altitude low-temperature conditions. Based on computational fluid dynamics methods, a solidification-melting model considering fluid-structure interaction heat transfer and phase change processes was adopted. Through reasonable simplification of the complex geometric model, a quasi-three-dimensional computational model suitable for engineering analysis was developed. The influence laws of key parameters, including high-altitude cold-soak temperature, ground initial water temperature, and cold-soak time, on the freezing characteristics of the water tank were investigated. Combining with the parameter influence laws, a safety criterion using the …

Optimization Of Node Deployment For Three-Dimensional Heterogeneous Wsn In Elongated Structural Space, Jiguang Yang, Jiuyuan Huo, Fang Cao, Cong Mu

Journal of System Simulation

Abstract: To achieve effective coverage of key monitoring points in an elongated structural space, a heterogeneous wireless sensor network(HWSN) deployment optimization method combining the virtual force algorithm(VFA) and multi-strategy improved whale optimization algorithm(MSIWOA), namely HVF-MSIWOA, was proposed. A dynamic adaptive weight mechanism and a t-distribution perturbation operator with heterogeneous degrees of freedom were designed, enabling the whale optimization algorithm(WOA) to balance global exploration and local exploitation and jump out of local optima; combining the topological characteristics of the elongated space and node density distribution, an adaptive virtual force distance threshold between heterogeneous nodes was constructed; the mapping relationship between network …

Combat Effectiveness Evaluation Of Anti-Ship Missiles For Intelligent Autonomous Recognition, Long Zhang, Xuanming Feng, Zhen Lei, Bo Yang, Ying Wang

Journal of System Simulation

Abstract: To address the core issues of poor adaptability of static fusion strategies in existing recognition models, as well as the simplistic evaluation system and its disconnection from dynamic confrontation requirements, a practical four-dimensional evaluation system encompassing "recognition accuracy, antijamming stability, decision timeliness, and modal complementarity" was constructed, and an operational effectiveness composite index (OECI) capable of dynamically adapting to tactical scenarios was proposed. A multimodal dynamic attention fusion network (MDA-Net) for anti-ship missiles in complex confrontation environments was designed. Through heterogeneous feature decoupling, dynamic weighting of cross-modal attention, and a hierarchical gating decision mechanism, the autonomous evaluation and adaptive …

Infrared Image Generation Method Based On Improved Cyclegan, Qiqi Jin, Xiang Zhang, Li Gao, Lin Zhang, Junliang Yan, Peiyao Li

Journal of System Simulation

Abstract: To address the problems in current infrared image generation such as insufficient contrast between target and scene, excessively large discrepancies from real scenes, indistinct thermal source features, and great difficulty in constructing measured infrared image datasets, an improved CycleGAN-based infrared image generation method was proposed. By optimizing the network structure of the generator and adding a non-local module and a CBAM convolutional attention mechanism into the generator, the extraction capability of CycleGAN for infrared features was enhanced, enabling the network to capture the subtle features of targets more accurately; a perceptual loss function was introduced to improve the detail …

Evaluation Of Dredged Sediments As A Partial Replacement For Fine Aggregate In Mortar And Concrete, Ashish Gautam

Graduate Theses and Dissertations (2019 - present)

The feasibility of using dredged sediment from the Mobile River as a partial replacement for fine aggregate in mortar and concrete was investigated through a series of laboratory characterization and performance evaluation. Three dredged sediment samples (A, B and C) were initially examined, and Sample A was selected for further evaluation due to its closer resemblance to natural fine aggregate. This sample exhibited lower moisture content, higher sand equivalent values, higher specific gravity, and lower absorption. Mortar mixtures with 0, 10, 20, 30, 50, 75 and 100% dredged sediment replacement showed decreasing workability as the replacement level increased. The 20% …

Human-Centered Electric Vehicle Adoption Framework For Smart Mobility: Modeling Perceived Range And Charging Anxiety As A Psychological Barrier, Fatemeh Nazari, Abolfazl (Kouros) Mohammadian, Thomas Stephens

Civil Engineering Faculty Publications

Electric vehicles (EVs) offer a transformative pathway toward reducing the environmental, economic, and health-related externalities of internal combustion engine vehicles in urban settings. Despite substantial advances in battery technology, charging infrastructure expansion, and supportive policy incentives, EV penetration remains limited which poses challenges for smart and sustainable mobility planning. A critical yet insufficiently modeled barrier to adoption lies in the psychological perceptions surrounding electric driving range and charging reliability, which is commonly framed as “range anxiety,” but more broadly reflecting perceived range and charging anxiety. To address this gap, this study introduces a latent psychological construct capturing individuals’ perceived range …

Machine Learning For Predictive Energy And Emissions Modeling Of Vehicles And Power Grids In The United States, S M Tanvir Faysal Alam Chowdhoury

Dissertations

The environmental benefits of electric vehicle (EV) adoption depend on more than replacing internal combustion engine vehicles with electric powertrains. EV adoption reshapes electricity demand, interacts with regional generation mixes, and influences travel behavior and congestion, creating a coupled transportation-energy system in which vehicle and power-plant emissions must be evaluated together. This dissertation develops machine-learning frameworks for predicting energy consumption and emissions from vehicles and power grids under rising EV adoption. The first component forecasts grid emissions from EV charging. Using simulation data from NREL's Cambium database, a Prophet-based time-series framework predicts carbon dioxide, nitrous oxide, and methane emission rates …

Understanding The Correlation Between Prediction Performance And Trust In Ai Through Scenario-Based Tasks, Likhitha Kammara

Theses and Dissertations

Trust in artificial intelligence is commonly assessed through self-reported scales or behavioral reliance, yet behavioral reliance is retrospective and can only be observed after a decision has already been made. This thesis examines whether prediction accuracy — a user's ability to predict what an AI system will recommend before its output is revealed — can serve as a prospective correlate of trust in the same empirical sense as behavioral reliance. The study was conducted in two phases using scenario-based AI decision tasks across disaster response, healthcare, and infrastructure restoration contexts, employing a between-group design in which participants either predicted AI …

Predicting Student Belonging In Computing Education: A Multimodal Machine Learning Approach Using Eeg And Survey Data, Hannah Moshtaghi

Master's Theses

Measuring students’ sense of belonging, characterized by feelings of acceptance, inclusion, and encouragement from teachers, remains a significant challenge in computing education. Prior research has associated this multidimensional construct with positive academic outcomes and has identified instructors’ growth- and fixed-mindset messaging as a potential influence. However, belonging is a complex and deeply personal experience that is difficult to capture through direct observation alone. Current measurement methods rely on self-report surveys, which may not capture every aspect of an experience that can also involve emotional and cognitive responses.

This thesis investigates whether combining EEG data recorded during a belonging questionnaire with …

Synthesis And Characterization Of Carbon Quantum Dots And Gold Nanoparticles For Norovirus Biosensing Applications In Water Systems, Breanne Evans

Master's Theses

Rapid, reliable detection of viral pathogens remains a significant challenge across water-treatment and environmental monitoring systems, including drinking-water, wastewater, water reuse, and environmental surveillance applications. Waterborne viral contamination can pose substantial public-health risks, making early detection essential for protecting water quality and responding quickly to treatment failures or contamination events. Direct potable reuse (DPR) is one particularly demanding example because it requires continuous verification of treatment performance and the broader need for rapid virus monitoring extends across many water-treatment and environmental surveillance applications. Norovirus is a priority target because of its widespread occurrence in wastewater, environmental persistence, and exceptionally low …

Evaluating Machine Learning Models On Classification Of Novel Cyber Attacks In The Healthcare Domain, Promise Ehimen

Dissertations, Theses, and Projects

The increasing adoption of the Internet of Medical Things (IoMT) has improved healthcare delivery through connected medical devices while simultaneously expanding the cybersecurity risks facing healthcare organizations. Although machine learning based intrusion detection systems have demonstrated high detection accuracy, their ability to respond reliably to previously unseen cyberattacks remains uncertain. This study investigated how a Neural Network model and a Logistic Regression model classified novel cyberattacks within the IoMT environment. The Neural Network and Logistic Regression models were both trained and tested using a subset of the CICIoMT2024 benchmark dataset. The Neural Network achieved 99.82% test accuracy and a 0.94 …

Systematic Review Of The Institutionalization Of Service Learning In Higher Education, Wilmer Hernan Cruz Gutierrez

ASEAN Journal of Community Engagement

An increasing number of universities are integrating service-learning (SL) to fulfill their social mission. However, sustainable institutionalization of SL remains a persistent challenge. This study identifies and analyzes the factors, actors, and strategies that drive and inhibit SL institutionalization in higher education. Using the PRISMA 2020 guidelines, a systematic literature review analyzed 52 documents from seven academic databases (including WoS, Scopus, and ERIC). The findings were grouped into three sections: cultural (integration into institutional values/missions), process (articulation within teaching, research, and outreach), and structural dimensions (dedicated support entities). The results obtained reveal a reciprocal relationship where cultural alignment enables processual …

Digraphicsoft Sets And Bidigraphicsoft Sets: Directed And Bidirected Extensions Of Graphicsoft Modeling, Takaaki Fujita, Ajoy Kanti Das, Suman Das, Sankar Prasad Mondal, Volkan Duran, Mithun Datta

Neutrosophic Systems with Applications

Uncertainty has been modeled through a wide variety of mathematical frameworks, including fuzzy sets, neutrosophic sets, rough sets, and plithogenic sets. Among these approaches, soft sets offer a parameterized representation of uncertain information and have inspired numerous extensions, such as multisoft sets, double-framed soft sets, hypersoft sets, SuperHyperSoft sets, TreeSoft sets, ForestSoft sets, IndetermSoft sets, and IndetermHyperSoft sets.
This paper focuses on GraphicSoft Sets, which extend the classical soft-set framework by assigning a subset of the universe to each subgraph of an attribute graph. In this way, relationships among attributes are incorporated directly into the parameterized model. Building on …

Foundations Of Neutrosophic N-Semirings Theory And Structural Properties, Raja Muhammad Hashim, Muhammad Gulistan, Muhammad Shahzad

Neutrosophic Systems with Applications

In this paper the concept of neutrosophic n-semirings (S∪ I, ∗ ₁, ∗ _2, ∗ ₃,..., ∗ _n, ∗ _n+1) has been introduced. The substructure of n-semirings (S∪ I, ∗ ₁, ∗ _2, ∗ ₃,..., ∗ _n, ∗ _n+1) has been defined and some useful results have been proved. Moreover, in order to familiarize the readers with these concepts some worthy examples have been coined. The left, right and two sided ideals of neutrosophic n-semirings have been paid a special heed. Finally we have turned our discussion towards the compatible and congruence …

A Fuzzy–Neutrosophic Suitability Index For Selecting An Appropriate Reasoning Model Under Vagueness, Incompleteness, And Conflict, Nada A. Nabeeh, Ahmed Samy

Neutrosophic Systems with Applications

Fuzzy reasoning and neutrosophic reasoning are both used to handle uncertainty, but they are not intended for the same uncertainty structure. Fuzzy reasoning is suitable when uncertainty appears mainly as gradual vagueness, where a value may belong to a concept such as ``high risk'' or ``good performance'' to a certain degree. In this case, a membership value is often sufficient. Neutrosophic reasoning is more suitable when the problem also contains incomplete information, undecided evidence, or conflict between sources. In such cases, one membership degree may be too limited because it cannot represent support, rejection, and indeterminacy separately. This study introduces …

Evaluating Generative Ai-Based User Interfaces Using An Integrated Neutrosophic Multi-Criteria Decision-Making Framework, Nada Mohamed, Alshaimaa A. Tantawy

Neutrosophic Systems with Applications

User Interface (UI) design can be seen as an essential aspect of human-computer interaction (HCI) and makes communication easier between people and technology. In today's digital economy, interface quality has become one of the most important business concerns, since it has a direct impact on customer satisfaction and retention while affecting revenue. Although creating user-centered and accessible interfaces is crucial, doing so is a difficult and time-consuming process, which leads to burnout for many usability professionals. Although conventional artificial intelligence (AI) was utilized for design assessment and automation, the arrival of generative AI technology has created new possibilities for automated …

Neutrosophic Time-Truncated Acceptance Sampling Plans Based On The Exponentiated Weibull Distribution For Reliability Applications, Divya P.R., Preethi John

Neutrosophic Systems with Applications

Classical acceptance sampling plans require precisely specified parameter values, an assumption routinely violated by measurement uncertainty and gauge imprecision in practice. This article develops Neutrosophic Time-Truncated Acceptance Sampling Plans (N-TTASP) for the Exponentiated Weibull (EW) distribution by representing the scale parameter as a neutrosophic interval. The neutrosophic sample size n_N ∈ [n_L, n_U] and acceptance number c_N ∈ [c_L, c_U] are obtained by minimizing n_U subject to dual producer and consumer risk constraints on the neutrosophic Operating Characteristic interval. A new indeterminacy ratio η is introduced as a …

Enhanced Transdermal Immunization Via Solid-In-Oil Nanodispersions Incorporating Dendritic Cell-Targeting Peptide, Md Samiul Islam, Md. Shahin Ekka Sarker, Yoshirou Kawaguchi, Rie Wakabayashi, Noriho Kamiya, Muhammad Moniruzzaman, Masahiro Goto

Publications and Research

Transdermal immunization represents a promising needle-free alternative to conventional vaccination. However, efficient antigen delivery and robust immune activation remain major challenges. In this study, a solid-in-oil (S/O) nanodispersion system comprising a dendritic cell-targeting peptide (HR8), ovalbumin (OVA), and an adjuvant was developed for transdermal immunization. The HR8 peptide along with OVA was successfully incorporated into an S/O nanodispersion with an optimal hydrodynamic diameter of particles (< 200 nm) and exhibited stable physical properties for up to 90 days. In vitro and in vivo studies demonstrated enhanced antigen delivery with insignificant skin irritation in C57BL/6N mice. Moreover, in vivo transdermal immunization studies demonstrated that the addition of the HR8 peptide enhanced OVA-specific IgG responses (~1.5-fold). Notably, the HR8 peptide also promoted an approximately 2.5-fold increase in IgG2c levels, suggesting a shift toward a more T helper type 1-biased immune response, as reflected by an increased IgG2c/IgG1 ratio. Overall, these findings demonstrate that the incorporation of HR8 peptide into an S/O nanodispersion enables efficient transdermal antigen delivery and improved immunogenicity, highlighting its potential as a simple, non-invasive, and patient-friendly immunization strategy.

Emergent De Sitter Expansion And Closed Topology From The Cosmic Fabric Model As An Open Thermodynamic System: Resolving The Negative Bulk Modulus Paradox, T G. Tenev, C B. Ward, T F. Tenev, M F. Horstemeyer

Faculty Publications and Presentations

The Cosmic Fabric Model establishes a continuum-mechanics isomorphism to General Relativity by representing physical space as an elastic three-dimensional hyperplate embedded in a four-dimensional spatial bulk. Reproducing vacuum kinematics requires a vanishing P-wave modulus, which in turn implies a negative bulk modulus—an apparent thermodynamic instability in a closed system. This paradox is resolved by recasting the framework as an open system: the instability is not pathological but instead drives cosmic expansion. In this interpretation, the observable universe is a lower-energy solid formed through continuous solidification from a higher-dimensional precursor fluid. Using multiplicative kinematics from finite-growth mechanics, the model shows that …

Dynamic Reconstruction Engineering Of Anti-Corrosion Ni-Based Anodes For Alkaline Seawater Electrolysis, Yi-Gang Zhang, Wen-Wen Xu, Tian-Yu Zhang, Zhi-Yi Lu

Journal of Electrochemistry

Green hydrogen production via alkaline seawater electrolysis offers an environmentally sustainable and potentially cost-effective route to address both energy and climate challenges. Achieving long-term anode stability under complex ionic environments and industrial current densities remains a central bottleneck. Specifically, Ni-based anodes exhibit intense surface reconstruction during the oxygen evolution reaction, necessitating dynamic anti-corrosion strategies. This mini review systematically summarizes reconstruction engineering approaches to develop anti-corrosion Ni-based anodes of alkaline seawater electrolysis across increasingly complex ionic environments from simulated seawater to real seawater: (i) Cl^– dominated; (ii) Cl^– with co-existing oxyanions, and (iii) Cl^–  with co-existing Br^{– …}

Preparation And Performance Study Of In-Situ Self-Assembled Biphasic Smmn2O5-Nimn2O4 Composite Cathode, Neng-Chu Xia, Yu Zhou, Qin Wang, Jia-You Zhang, Chun Yu, Yang Zhang, Wan-Bing Guan, Jian-Xin Wang

Journal of Electrochemistry

Mullite-structured oxides exhibit excellent oxygen reduction reaction activity, possess a low thermal expansion coefficient due to their unique crystal structure, and can eliminate the need for a barrier layer and simplify the preparation process as they contain no alkaline earth elements. Thus, they hold great promise as novel cathode materials for solid oxide fuel cells. In this work, a mullite-spinel-structured SmMn₂O₅-NiMn₂O₄ (SMO-NMO) composite cathode was one-step synthesized via a solid-liquid composite route, and its in-situ self-assembly enabled good compatibility with the electrolyte without any barrier layer. Characterization results showed that the SMO:NMO = …

In-Situ Stm Visualization Of Molecular Structural Evolution During Electrochemical Oxidation Coupling Of Para-Aminothiophenol On Au(111), Zi-Wei Ma, Tai-Rui Wu, An-Ni Zheng, Lai-Ke Chen, Yuan-Hui Xiao, Zhao-Bin Chen, Qing-Na Zheng, Jian-Zhang Zhou, Jia-Wei Yan, De-Yin Wu

Journal of Electrochemistry

Para-aminothiophenol (PATP) is not only a widely-used probe molecule in the field of surface-enhanced Raman spectroscopy (SERS), but also an important model molecule for interfacial reactions, exhibiting distinct photo- and electro-oxidation pathways, so that PATP is selectively activated under different external fields. The evolution of products and intermediates during electrochemical oxidative coupling remains unknown. In this study, we have investigated the dynamic electrochemical oxidation process of PATP on the Au(111) surface using cyclic voltammetry, electrochemical (EC)-SERS, and in situ electrochemical scanning tunneling microscopy (EC-STM). The results showed that PATP forms an unsaturated adsorption coverage on Au(111) in an acidic solution. …

Mapping And Modeling Threat-Evoked Brain States After Early Life Adversity, Taylor W. Uselman

Biomedical Sciences ETDs

Early life adversity (ELA) increases lifelong neuropsychiatric vulnerability. Yet how ELA reorganizes brain-wide activity and circuit coordination across later experience remains unclear. This dissertation tests the hypothesis that ELA alters adult brain-wide activity and responses to threat through disrupted coordination among neural systems that regulate emotional experience, including prefrontal-limbic and monoaminergic systems. Longitudinal manganese-enhanced MRI of adult mice exposed to standard or fragmented early care, combined with computational processing and statistical modeling, quantified brain states before, during, and long after innate predator threat. These studies established that acute threat evokes large-scale, distributed brain activity that evolves over time. ELA potentiates …

Multiscale Network Modeling Of Native And Modified Photosynthetic Light-Harvesting Complexes, Zane E. Armijo

Chemical and Biological Engineering ETDs

Photosynthetic light-harvesting complexes harvest solar energy and direct electronic excitations toward reaction centers with exceptional efficiency. This dissertation models the Fenna--Matthews--Olson complex of green sulfur bacteria, coupled to the PscA1 reaction center, as a chromophoric network. Forster resonance energy transfer theory, validated against numerically exact hierarchical equations of motion, was implemented in kinetic Monte Carlo simulations to resolve fine-grained excitation-transport pathways. The predicted charge-transfer efficiency of 77\% agrees with experiment, with the FMO2 monomer and its gateway pigment governing interfacial transfer. Systematic single, multi, and symmetry-preserving site removals, interpreted through Mobius inversion, identify critical pigments and show that cooperative effects …

Wildfire Impacts On Fluvial Hydrology From Watershed To National Scales, Paige G. Tunby

Civil Engineering ETDs

Wildfires alter the water quantity and quality in downstream river networks. Fires promote biodiversity, maintain habitat, and provide many ecosystem services in a fire-adapted landscape. However, changes in the natural fire regimes can alter ecosystem function and threaten the water security of impacted downstream communities. The magnitude, timing, and persistence of these impacts are difficult to predict due to the lack of high-resolution datasets with adequate coverage to evaluate spatiotemporal trends after a fire. This dissertation moves us beyond the status quo to evaluate post-fire fluvial responses across scales, from the event-scale impacts after the Hermit’s Peak-Calf Canyon wildfire in …