Digital Commons Network^™

Enhanced Adaptive Smith Predictor Control For Underground Coal Gasification With Long Time Delays, Tang Yang, Wu Qiong, Zhang Lei, Zhou Mingjun, Wan Min, Liao Zhuodong

Coal Geology & Exploration

Background Underground coal gasification (UCG) represents an in situ conversion technology used to convert solid coals into gaseous fuel. However, the reaction process during UCG exhibits significant time delays. Such a limitation will reduce the response capability of the UCG system and is prone to induce overshoot and oscillation, thereby increasing the system’s control difficulty and reducing its stability and dynamic performance. Method To address these issues, this study proposed an enhanced Smith predictor control algorithm based on a genetic algorithm and established a semi-physical experimental platform integrating a physical distributed control system DCS-Matlab for modeling. Using the platform, experiments …

Discovery And Implications For Ore Prospecting Of Gravitational Gliding Structures In The Lutang Coal-Based Graphite Mining Area, Hunan Province, China, Xiao Jincheng, Lu Jiang, Liu Zhiyu, Zhu Linying, Xiao Haibin, Li Long, Xiao Jing

Coal Geology & Exploration

Background Data from previous exploration and studies indicate that the Lutang coal-based graphite mining area in Hunan Province falls within the Lutang-Shatian synclinorium in terms of tectonic location, with coal-bearing strata dominated by the upper member of the Upper Permian Longtan Formation. Influenced by the intrusion of granites, coal seams adjacent to the Qitianling pluton on the eastern flank of the mining area have undergone contact metamorphism, forming coal-based graphite. Previous exploration results suggest that the Qitianling pluton has a maximum burial depth measured at an elevation of 0 m or less. However, with constant underground exposure in mines, previous …

Comparison Of Log-Based Coal Structure Identification Methods For Structurally Complex Areas: A Case Study Of The Huainan Mining Area, Zhang Zixin, Zhou Xiaozhi, Chen Xuehua

Coal Geology & Exploration

Objective CO₂ displacing coalbed methane (CBM) provides substantial environmental and energy benefits. However, differences in coal structures represent a key geological factor influencing the effectiveness of this technique. Constrained by the complex geological conditions for CBM occurrence and the impacts of multiple factors on the log responses of coal structures, traditional log-based methods for coal structure identification face challenges such as much human intervention, complex feature engineering, and poor adaptability. This study aims to achieve effective identification of complex coal structures within a single coal seam. Methods An asymmetric convolution kernel-based convolutional neural network (CNN) model for coal structure …

Heterogeneity And Its Controlling Effect On Coalbed Methane Productivity For Deep Coal Reservoirs In The Northern Part Of The Eastern Margin Of The Ordos Basin, Xi Zhaodong, Tang Shuheng, Wu Jian, Zhang Songhang, Zhao Hang, Chen Jiang, Li Yanfei

Coal Geology & Exploration

Objective With the continuous advancement in the exploration and exploitation of coalbed methane (CBM), the focus of research and practices is gradually shifting from shallow to deep parts. Deep CBM, an important unconventional natural gas resource, has become a strategic replacement to ensure energy security and prompt industrial development in China. However, deep coal reservoirs exhibit strong heterogeneities, posing a core geological challenge to their efficient exploration and development. Methods This study investigated the deep No. 8 coal seam in the northern part of the eastern margin of the Ordos Basin. By integrating multiple technical methods, including geostatistics, spatial interpolation, …

Helium Origin And Primary Factors Controlling Helium Enrichment For Bauxite Gas Reservoirs In The Longdong Area, Ordos Basin, Chen Keyu, Wang Xiaofeng, Liu Wenhui, Zhang Dongdong, Li Xiaofu

Coal Geology & Exploration

Objective Significant breakthroughs have been achieved in the exploration of bauxite gas reservoirs in the Taiyuan Formation, Longdong area, Ordos Basin. Bauxites are generally considered to hold great helium generation potential due to their relatively high uranium (U) and thorium (Th) contents. However, there remains a lack of quantitative studies on their actual contribution to helium abundance in natural gas in the area. Methods To determine dominant helium source rocks and mechanisms behind helium enrichment, this study investigated the bauxite gas reservoirs within the Taiyuan Formation in the Longdong area. Through analyses of the composition, carbon isotopes, and noble gas …

Damage And Fracture Field Evolution In The Overburden Of An Extremely Thick Coal Seam Under Multi-Layered Fully Mechanized Top-Coal Caving Mining, Zhang Cun, Fan Baiqiang, Ren Yiming, Zhao Ruihang, Peng Baoshan, Pan Weidong, Liu Shiqi

Coal Geology & Exploration

Objective Multi-layered fully mechanized top-coal caving mining represents a primary method for exploiting extremely thick coal seams. Quantitatively characterizing the damage patterns and fracture field evolution characteristics of the overburden in stopes subjected to high-intensity layered mining is critical to the safe production of coal mines. Methods The extremely thick B1 coal seam (average thickness: 53.59 m) in the No. 2 mine of the Dajing mining area in the Zhundong coalfield was selected as the engineering background. By integrating physical simulation using similar materials and numerical simulation, this study revealed the geometric and fractal characteristics of damage to the overburden …

Triaxial Shear Test-Derived Strength Model Of Deeply Buried Frozen Calcareous Clay Incorporating The Effect Of Unfrozen Water Content, Xing Lezhang, Rong Chuanxin, Chang Lei, Wang Bin, Deng Jiyuan

Coal Geology & Exploration

Background The Huanghuai mining area represents an important coal base in eastern China. However, the Cenozoic calcareous clay in the area exhibits high plasticity, low permeability, and potential expansion and deformation during freezing, leading to unstable freezing performance. Consequently, artificial ground freezing (AGF) in the area generally faces a risk of cost surge or out of control due to the excessive thickness or limited strength of frozen walls.Methods This study investigated calcareous clay remolded based on soil samples from the Huanghuai mining area. Using a low-field nuclear magnetic resonance (LF-NMR) spectrometer and a high-pressure triaxial system, this study systematically …

Bp-Kan-Based Inversion Imaging For Borehole Resistivity Method And Its Application, Xu Zhongzhong, Yin Longlong, Cheng Jiulong, Xu Jinpeng, Lu Cunjin, Zhao Hongpeng

Coal Geology & Exploration

Objective In the monitoring of coal seam mining-induced deformation and failure of surrounding rocks, the borehole resistivity method stands out due to its capacity for dynamic, three-dimensional (3D) full-space measurements. However, conventional resistivity inversion for the method is generally carried out using the least squares algorithm, leading to limited accuracy in practical engineering. In recent years, neural network-based inversion has demonstrated the potential for addressing this challenge, while its performance is yet to be further improved. Methods In this context, inversion imaging based on a back propagation-Kolmogorov-Arnold network (BP-KAN) was proposed for the borehole resistivity method, aiming to accurately monitor …

Design Of An Intelligent Failure Diagnosis And Early Warning System For Tunnel Drilling Rigs In Coal Mines, Song Haitao, Zhang Naiwen, Han Jian, Wu Min

Coal Geology & Exploration

Objective In coal mines, harsh environments and complex geological conditions underground lead to frequent failures of tunnel drilling rigs. However, conventional techniques for failure diagnosis and early warning suffer from limitations in diagnostic accuracy, real-time performance, and interpretability. Therefore, these techniques are insufficient for both the rapid identification of the anomalous status of tunnel drilling rigs and the early warning of their potential failures. Methods Considering the complex underground environments in coal mines, this study developed an intelligent failure diagnosis and early warning system for tunnel drilling rigs in coal mines, placing a particular emphasis on key technologies for failure …

A Method For Optimizing The Digital Twin Model Of The Mechanical-Electro-Hydraulic System Of Cantilever Tunnel Boring Machines, Wang Yan, Jia Zeyu, Zhao Yihui, Wei Shirui, Zhang Xuhui, Zhao Youjun, Han Xiao

Coal Geology & Exploration

Objective Cantilever roadheaders represent roadway tunnelling equipment that integrates the deep coupling of mechanical, electrical, and hydraulic systems, and their control accuracy directly determines the forming quality of roadways.Methods Cantilever roadheaders involve nonlinear mechanical motion, hydraulic control, and cutting load, rendering it challenging to establish accurate control models. Using the philosophy of digital twin modeling, this study developed a method for optimizing the digital twin model of the mechanical-electro-hydraulic system of cantilever roadheaders based on virtual-physical consistency evaluation. Specifically, a digital twin model of the mechanical-electro-hydraulic system was developed using multi-domain co-simulation between AMESim and Simulink. This model allows …

Iron-Decorated Graphene Nanoplatelets Produced By Atmospheric-Pressure Ferrocene Pyrolysis As Nano-Additives For Cement Mortars, Harutyun Gyulasaryan, Manoj Chhetri, Karen S. Martirosyan, Nelli Muradyan, Hovsep Hoveyan, Manuk Barseghyan, Aram Manukyan

Physics & Astronomy Faculty Publications

This study examines iron-based graphene nanoplatelets (Fe-GNPs), synthesized through a modified ferrocene pyrolysis route, as hybrid nano-additives for cement mortars. The nanomaterial was characterized by scanning electron microscopy, X-ray diffraction, Brunauer–Emmett–Teller surface area analysis, and thermogravimetric analysis, confirming a graphitic carbon network decorated with crystalline α-Fe nanoparticles. Mortars containing 0.001, 0.01, 0.05, and 0.1 wt.% Fe-GNPs, with and without surfactant-assisted ultrasonication, were tested in flexure and compression after 7 and 28 days of curing. The results showed a clear concentration-dependent response, with 0.01 wt.% yielding the highest strength gains. At 28 days, this dosage increased flexural strength by 14.5% without …

Culmination Of The Arts And Stem To Enhance Creativity And Promote Learning, Kaleigh Evans

Physics and Astronomy Summer Fellows

In this work, we investigate the results from a survey, issued to a course in “Stained Glass” (n= 23 students). Major findings include that the introduction of a problem-based learning (PBL) course in the arts of stained glass may support high demand skills such as interdisciplinary conceptual learning as well as soft skills such as scientific confidence, interdisciplinary transfer, and collaborative learnings. A journal paper draft was completed and will be submitted this Fall. This summer, work was also done to establish a guide to modeling and 3D printing to help establish and grow a makerspace on campus for use …

Minerals Rock!: Improving Audience Engagement And Interest In Stem Through Enhancement Of The In-Person And Online Mineral Collection At Ursinus College, Juliette Lyons

Environment and Sustainability Summer Fellows

Museums are a vital source of educational resources for the general public. They provide information on a variety of topics and disciplines and encourage visitors to be excited about and engaged in learning something new. As we work to comprehend key topics such as climate change, it is especially important for the broader public to better understand science, including geology. While the geological collection at Ursinus, Pieces of Earth’s History, is not in a museum, implementing methods that museums use can improve the reception of the collection. Through the application of research gathered through articles, journals, books, and talking with …

Can Machines Testify? Llms And The Boundaries Of Testimonial Epistemology, Michael J. Cummins

Philosophy Summer Fellows

As Large Language Models and AI chatbots become increasingly prevalent, pressing questions are raised about whether beliefs formed through LLM interactions carry the same epistemic weight as beliefs formed through human testimony. How we answer this question depends on whether LLMs can function as testifiers, a role which is typically assumed to require a human or human-like agent. This assumption has gone largely unexamined, yet its consequences are significant: if LLM outputs cannot constitute testimony, then the justificatory tools of testimonial epistemology are unavailable to any beliefs formed through LLM interaction. This paper challenges that assumption. It first argues that …

Search For Planetary-Mass Ultracompact Binaries Using Data From The First Part Of The Ligo–Virgo–Kagra Fourth Observing Run, The Ligo Scientific Collaboration, The Virgo Collaboration, The Kagra Collaboration, Marc Favata, Shoan Ghosh, Rodica M. Martin

Department of Physics and Astronomy Faculty Scholarship and Creative Works

We present a search for gravitational waves from inspiraling, planetary-mass ultracompact binaries using data from the first part of the fourth observing run of LIGO, Virgo, and KAGRA. Finding no evidence of such systems, we determine the maximum distance reach for such objects and their merger rate densities. Then, we identify classes of primordial black hole mass distributions for which these rate limits can be translated into relevant constraints on the mass distribution of primordial black holes, assuming that they are all composed of dark matter, in the mass range [10−6,10−3]⁢𝑀⊙. Our constraints for the class of primordial black hole …

Search For Planetary-Mass Ultracompact Binaries Using Data From The First Part Of The Ligo–Virgo–Kagra Fourth Observing Run, A. G. Abac, I. Abouelfettouh, Teviet Creighton, Mario C. Diaz, Raul Alberto Espinosa Perez, J. Lawrence, Francisco Llamas Villarreal, Soma Mukherjee, Volker Quetschke, Miriam Ramos Arevalo, Wenhui Wang

Physics & Astronomy Faculty Publications

We present a search for gravitational waves from inspiraling, planetary-mass ultracompact binaries using data from the first part of the fourth observing run of LIGO, Virgo, and KAGRA. Finding no evidence of such systems, we determine the maximum distance reach for such objects and their merger rate densities. Then, we identify classes of primordial black hole mass distributions for which these rate limits can be translated into relevant constraints on the mass distribution of primordial black holes, assuming that they are all composed of dark matter, in the mass range [10−6,10−3]⁢𝑀⊙. Our constraints for the class of primordial black hole …

Sustainable Consumer Behavior Modeling: A Complex-Systems Approach To Neuromarketing, Preethi Nanjundan, Nupoor Sanjay Bhute, Ragini Topre, Lijo Thomas

Northeast Journal of Complex Systems (NEJCS)

This study examines the application of complex-systems modeling to neuromarketing data for gaining deeper insights into the mechanisms underlying sustainable consumer behavior. It investigates how neural and biometric responses, interpreted through a systems-based perspective, can uncover dynamic interactions, feedback mechanisms, and emergent behavioral patterns influencing sustainable purchase decisions. The research explores the impact of sustainability-oriented marketing stimuli on long-term behavioral intentions by emphasizing the interconnected roles of cognitive processing, emotional engagement, implicit associations, and collective consumer dynamics. Through simulation-based modeling and structural analysis, the study demonstrates how subconscious neural responses and affective mechanisms mediate the relationship between marketing interventions, consumer …

Editorial: Participatory And Just Governance: Empowering Local And Indigenous Communities, Melissa Haeffner, Maiko Sakamoto, Jenia Mukherjee, Hong Quan Nguyen, Soyo Takahashi

Environmental Science and Management Faculty Publications and Presentations

The papers in this Research Topic (RT) extend insights on the roles of social relations, institutional arrangements, Indigenous ways of knowing, local knowledge, and decisionmaking participation in shaping water governance and practice. Despite efforts to predict flows and possible hazards, we continue to observe “unintended consequences” when humans interact with waterscapes. What we often learn, we argue, is that what appears “unintended” often reflects a deliberate architecture of exclusion; one that becomes legible only when social power relations are placed at the center of analysis alongside hydrological variables. Doing so may illuminate where injustice complicates intentions and what difference participatory …

Using A Cell Flux Model To Investigate Phytoplankton Growth And Macromolecular Allocation Under Iron Limitation, Margaret Bernish, Meng Gao, Jongsun Kim, Benoit Pasquier

School of Earth, Environmental, & Marine Sciences Faculty Publications

Global biogeochemical models are powerful tools used to interpret observations and empirical data, create hypotheses, and make predictions. Many of these models, however, represent marine microbes as static stoichiometric reactions that convert nutrients into biomass. To better constrain the biological processes that control nutrient cycling in the global ocean, we extend the Cell Flux Model of Phytoplankton to explore the impact of dissolved iron concentration on the allocation of macromolecules and elemental ratios within phytoplankton cells. This model is supported by data obtained from a range of incubation experiments conducted with phytoplankton of varying species and size categories. Model output …

Glassy Magnetic Freezing Of Interacting Clusters In Materials Related To The Lk-99 Family, Serafim Teknowijoyo, Domenico Napoletani, Vahan Nikoghosyan, Armen Gulian

Mathematics, Physics, and Computer Science Faculty Articles and Research

We report reproducible magnetization anomalies appearing below room temperature in copper-doped apatite materials belonging to the LK-99 family synthesized via hydrothermal methods. These anomalies are observed consistently across samples prepared under comparable conditions. Although the extracted Mydosh parameter lies within the range often associated with vortex-glass behavior in superconductors, a detailed analysis of DC magnetization, AC susceptibility, field dependence, and magnetic memory effects demonstrates that the observed phenomena are not related to superconductivity. Instead, the data are consistent with glassy magnetic freezing of interacting clusters. Compositional and structural analysis identifies covellite (CuS), one of the constituent phases in these multiphase …

Stylometric And Formal Patterns In The Scholarly Impact Of Scientific Literature, Joshua Ange, Eric Godat, Rajani Sudan

SMU Journal of Undergraduate Research

Scientific communication is typically tied to promoting public engagement and interest in science, increasing scientific literacy, and playing an essential role in policymaking. The success of public communication of scientific findings is largely associated with secondary characteristics of research (e.g. the style of writing and presentation), rather than the primary content or research quality. But it is unclear to what extent the success of scientific literature intended for working scientists is influenced by those same secondary characteristics. Does the writing style of scientific articles impact their success in academic spheres? In this study, we explore the stylometric and formal characteristics …

Image Fusion Based On Deep Learning With Different Locations And Sizes Of Objects, Baneen Al-Kalabi, Tawfiq Al-Assadi

Journal of Intelligent Informatics, Networking, and Cybersecurity

Multi-focus image fusion combines partially focused images into a single all-in-focus composite. Existing object-based methods assume precise spatial and scale alignment across source images, an assumption that frequently fails in Misaligned Multi-Focus Dataset scenarios due to camera displacement and focal length variation. This paper proposes a novel training-free, object-aware fusion framework to address this limitation through a five-stage pipeline: YOLOv8x detection, SAM2-L segmentation, LoFTR correspondence matching, a novel Scale-Aware Area Resize Algorithm, and GLCM-guided MSB/LSB bit-level fusion. The framework was evaluated on the EDMF benchmark (20 image pairs, synthetically modified to simulate Misaligned Multi-Focus Dataset shifts) and a Misaligned Multi-Focus …

Lossless Medical Image Compression Using Integer Discrete Wavelet Transform With Adaptive Subband Differencing And Context-Adaptive Entropy Coding, Rasha F. Nadhim, Ibrahim Adel Ibrahim, Ashwaq T. Hashim

Journal of Intelligent Informatics, Networking, and Cybersecurity

From transform-domain decorrelation and adaptive entropy coding, we propose a method for efficient lossless compression of medical images in this work. We implement the Integer Discrete Wavelet Transform (IDWT) to decompose the input image into four subbands of LL, LH, HL, HH, encompassing approximation and directional detail elements, in the initial implementation. It also removes spatial redundancy in image information and decomposes image information into a less correlated and more sparsely distributed set of coefficients. To decrease redundancy further, it proposes a subband-dependent differencing scheme, which decorrelates neighbouring wavelet coefficients with directional prediction. So horizontal differencing is done on LH, …

A Blockchain-Integrated Federated Learning Model And Autoencoder-Based Feature Reduction For Improving Iot Intrusion Detection, Tahseen A. Wotaifi

Journal of Intelligent Informatics, Networking, and Cybersecurity

The rapid growth of Internet of Things (IoT) environments has brought forth a wealth of security challenges in detecting network intrusions in diverse and resource-restricted systems. Privacy, scalability, and single point of failure issues plague traditional centralized intrusion detection solutions. To address these challenges, the study proposes a secure and adaptive intrusion detection model using Federated Learning (FL) and Blockchain, augmented with autoencoder-based feature reduction. The ToN-IoT dataset is pre-processed, and then an unsupervised autoencoder is used to build informative low-dimensional feature representations. The processed data is deployed to various clients to mimic a real federated situation. Every client will …

A Dual- Task Hierarchical Graph Attention Network For Protein-Protein Interaction Sites Prediction, Oras A. Hussein, Eman S. Al-Shamery

Journal of Intelligent Informatics, Networking, and Cybersecurity

In computational structural biology, it is still very hard to accurately find protein-protein interaction (PPI) sites and estimate how strong the interaction would be. In this research, we provide an innovative two-stage deep learning framework that combines residue-level graph representation learning with protein-level regression to achieve a thorough modeling of protein interactions. Protein structures first encoded as residue graphs, with nodes that stand for amino acids and edges that show how close they are to each other in space. To find binding residues, a deep residual Graph Attention Network v2 (GATv2) uses multi-head attention, residual connections, and Jumping Knowledge aggregation …

A Professional Development Course On Data-Driven Dynamical Systems At A Primarily Undergraduate Institution - Part B: Professional Development Framework And Institutional Implementation, Alessandro M. Selvitella, Jeffrey R. Anderson

CODEE Journal

This paper presents the professional-development and institutional-implementation component of a three-paper program on introducing data-driven dynamical systems into undergraduate ordinary differential equations instruction at a primarily undergraduate institution. The companion paper \cite{SelvitellaAnderson2026} develops the mathematical and computational content, including regression, regularization, Dynamic Mode Decomposition, Sparse Identification of Nonlinear Dynamics, and a Van der Pol oscillator activity. The present paper asks a complementary implementation question: what departmental structures, graduate teaching assistant roles, professional-development activities, and course-support pathways are needed for such materials to become teachable within local undergraduate settings?

We describe a three-phase professional-development model for graduate teaching assistants in the …

Cultural Traits May Replace Human Mobility Data In Forecasting Covid-19 Mortality: A Deep Learning Approach, Saif Abbas, Tamer Oraby, Michael G. Tyshenko, Samit Bhattacharyya

School of Mathematical & Statistical Sciences Faculty Publications

The COVID-19 pandemic highlighted the need for accurate epidemic forecasting to support public health decision-making. Most existing approaches depend heavily on human mobility data, while largely neglecting population behavior shaped by socio-cultural norms. In this study, we analyze daily COVID-19 mortality and Google mobility data from 72 countries during the first 130 d of the pandemic, a period characterized by high uncertainty and behavioral heterogeneity. In particular, we examine whether Hofstede’s country-level cultural dimensions can serve as latent behavioral forecasters of mortality in lieu of dynamic mobility indicators. Using 100 d for training and 30 d for forecasting, we employ …

Global Performance Of Remote Sensing-Based And Reanalysis-Driven Models To Estimate Open Water Evaporation, Júlia Brusso Rossi, Ayan Santos Fleischmann, Leonardo Laipelt, Bruno Comini De Andrade, Joshua B. Fisher, Justin L. Huntington, Christopher Pearson, R. Iestyn Woolway, Roseilson Vale, Júlio Tota, Gabriel B. Senay, Huilin Gao, Anderson Ruhoff

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Evaporation plays an essential role in the water cycle, influencing local and regional climates while directly impacting water availability in lakes. However, directly measuring evaporation over water bodies remains challenging due to the high costs of installing and maintaining the required in situ instrumentation. Although several remote sensing algorithms have been providing evaporation estimates, the lack of a global validation hinders our understanding of their relative uncertainties and performances across different regions. Here, we analyze the performance of a suite of models that leverage satellite data and meteorological reanalysis to estimate evaporation over lakes worldwide. We compare 3 remote sensing‐based …

The Climasentar Dataset For Evaluating Cross-Domain Transferability Of Large Language Models In Climate Sentiment Analysis, Sanaa Kaddoura, Mariam Alzaabi, Reem Nassar

All Works

Arabic research on climate sentiment analysis remains limited due to linguistic diversity, limited resources, and the scarcity of annotated datasets. Existing approaches primarily rely on questionnaires or general-purpose sentiment analysis models, which often fail to capture domain-specific sentiment expressions. To address this gap, this paper introduces ClimaSentAR , the first large-scale Arabic climate-focused sentiment dataset comprising 23,957 samples from the X platform. Native Arabic speakers annotate the dataset with a moderate inter-annotator agreement of 0.45. It contains 5510 positive, 8140 negative, and 10,307 neutral instances. To validate the importance and robustness of ClimaSentAR and address the gap in Arabic climate …

Global Time-Resolved Measurements Of Inlet/Isolator Unstart Induced By Mass Injection, Andrew N. Bustard, Benjamin L. Bemis, Aaron Marques, Matthew J. Zahr, Thomas J. Juliano

Publications

The inner surface pressure of an axisymmetric inlet/isolator model was measured using anodized-aluminum pressure-sensitive paint (PSP) viewing through cast acrylic. Temperaturesensitive paint was utilized to correct for the PSP’s temperature sensitivity. The model was tested under Mach 5.7 flow at 𝑹𝒆 = 7.1 ×106 /m under conventional noise conditions. Transverse jet injection with jet-to-inlet mass-flow ratios up to 0.8 was used to induce unstart in the inlet/isolator. Background-oriented schlieren visualization of the inlet shocks was collected simultaneously with the PSP to determine when the inlet unstarted. Computational fluid dynamics results were used to determine off-wall flow structures and quantify approach …