bluuebunny/crossref_metadata_2025_split huggingface dataset:
Lamb Wave-Based Inspection of Solar Cell Arrays
Authors: Green Mattie , Alsaffar Fadhel , Mal Ajit , Schaal Christoph 
Published: January 2025

Abstract
Solar arrays provide electricity to spacecraft by converting energy from the sun. Generally, solar arrays are made by adhering multiple solar cells to a substrate, usually with silicone based adhesives. They may be prone to disbond failures at the cell interface due to mismatch of the coefficients of thermal expansion. Manufacturing errors like voids in the adhesive layer can also occur. If disbonds are not detected and repaired, the electrical interconnects can fail due to cyclic thermal loads in space. This is significant because the failure of even one interconnect can cause power loss to a number of cells. This paper aims to evaluate the feasibility and sensitivity of inspecting bonded joints in solar arrays in space. One potential nondestructive evaluation technique relies on Lamb waves. These waves have been used for disbond detection in layered media. In this work, this methodology is extended to detecting disbonds between layers of different materials and sizes as in the case of a solar cell bonded to a larger substrate. Transient structural finite element analyses are conducted using Abaqus. For simplicity, a 2D representation is modeled of an isolated silicon solar cell bonded to a larger polymer substrate panel. Disbonds of varying size and location are studied and compared to a pristine case with no disbond between the cell and substrate. Several damage indices are defined and evaluated for effectiveness in indicating specific defect characteristics. Using these damage indices, almost all of the tested disbond cases are shown to be fully characterizable according to size and location, including disbonds as small as 1 mm. The results of this study could be applicable beyond the scope of this work to any layered medium with materials of highly dissimilar stiffness.
Development and Modeling of a Structural Health Monitoring Payload for Low Earth Orbit Experiment
Authors: Ellis Gage , Fawcett William , Garcia Chrstopher , Tapia Dylan , Zagrai Andrei 
Published: January 2025

Abstract
This contribution discusses aspects of mechanical design, fabrication, and modeling of a payload that supports Structural Health Monitoring (SHM) experiments aboard the International Space Station (ISS). As the space industry becomes more commercialized, the need for safe and long-lasting space assets has increased exponentially. Implementation of SHM to space structures has considerable potential to improve safety of operation, and controllability of spacecraft. In order to better understand the effects of the space environment on space structures, the New Mexico Institute of Mining and Technology (NMT) is sending a payload to the ISS to collect data representing the effects of the space environment on SHM methodology and hardware. This is an active payload designed to house several SHM experiments. SHM experiments include guided wave propagation in a metallic structure, monitoring of an imitated crack, assessment of a bolted joint, investigation of structural vibration via electromechanical impedance method, and acoustic emission monitoring. In addition, piezoelectric sensor self-assessment is realized using the impedance diagnostics.
The payload fits the Materials International Space Station Experiment (MISSE) module specifications and is designed to operate in LEO under vacuum, volatile orbital thermal cycles, and background radiation. In order to simulate the effects of the environment on the payload, two finite element models are performed for thermal analysis: an orbital heating model, and a quarter cycle heat distribution model. The orbital heating model predicts the external thermal loads on the payload at any point in an orbit, including solar radiation, albedo, radiation from the earth, and radiation to deep space. The quarter cycle model predicts the internal thermal loads as the payload travels from shade to sun and predicts the temperature at critical locations including computer location. The payload experimental data will serve as a baseline for environmental conditions and will aid design and modeling of future SHM systems. Measures to protect SHM systems are discussed. Predictive models and calculations of payload thermal performance obtained in laboratory tests are presented and discussed considering expected variations due to the LEO environment.
Semi-Customized Orthoses Designed With Adjustable Features to Facilitate Mass Production With Enhanced Fitting Performance
Authors: Mo Yaru , Johnson Shane 
Published: January 2025

Abstract
Orthoses are essential medical devices used in rehabilitation. A high degree of orthotic customization enhances the fitting performance. However, it generally necessitates higher cost and longer time for fabrication. This study proposes a semi-customized approach for orthotic design, aiming at reducing the time and cost related to the orthotic manufacturing while maintaining the fitting quality. Twelve semi-customized modular arm braces integrated with adjustable connectors were developed, and their adjustability and fitting performance were evaluated computationally and experimentally. It was shown that the connectors designed with special features can provide the required deformation range within [−9.2, +10.5] mm to accommodate intra-cluster variations. Computational analysis demonstrated the necessity of incorporating adjustable features in providing customized fitting. Additionally, the designed semi-customized modular braces exhibited the ability to conform to target surfaces, with 75% of regions showing a normal distance &lt; 1.5 mm post-adjustment. As for the experiment, the participant provided positive feedback on fitting, further demonstrating the satisfactory performance of adjustable semi-customized designs. This proposed semi-customized methodology offers cost-effective and time-saving solutions for orthotic manufacturing without compromising fitting quality, which enables mass production of orthoses with enhanced comfort and advances the orthotic technology.
A Two-Level Optimization Approach for the Synthesis, Design and Operation of Multi-Energy Systems Integrated With Energy Networks
Authors: Dal Cin Enrico , Carraro Gianluca , Tsatsaronis George 
Published: January 2025

Abstract
Achieving decarbonization targets requires optimizing the synthesis, design, and operation of multi-energy systems that meet end-user demand for different forms of energy, with the goal of minimizing costs. This means contextually finding the number, type, location, size and operation conditions of the conversion and storage units that supply the required energy, as well as the topology and capacity of the networks that deliver it to the end users. However, this inherently integrated problem includes several nonlinearities and an extremely large number of continuous and binary decision variables, making it impractical to solve. Linearization allows the computational complexity to be drastically reduced. Nevertheless, the combinatorial nature of binary variables exponentially increases computational time. To simplify the problem while ensuring good accuracy of the results, this study presents an evolutionary algorithm that decomposes the overall problem into two levels: i) selection and placement of components to be included in the system (synthesis) and ii) sizing and scheduling of the included components (design and operation). This allows for a drastic decrease in combinatorial complexity and, in turn, in computational time. The proposed two-level algorithm is validated here against the traditional mixed integer linear programming (MILP) approach for solving the complete, non-decomposed problem. Finally, application examples considering electrical and heating networks coupled with both renewable and conventional energy conversion and storage systems show that decomposition reduces computational time by up to 70% and provides solutions to problems that otherwise cannot be solved in an acceptable time.
Closed Loop Vision Guided Control of Flyer Position for High-Throughput Laser Shock Experiments
Authors: Wang Heyun , Diamond Jacob M. , Bhattacharjee Anuruddha , Wanchoo Piyush , Mirzaei Ahmad , Li Liuchi , Nkansah-Mahaney T. Joseph , Ramesh Kaliat , Krieger Axel 
Published: January 2025

Abstract
In materials science, high-throughput material processing and testing are crucial for rapid materials design and discovery, but manual operations often create bottlenecks in terms of speed and accuracy. Automating the repetitive and labor-intensive aspects of material testing significantly increases throughput and consistency, facilitating a more efficient pathway to material innovation. This study demonstrates automated process control by integrating robotic automation in a high-throughput laser shock system using closed-loop “see-move-shoot” experiments. The system employs two automated linear stages to sequentially manipulate material specimens (flyers) under a laser for impact testing. Each experiment includes automatic target detection, sample centering, laser activation, impact verification, and progression to the next sample. For flyer detection, we developed a computer vision algorithm using a convolutional neural network (CNN) model based on EfficientNetB0. Trained on 16,000 labeled images under various lighting conditions, the model achieved a root mean square error (RMSE) of 0.038 mm in extreme testing conditions (i.e., under high exposure, low light, or blurry images) ensuring reliable and efficient real-time processing. In our “see-move-shoot” comparison study, manual operation took 30.6 seconds for a novice user and 19.2 seconds for an expert user per shot, while the CNN model required only 7.46 seconds. Consequently, the CNN model conducts experiments 4 times faster than the novice user and 2.5 times faster than the expert user.
Empowering Future Engineers: Integrating Scientific Literacy and Critical Analysis in the Study of Waste Treatment and Gaseous Effluents
Authors: Carvalho Violeta , Teixeira Senhorinha , Teixeira José C. 
Published: January 2025

Abstract
This study introduces a teamwork approach implemented in the “Treatment of waste and gaseous effluents” curricular unit (CU) within the Mechanical Engineering Master program at the University of Minho. Recognizing the importance of fostering critical thinking and scientific literacy skills, particularly for master dissertation development, this CU included teamwork where students had to prepare a short critical literature review about a separator technology selected by them using some scientific papers. Furthermore, a field visit to a company was organized and a seminar seeking to promote active learning strategies.
To equip students for teamwork, lessons covered effective scientific literature searching, reference management software utilization, and the critical review writing process. Initial feedback from students was obtained through the application of a short questionnaire and the results indicated a positive response to the teamwork activity, with reported improvements in literature search proficiency and critical analysis skills. The collaborative learning environment was appreciated, and students expressed enhanced confidence in evaluating research methodology and forming informed opinions.
Dynamic Fault Tree Games and Reinforcement Learning for System Reliability
Authors: Jha Mayank , Chulliyat Jose Amal , Grimstad Joachim , Morozov Andrey 
Published: January 2025

Abstract
This paper introduces a novel approach to analyzing the reliability of complex systems using model-based system engineering and adversarial multi-agent reinforcement learning. The merger of these approaches aims to identify the critical paths in a dynamic fault tree that may lead to system failure. Further, this study also explores the feasibility of leveraging transfer learning to train neural networks representing adversarial agents within a simulated gaming environment and craft fault-tolerant systems capable of adaptations in dynamic settings. The proposed methodology involves adversarial multi-agent reinforcement learning, where adversarial agents, labeled “red agent” and “blue agent,” compete in a zero-sum game environment to induce or avert system failure, respectively. Multiple games are played on different environment versions, reflecting changes introduced by dynamic fault tree adjustments. However, the extensive interactions between the agents and the environment pose challenges for complex, large-scale systems because of the many interactions involved. These interaction results must be stored for optimizing the policy later on, thus increasing the space and time complexities. To mitigate this challenge, transfer learning is introduced to enhance agent learning performance by transferring knowledge acquired from previous game environment versions instead of training them from scratch each time.
Comparison of Electrode Configuration for (0,2) Piezoelectric Micromachined Ultrasound Transducer
Authors: Popal Abdul Q. , Janardhana Ranjith D. , Akram Fazli , Jackson Nathan 
Published: January 2025

Abstract
Piezoelectric micromachined ultrasound transducers (PMUT) have been extensively used in numerous applications. Most PMUT applications operate in the first mode (0,1), and extensive investigation into the effects of the electrode design on performance have been previously investigated. However, specific applications such as atomizers or biosensors can operate in higher modes such as (0,2) and (0,3), but the effects of electrode configuration on these modes are limited. This study focuses on optimizing the electrode configuration of higher-order PMUT devices. The (0,2) and (0,3) modes are essential for vibrating mesh atomizers (VMA) as it has a high central force that allows liquid to be squeezed through the nozzles. The PMUT devices comprise two thin Pt electrodes, a lead zirconate titanate (PZT) piezoelectric layer sandwiched between the electrodes and a Si membrane. The Finite element modeling (FEM) study aims to determine an optimal electrode configuration to enhance displacement and velocity of the membrane. A 2D FEM was used to simulate the devices, and multiple electrode designs were compared in terms of membrane amplitude and velocity. The devices were operated at resonant frequency, with a constant AC voltage of 100 Vpp. The results showed that the electrode design significantly affects both displacement and velocity, and the optimal electrode configuration is based is based on nodal circles which is different from (0,1) mode. A single-layer circular electrode covering the entire membrane had the lowest displacement. In contrast, a multiple-ring configuration with the electrode rings located at a gap from the nodal circle locations gave the highest displacement and velocity.
Experimental Investigation on the Annular Drilling of Acute Angle Micro-Holes in Nickel Based Superalloy With Femtosecond Laser
Authors: Gonumakulapalle Lodi Samuel , Kumar Sunil 
Published: January 2025

Abstract
Micro holes play a pivotal role in enhancing the efficiency of aero engines. These micro holes necessitate precise drilling at acute angles with respect to plate surface to optimize cooling performance and enhance film cooling effectiveness. Inclined holes offer an advantage over those perpendicular to the surface by promoting more uniform airflow, thereby facilitating better dispersion of coolant. This study introduces femtosecond laser annular drilling with different scanning routes as a novel method for fabricating high quality acute-angle micro holes. Cylindrical micro holes with a diameter of 400 μm are drilled at angle of 30° from the surface of 0.68 mm thick IN718 plate. The influence of different processing parameters like laser fluence, laser spot overlap ratio and scanning speed on surface roughness, taper angle, and aperture circularity is thoroughly evaluated and discussed. The cross-section morphology analysis is conducted using scanning electron microscope (SEM) integrated with energy-dispersive spectroscope (EDS). Experiments have done using proposed drilling method with femtosecond laser. The diameters of entry and exit holes were assessed using a 3D microscope from Olympus, while the surface roughness of the sidewalls, characterized by Ra and Rq are 907.79 nm and 1.20 μm respectively. Experiments will aim to generate acute angle holes of superior quality, with the findings of this study opening up latest avenues for refining the femtosecond laser (fs) drilling method.
Reinforcement Learning-Based Identification of Failure Scenarios for Dynamic Risk Assessment of AI-Controlled Robotic Systems
Authors: Grimmeisen Philipp , Sautter Friedrich , Morozov Andrey 
Published: January 2025

Abstract
AI-controlled robotic systems can pose significant risks to both human workers and the environment due to their complex, autonomous operations. Traditional risk assessment methods fall short in adequately describe sophisticated failure scenarios of systems controlled by black-box policies. These traditional methods are applied manually and do not considering frequent software updates. Therefore, novel methods that enable a dynamic risk assessment for AI-controlled robotic systems are required.
In this paper, we present the concept of a new approach that enables the dynamic risk assessment of unknown or dynamically changing control policies. This includes AI-controlled robotic systems, especially those utilizing reinforcement learning. The new approach combines two key methods: (i) automated identification of failure modes and (ii) a reinforcement learning-based search for critical failure scenarios. Additionally, it incorporates an evaluation method that analyzes the detected sets of critical scenarios or events. This evaluation method creates dynamic high-level risk models and identifies vulnerabilities to specific failures.
Dynamic Analysis of Main Coolant Pump Based on Precise Integration Method
Authors: Zhu Bao , Feng Yang , Lei Ming-kai 
Published: January 2025

Abstract
The rotor-bearing system is an important part and core component of the main coolant pump. In this paper, the finite element modeling method of Timoshenko beam is used to carry out dynamic modeling of the rotor-bearing system of the main coolant pump. The stator and rotor in this model are constrained by the thrust bearing and the guide bearing in axial and radial directions. The difference between the radial and axial natural frequencies of the main coolant pump will cause the stiffness problem in numerical calculation. The precise integration method is used to calculate dynamic response of the rotor bearing system by overcoming the stiff problem. Our results show that, a very high-precision solution could be achieved in large time step by using the precise integration method. Based on the proposed model, the influence of operating condition parameters on dynamic response of the rotor-bearing system is investigated and discussed in details.
Effect of Surfactants on the Acoustic Patterning of Organic and Inorganic Microparticles in a Polymer Matrix
Authors: Shovon S. M. Abu Naser , Subedi Saroj , Ware Henry Oliver Tenadooah 
Published: January 2025

Abstract
Polymer matrix composites with acoustic-based filler orientations have multifunctional engineering applications, including sensors, flexible electronics, and embedded electrical wiring. In this work, we presented the effect of surfactants on controlling the patterning behavior of organic and inorganic microparticles in a liquid pre-polymer matrix using acoustic radiation forces created from Bulk Acoustic Waves (BAWs). A customized (30 × 22 mm2) chamber was utilized in this study. This chamber incorporated two piezoelectric transducers placed in a parallel orientation to efficiently align the embedded microparticles along the nodes of the acoustic pressure wave. In suspensions, Microparticles tend to have unwanted agglomeration when the suspension is at rest, and surfactants help to stabilize particle dispersion within the suspension. The effect of surfactants on the alignment of organic and inorganic microparticles has been analyzed at varying concentrations of particles (0.5 %, 2.5 %, 5 % w/w) in a low-viscosity liquid pre-polymer (PEGDA). Two different surfactants were studied to identify their compatibility on the suspension of particles in a ratio ranging from 1:0 to 1:1 (particle to surfactant ratio). In a 5 wt.% of organic particle concentration, the nodal distance of patterned particles was 670 μm with no surfactants (1:0), which was reduced to 470 μm when surfactants were used in a 1:1 ratio. Similarly, in 5 wt.% inorganic particles, the nodal distance was reduced from 715 μm (1:0) to 450 μm (1:1) utilizing the surfactants. Additionally, surfactants reduced the alignment time of organic and inorganic particles from 20 seconds (1:0) to 10 seconds (1:1) in 5 wt.% particle concentration. The proposed acoustic patterning method utilizing surfactants provides efficient patterning of microparticles to create high-performance polymer-polymer and polymer-metal composites towards multifunctional applications.
A Finite Element Framework for Studying Mechanical Aspects of Blast Load Induced Traumatic Brain Injury in Humans
Authors: Peterson Luke , Murphy Michael , Lee Nayeon , Sharma Gehendra , Johnson Daniel , Bakhtiarydavijani Amirhamed , Miralami Raheleh , Hammi Youssef 
Published: January 2025

Abstract
This work presents the generation and validation of a Finite Element (FE) simulation framework to study Traumatic Brain Injury (TBI) resulting from blast loading of the human head. The framework involves a multi-step modeling approach: first, reflected pressures are collected from discrete regions around a rigid head geometry (within a gaseous medium) in coupled Eulerian-Lagrangian blast simulations. Second, the obtained pressures are applied as region-specific discrete surface loads to the surface of a deformable FE human head model in separate Lagrangian simulations, allowing the blast effects to deform the brain geometry. This multi-step approach is used to generate shock tube loading simulations of two FE head and brain geometries featuring two classes of brain constitutive models (hyperelastic-viscoplastic Internal State Variable (ISV) model and Prony series viscoelastic model). Simulation results for coup and contrecoup brain pressures generally agree with documented intracranial pressure measurements from shock tube testing of human cadaver heads for model framework validation. Methods for obtaining and comparing brain mechanical state variable evolution to literature, documented material state metrics for TBI, and the implications and challenges for predicting blast induced TBI are discussed.