bluuebunny/crossref_metadata_2025 huggingface dataset:
A New Methodology for Techno-Economic Comparison of Waste Heat Recovery Options in Industry
Authors: Giordano Lorena , Benedetti Miriam
Published: January 2025

The climate emergency requires a radical transformation of the energy system. Promoting waste heat recovery in industry is crucial to decarbonising its heat consumption, which accounts for more than 50% of the sector’s final energy use. Current literature evaluates waste heat recovery (WHR) projects primarily from an economic perspective, using metrics such as the payback time and the net present value. However, these metrics have inherent limitations, particularly for technologies with high initial costs. There is therefore a need for a more comprehensive assessment that considers their energy, economic and environmental impacts. This study proposes a new methodology to compare industrial WHR options, which provides for the evaluation of a set of energy, economic and environmental performance indices. Notably, this methodology introduces a new index, the Energy Recovery Cost (ERC), which relates benefits such as energy savings and CO2 emissions avoided to the costs incurred over the lifetime of the WHR system. The methodology was applied to six WHR projects identified through the analysis of mandatory energy audits carried out by Italian industrial companies. Firstly, the methodology is validated by comparing the calculated financial indices with the corresponding values from the energy audit reports. Then, the viability of WHR projects is evaluated by comparing the ERCs of WHR projects with the unit cost incurred by the companies to buy or produce the same amount of energy without reusing the waste heat sources. Overall, the ERC provides a new perspective on the evaluation of WHR projects, which can help stakeholders make informed decisions, especially when considering technologies with relatively high initial capital costs.
Computational Fluid Dynamics Analysis of Solar Air Heater Efficiency With Corrugated Absorber Plates in Alkharj, Saudi Arabia
Authors: Alqsair Umar F.
Published: January 2025

In this article, we investigated the performance of a solar air heater. Solar air heaters use solar energy to heat the air in various heating systems. Our study is on August 15 in Al Kharj, Saudi Arabia. For analyzing the performance of the solar air heater, we examined different hours during one day. So, we select different hours from 8 am to 4 pm. The proposed solar heater consists of an absorber plate and a glass cover. The absorber, the most important component in the heating system, has a Corrugated construction with a Chevron design. At different hours, we compare the thermal performance by two different configurations. Once, we considered a flat solar heater, and the other, an inclined solar heater with an angle of 30 degrees. In this study, we performed the numerical simulation using computational fluid dynamics (CFD) via Ansys Fluent software. Therefore, we used the Discrete Ordinates (DO) radiation model to consider radiative heat transfer and the Solar Ray Tracing model to apply solar irradiation. The results confirmed that both in the flat and the inclined absorber cases, the incident radiation has the greatest effect on the thermal performance of the solar air heater.
Topology Optimization of a Landing Gear Part Considering Fatigue Constraint for Additive Manufacturing
Authors: Kim Tae-Uk
Published: January 2025

The combination of topology optimization (TO) and additive manufacturing (AM) is bringing lots of benefits into design and production of aircraft parts. Realizing the complex geometry as near net shape and part simplification by removing fasteners are examples of such advantages, and the related research efforts have been consistently increasing. In this paper, a landing gear torque link is optimized for weight reduction with static and fatigue constraints and fabricated by AM to investigate the possibility of practical use. Many structural designs using TO have considered compliance minimization with constraints such as static strength and volume fraction. But, most aircraft components undergo repeated loadings and it becomes important to consider fatigue life when designing the parts. A landing gear is generally a safe-life structure which does not allow any crack initiation during entire service life, it is essential to identify the damage resulting from fatigue spectrum at the design optimization. The final prototyping results show the possibility of practical usage and applicability to other aircraft parts.
A Two-Step Selective Microscopic Surface Modification Technique: Combining Electrodischarge and Electrochemical Post-Processing
Authors: Ramver Ramver , Tiwari Tanmay , Sekhar Rakurty Chandra
Published: January 2025

This paper introduces an in-situ two-stage surface modification method for micro-sized titanium components, particularly crucial in high-value manufacturing engineering sectors like biomedicine, aerospace, and automotive. The method combines Dry Electric Discharge Surface Modification (Dry-EDSM) for selective nitriding and Electrochemical Polishing (ECPP) to refine surface quality. Detailed characterization including X-ray diffraction, X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), white light interferometry (WLI), and micro-hardness, confirms the effectiveness of the combined approach in achieving desired modifications while also highlighting the impact of process parameters on surface properties. Surface characterization following Dry-EDSM revealed a titanium nitride layer, hard but initially rough. Post-processing notably increased micro-hardness by 35% (from 300 HV to 405 HV) and reduced surface roughness by 84% (from 4.5 μm to 0.72 μm). The average surface modification layer thickness decreased from 33 μm pre-ECPP to approximately 21.3 μm post-ECPP. XRD analysis confirmed titanium nitride presence post-ECPP. ECPP eliminated rough ridges and valley-like features, rendering the surface smoother and crack-free, affirming the combined approach’s efficacy in achieving desired modifications while preserving micro-sized component integrity. The findings of this study significantly advance surface modification techniques by developing a cost-effective in-situ machining and post-processing approach for micro-components, offering valuable insights for industries reliant on precise surface characteristics.
Simulation Based Analysis and Design of Passive Back Exoskeleton for Squat Lifting
Authors: Sahu Neha , Gupta Abhishek
Published: January 2025

Back pain is the most common musculoskeletal disorder that manual material handling laborers face as they lift heavy objects. To overcome the back pain problem, it is advised to wear assistance (Exoskeleton) during lifting. Through musculoskeletal simulation, this work investigates how the passive back exoskeleton affects the spinal muscle forces and spinal joint reaction loads. Such simulation findings can provide insights to improve the back exoskeleton design further. For this purpose, the passive exoskeleton is modeled as a set of elastic elements (springs), and dynamic analysis for a lifting cycle is done during a squat lifting task. Musculoskeletal simulations were carried out in OpenSim software utilizing the open-source OpenSim lifting full body (LFB) model. The LFB model is modified by adding an external spring that provides assistive forces like a passive exoskeleton. During the whole lifting cycle, the erector spine muscle is strained, so unloading the erector spinea muscle is the primary goal of most back support exoskeletons. This work aims to identify optimal spring configurations for the design of a passive back exoskeleton to aid in squat lifting. Corresponding spring stiffnesses will also be determined. The optimized back exoskeleton is expected to reduce compressive and shear forces on the L5S1 joint during lifting.
Use of Game Theory for Strategic Scheduling of Different Types of Chillers
Authors: Allen-Magande Hugh , Khazaii Javad , Esmaeili Amin , Khazaei Ali
Published: January 2025

Abstracts Game theory is a decision-making tool that focuses on the strategic planning for cooperative or non-cooperative (conflicting) problems by two or more agents. All agents’ decisions directly affect the outcomes (pay-offs) received by each of them. Strategic operation of the equipment in the mechanical room of any commercial building can have a significant energy-saving impact. Chillers and boilers are the two primary energy-consuming equipment in cooling and heating systems. Regular centrifugal chillers consume energy when electricity is used to run the refrigeration cycle inside the chiller (mainly consumed to operate compressors). At the same time, hot water boilers consume natural gas to heat the building’s air conditioning and water. It is important to remind here that in large commercial buildings, throughout the year, both chillers and boilers are required to operate at the same time — for the building cooling, heating, reheating, and water heating needs — and not just chillers for hot seasons and heating for cold seasons. Absorption chillers are a different type of chiller that, instead of consuming electricity at compressors, uses heat for the compression process of the cooling generation cycle. A pump in this system consumes a much lower quantity of electricity relative to the compressor in vapor-compression cycles. The aforementioned will result in a considerably larger consumption of natural gas and a significantly lower consumption of electricity instead. It is also customary for designers to have at least two chillers (each at capacity higher than 50% capacity of the whole system) for each building to keep at least a level of backup capacity when one of the chillers is out of commission due to required service or due to unexpected system failure.

In the current paper, the authors will use the rules of game theory to make the most energy-efficient scheduling decisions for energy saving in a typical air conditioning system when utilizing two different types of chillers in one building. The authors will compare the overall energy consumption of a typical system using two centrifugal chillers, two absorption chillers, or one of each, and recommend the most efficient strategy for the building.
High Strain Rate Fracture of Shear Wrinkled Graphene
Authors: Avasarala Nandana , Kim Leo , Dorsey Fahim , Park Jungkyu
Published: January 2025

This study explores the mechanical responses of shear-wrinkled graphene to high strain rate impacts, employing molecular dynamics simulations to model the high-speed fracturing of this material. Initially, we induce shear in a graphene layer to naturally create wrinkles, following which a silver particle is propelled at the wrinkled graphene at predetermined velocities. The interaction between silver and carbon atoms is modeled using the Lennard-Jones potential, while silver atoms themselves are simulated via the embedded atom method (EAM) potential, with the second-generation REBO potential governing the carbon atoms with a cutoff distance of 2.0 Ångström. Our results reveal that shear-wrinkled graphene demonstrates greater stiffness compared to its unwrinkled counterpart, absorbing less impact energy. Notably, all graphene layers, regardless of wrinkling or shear deformation, fracture upon impact at velocities of 5 km/s, suggesting that fracture is primarily influenced by C-C bond breakage rather than pre-existing deformations. This investigation marks a significant step towards the development of robust, lightweight materials designed for military applications, significantly enriching the defense technology sector.
Identification and Localization of Areas of Damage in Composite Materials Using Infrared Thermography and Artificial Intelligence
Authors: Barua Aditi , Dabetwar Shweta
Published: January 2025

This study investigates the integration of Mask RCNN with Infrared (IR) thermography for non-destructive testing to detect defects in composite materials. Due to their high strength-to-weight ratio and customizable properties, composite materials are widely used in various engineering applications. However, these materials are prone to subsurface defects such as delamination, cracks, and voids which cannot be detected by visual inspection. Traditional defect detection methods are limited, emphasizing the need for advanced techniques like IR thermography, which detects surface heat variances indicative of underlying defects. The research introduces a high-fidelity instance segmentation model, namely, Mask RCNN that is capable of identifying the defects in thermal images. The model is analyzed for sensitivity with respect to the number of epochs. The results showed accurate identification and localization of multiple types of subsurface defects. Sensitivity analysis showed that the accuracy improved from about 77% at epoch 30 to 97% at epoch 120, while the training loss decreased from 0.13 to 0.07. These results highlight the model’s learning efficiency and potential for real-time monitoring of structural integrity. This approach not only advances non-destructive testing technologies but also provides a scalable option for ongoing structural health monitoring of composite materials, ensuring their safety and functionality in engineering applications.
Measurement of Chaotic Complexity in a Planar Mechanism Due to the Motion of the Follower With Clearance Using Lyapunov Exponent, Phase Plane Diagram, Poincaré Map, and Spectral Entropy Representations
Authors: Yousuf Louay S.
Published: January 2025

This paper considers the planar mechanism with rotating cam, flat faced follower, two guides with clearance, crank arm and connecting rod. There is clearance between the follower stem and guide by taking into consideration the effect of impact and friction. The aim of this paper is to describe the complex dynamic motion of the mentioned planar mechanism using different chaotic methods at different cam speeds and different follower guide’s clearance under normal impact and impact with coefficient of restitution. Time delay and global embedding dimension are used using the algorithm of mutual average information and false nearest neighbors algorithms. Lyapunov exponent is extracted at different cam speeds and different follower guide’s clearance. Spectral entropy is used to detect the chaos due to the white noise at different contact levels and high speeds of the cam. SolidWorks program is used to calculate the point linear displacement at the contact point between the cam and the follower. The dynamic tool package algorithm has been written using Matlab software to describe the chaotic motion. Moreover, phase plane diagram, and Poincaré map are added to the detection of the dynamic chaotic motion. The normal impact and impact with coefficient of restitution have been taken into account in this paper. Time delay and global embedding dimensions are contributed in the calculation of Lyapunov exponent. Regarding largest Lyapunov exponent, the system with follower guide 17 mm and 19 mm at cam speeds 2000 rpm and 1200 rpm have a chaotic motion since the numeric values of Lyapunov exponent is positive. Regarding the Poincaré diagram, the system with the cam speed 100 rpm and coefficient of restitution 0.2 has a quasi-periodic motion while the other systems have chaotic motion. Regarding the phase diagram, the cross linking of point linear displacement is increased with the increment of cam speeds, coefficient of restitution, and follower guide clearance.
Failure Analysis for Lock Sensing Limit Switch on EMU Door System
Authors: Wu Lvxian , Hong Haifeng , Zhang Xiaoming , Zhang Long , Lu Hang , Li Dong , Yin Yanbo , Tang Yuxuan , Huang Wei , Chen Qiubo
Published: January 2025

The EMU plug sliding door system’s security loop relies on two crucial components: the lock limit switch and the lock sensing limit switch, wired in series. Any malfunction in either switch during operation can disrupt the train’s ability to initiate traction during berthing or induce emergency brake during revenue service, leading to operational issues, and impacting the service schedule and service life of the vehicle. Thus, ensuring the high-quality manufacture and precise installation of these limit switches is paramount. This paper focuses on the analysis of serval fault reports of the security loop. Upon inspection of current units, sporadic lock sensing limit switch malfunctions emerge as the primary cause of safety loop failures. Consequently, this paper aims to conduct an in-depth analysis of lock sensing limit switch failures on different train series, focusing on identifying the underlying issues and proposing practical solutions. Investigations and testing were conducted on actuation force, fitness of the components, and electrochemical oxidation to identify the root cause of the safety loop’s failure. A manufacturing defect was located and corrected significantly reducing the failure rate. Further correction, experience, and suggestions are provided for manufacturers and car builders.
Sensor Optimization for Damage Detection Within a Digital Twin Framework
Authors: He Junyan , Aguilar Enixe , Eger Markus , Sotoudeh Zahra , Zhuang Linqi
Published: January 2025

A random forest model is trained on dataset generated by finite element (FE) simulation to predict the damage location on a metallic plate. An optimization framework is integrated to identify minimal number of sensors required and optimal sensor placements. The accuracy of the FE model was validated against analytical solutions and experimental measurements, where satisfactory agreement was found with analytical solutions. The out-of-plane displacement and the normal strain at the bottom of the plate surface were extracted from the simulation at different virtual sensor locations to serve as inputs to the random forest model. It was found that satisfactory prediction accuracy can be achieved with just two sensors for this specific problem. Using a response surface optimization method, the optimal sensor locations that minimizes prediction error are identified, and achieved higher accuracy than the baseline case with equidistant sensor placement. This study lays a strong foundation for developing a machine-learning-based structural health monitoring model within a digital twin framework.
A Non-Destructive Testing Method for Rolling Bearing Internal Temperature Based on Ultrasonic Signals
Authors: Zhang Rongfeng , Chen Li , Zhou Rui , Liu Heng , Qi Shemiao , Liu Yi , Li Yuan
Published: January 2025

Obtaining the internal temperature of rolling element bearings during the operation plays a vital role in the dynamic analysis of the bearings. A non-destructive testing method of the internal temperature of the outer race based on the ultrasonic signals is proposed in this paper. The study initially measured the speed of sound at various temperatures using the same bearing steel as the tested bearing outer race. The measurement results revealed a significant linear correlation between the speed of sound and material temperature, which also provided the reliability of the proposed method. The operating temperature of the outer race of an N306 cylindrical roller bearing was tested in this paper. In addition to measuring the internal temperature, a temperature sensor was used to obtain the surface temperature. When properly lubricated, the lubricant removes most of the heat inside the bearing. This results in the surface temperature being slightly lower than the tested internal temperature. As the bearing is inadequately lubricated, more heat is transferred to the outer race surface, leading to a larger temperature difference. The test results indicate that monitoring the internal and surface temperature of the outer race can detect changes in the bearing’s operating condition.
Compressor Speed Impact on Positive-Slope and Second-Quadrant Performance
Authors: Pronk Ola Ilseth , Bakken Lars Eirik
Published: January 2025

Rotational speed is a critical process variable that dictates the performance and dynamic behaviour of a compressor. Speed control, when possible, is the most effective method of optimising compression systems, while speed decay strongly influences machine rundown and stability. The speed affects the system and compressor responses during transient events, including trips and process disruptions. An accurate description of speed impact on off-design operation is needed to predict instability development and rundown trajectories in the surge area.

This study examines the off-design performance of a single-stage centrifugal compressor at five different speeds, focusing on the positive-slope and second-quadrant areas. Instability behaviour, system interactions, and second-quadrant characteristics are discussed based on experimental data. The second-quadrant characteristics of a stationary impeller with both an interlocked and a free-spinning shaft are shown.

Modified affinity laws are used to predict the machine response to speed changes in the unstable operating area. Similitude-compliant blowdown tests demonstrate speed scaling in the first and second quadrants. The speed significantly impacts surge development and the amplitude of surge oscillations, while the plenum volume affects the oscillation amplitudes, frequencies, and phase shifts. Finally, rundown trajectories showcase speed-related system dynamics in the off-design area.
The Development of the Awesome STEM Lab for the 21st Century Students
Authors: Gharib Mohamed
Published: January 2025

In this paper, the state-of-the-art STEM and fabrication lab, which spans the learning and fabrication applications for high school and freshmen college students, is pioneered and presented in detail. The lab was crafted from scratch to make the most of the available space for both learning and developing prototypes in a safe, efficient, elegant design and attractive environment for the students. The developed lab is called the Innovation Lab, which is a part of the educational STEM and outreach initiatives at Texas A&M University at Qatar. It is a space precisely designed and implemented to encourage students to learn, create, and innovate in a safe and efficient environment. The Lab was designed to be a destination for learners and educators from the community to come and use the state-of-the-art rapid manufacturing equipment and benefit from the STEM experts at the university. The developed lab is divided into two stations: the design station and the fabrication station. This paper details the designs, functions, and advantages of the elements in the developed lab to provide a guide for STEM lab designers and developers in establishing the labs needed by 21st-century students.
The Exergy Entity Environmental Analysis Applied to the Air Refrigeration Machine
Authors: Castillo Paz Jorge Renzo , Tsatsaronis George
Published: January 2025

This study showcases the practical application of the Exergy Entity Environmental Analysis (EEEA) for evaluating and improving energy conversion systems, particularly those operating below ambient temperature. Environmental impacts or footprints of the studied process, consolidated in a single score, are objectively distributed among all involved exergy entities based on two categories: one linked to the exergy source (E-footprint) and the other tied to the plant infrastructure (Y-footprint). Notably, this allocation process does not necessitate auxiliary equations, as well as product/fuel definitions at the component level. The circulation pathways of exergy entities (plant products, degraded and recirculated exergy streams) depicted by the Castillo Paz diagram are fundamental for this allocation. Furthermore, this method diligently examines the influence of decision variables on thermodynamic and environmental data, providing a valuable set of exergetic and exergoenvironmental variables, along with parametric charts to find design solutions in line with exergetic and environmental objectives. The simple air refrigeration machine (ARM) process serves as an academic case study, with the Eco-indicator 99 approach used to quantify environmental footprints. Our findings suggest that mitigating the overall exergetic imperfection of the ARM process typically results in reduced associated plant environmental footprint, as well as diminished environmental inefficiency.
A Data-Driven Design Pipeline for the Structural Optimization of Quadcopters
Authors: Subramanya Rishab
Published: January 2025

Unmanned aerial vehicles (UAVs), particularly quadcopters, are increasingly prevalent in hazardous scenarios such as disaster rescue or military reconnaissance. To tackle these issues, optimizing their structural integrity is crucial for enhancing their effectiveness. Currently, designers make improvements incrementally, which is time-consuming and expensive. This research paper uses data-driven design, performance prediction models, and AI-driven design recommendation tools to structurally optimize quadcopters (a subset of UAVs). The presented methodology offers a design assistant for human designers, satisfying rigorous design constraints through a streamlined and replicable process. The methodology involves creating a fundamental quadcopter model with nine parameters representing common features. Thousands of models were generated (and eliminated) via SolidWorks and further analyzed using finite element analysis (FEA) to quantify structural performance under identified loads. An Automated Machine Learning (AutoML) model predicts structural performance values and is validated using a variety of statistical and graphical metrics. Sensitivity analysis using SHapley Additive exPlanations (SHAP) identifies the relationship between parameters and performance values. Multi-Objective Counterfactuals for Design (MCD) suggest actionable design recommendations to optimize multiple queries simultaneously. This data-driven approach serves as a useful design assistant for quadcopter designers, holding potential for broader applications beyond structural optimization. Its replicable nature ensures applicability across various optimization domains.
Exploring Nickel Based Layered Double Hydroxides (LDH) as an Alternative of Platinum for Fuel Cell Applications
Authors: Alshweiki Ali , Olukeye Tiwaloluwa , Udeochu Uche , Bari Bushra , Tyagi Pawan
Published: January 2025

With the aim of developing fuel cell applications that are capable of generating efficient electrical energy, much of the attention should be given to exploring new catalysts that could be less costly and more abundant than the most commonly used catalyst, platinum. This work explores nickel-based layered double hydroxide (Ni-LDH) as a fuel cell’s affordable catalyst for Oxygen Reduction Reaction (ORR). Ni-LDH was prepared and drop coated onto a Glassy Carbon Electrode (GCE) to conduct a 3-way electrode cyclic voltammetry using an oxygen-saturated aqueous sodium hydroxide (NaOH) solution as electrolyte. The electroanalytical study of the GCE-modified Ni-LDH working electrode showed an enhancement of both anodic and cathodic peaks because of the presence of oxygen at low temperatures. Data obtained from this experiment will serve as a reference for fuel cell systems in which Ni-LDH modified working electrodes are scaled up for comparison of area-specific properties.
Characterizing Laminated Composite Materials Utilizing the Reinforced Mixed-Mode Bending Apparatus
Authors: Boutin William , Yekani Fard Masoud , Westby Maximillian , Norkus Tyler
Published: January 2025

The accuracy of fracture toughness is pivotal for the safety of composite and nanocomposite systems, with various techniques developed to measure fracture energy across different modes. Apparatus compliance issues arising from geometric non-linearities remain a significant concern and warrant further investigation. In the late 1980s, NASA introduced the Mixed-Mode Bending (MMB) apparatus to assess mixed-mode I-II strain energy release rates. Very recently, Arizona State University (ASU) researchers refined MMB into the Reinforced Mixed-Mode Bending (RMMB) apparatus for improved accuracy. This advancement involves redesigning MMB components to enhance stiffness and interlaminar fracture toughness measurements, crucial for predicting crack initiation and propagation accurately. Over the past three decades, laminated composite and nanocomposite materials have seen increased demand in aerospace, nuclear, and space technology due to their high strength-to-weight and stiffness-to-weight ratios. However, delamination remains a persistent challenge despite manufacturing improvements. Carbon nanotube (CNT) membranes have been employed to enhance mechanical properties and mitigate delamination, prompting extensive research into their integration with composites. The interlaminar fracture toughness of laminated composites reinforced with CNT membranes using the MMB & RMMB fixtures will be examined. Finite element analysis (FEA) will aid in understanding fixture compliance, energy release rate initiation and propagation, and fracture toughness envelope functions. Fracture tests comparing MMB and RMMB methods will be conducted, with load-displacement curves analyzed across various mixed-mode ratios.
Real-Time Detection of Negative Road Objects for Autonomous Vehicles to Improve Safety
Authors: Hag Ahmed Yousif , Li Wenyao , Anwar Sohel
Published: January 2025

This paper presents the preliminary results of our investigation in detecting negative road objects such as potholes and cracks in real-time for autonomous vehicles in order to improve safety. It is important to not only detect the existence of the negative road object from a safe distance, but also to identify the size, depth, and shape of such objects which plays a critical role in determining if the object must be avoided for safety or it can be ignored. We utilized open-source image databases such as ROBOFLOW (pothole) and RDD2020 of negative road objects for training a single layer convolutional neural network (CNN), such as YOLO. To test the trained algorithm, a small data set taken on the city streets in Indianapolis, IN was used in order to evaluate the accuracy of detection of the negative road objects. While the initial results show the ability of detecting the negative road objects through the proposed algorithm, more work needs to be done to improve the overall accuracy of detection with respect to size and shape of these negative road objects.
Performance Monitoring and Optimization of Robotic Production Lines: A Granular Approach for a KPIs-Based Study in Industrial Automation
Authors: Brunzini Agnese , Micucci Filippo Maria , Cappelletti Federica , Rossi Marta , Germani Michele
Published: January 2025

Technological innovation is profoundly transforming industrial production, notably through automated systems like robotic production lines. To harness their full potential, effective monitoring and evaluation are essential, facilitated by Key Performance Indicators (KPIs). This study conducts a thorough analysis of KPIs within industrial automation, focusing on a robotic production line assembling heat exchangers for refrigeration equipment. The aim is to measure, evaluate, and optimize performance in a smart, adaptable manner, creating a robust database that is not currently available as intended. Identified KPIs include standards such as cycle time, utilization, efficiency, and tailor-made metrics for this application, aligning with Industry 4.0 principles and sustainable manufacturing by monitoring energy and resource consumption as well. A granular data analysis approach captures the daily performance of each robot, enabling comprehensive assessment. Operational, daily, and line-level indicators provide insights into specific improvement areas. The methodology’s scalability allows for easy adaptation to larger production lines, highlighting its versatility and potential applicability across various industrial settings.

By proposing a granular and scalable KPIs framework, this research underscores the critical role of detailed performance monitoring in industrial robotics, driving continuous improvement and innovation while enhancing operational efficiency and competitiveness, in an ever-growing landscape of automated manufacturing environments.
Optimizing Aerodynamic Heating of a Mars Landing Vehicle: The Impact of Nose Angle and Aspect Ratio
Authors: Rhisat Fahad Nizam , Molki Majid
Published: January 2025

This paper presents a computational study of a Mars entry vehicle at three different Mach numbers: 5, 7.5, and 10. The study is two-dimensional and axis-symmetric. We simulated the entry vehicle for each Mach number with four different body lengths and nose angles. The primary objective of this study is to evaluate the impact of the Martian atmosphere’s viscous effects on aerodynamic heating. The computations used Unsteady Reynolds-Averaged Navier-Stokes (URANS) numerical simulations. The results demonstrate how nose angle and body length change the entry vehicle’s surface heat distribution. We conducted simulations to investigate the shockwave forming at the vehicle’s nose and the subsonic layer near its surface. The research highlights using computational models and simulations to explore aerodynamic heating during hypersonic flight and enhance the design of entry vehicles for secure landings on Mars.
Simulation of the Linearity and Sensitivity of Cantilever Beam-Based Relative Humidity Sensor With Peptidoglycan as the Functional Material
Authors: Fang Shuo , Chen Xi , Voiculescu Ioana
Published: January 2025

In this paper we present the MATLAB modeling of a cantilever beam humidity sensor based on peptidoglycan as sensitive material. This humidity sensor is conceived to monitor the humidity required for an actuating device fabricated from water-responsive paper. In order to produce dynamic response of the water responsive paper, the relative humidity should alternate between high level and low level of humidity. A humidity sensor with short response time that is sensitive and linear is required for this application. Peptidoglycan was chosen for this type of humidity sensor, because of its short response time. As a disadvantage, experiments with peptidoglycan showed the mass change versus relative humidity as not being linear. In order to improve the peptidoglycan linearity, we intend to fabricated a cantilever beam as support for humidity absorbent peptidoglycan. The cantilever bending as a function of relative humidity will be monitored by strain gage type of resistors.

The model of a cantilever beam was analyzed with MATLAB to explore methods to enhance the humidity sensor sensitivity and to find optimal geometry for the cantilever beam.
A Study on the Modeling Method of 3C Products Precision Assembly Based on Data-Driven and First-Principles Coupling
Authors: Shao Hongyu , Li Quanfu , Mi Xuefei , Tian Jiahan , Dong Shujun
Published: January 2025

3C products (Computer, Communication and Consumer electronics) assembly precision affects product quality and production efficiency directly. Aiming at the assembly process of 3C products, especially smart phones, this paper is proposing a coupling modeling method of data-driven and first-principle. Through the systematic analysis of the assembly error source, the corresponding dual-drive solution based on the engineering practice is proposed. Innovative coupling mechanisms such as mechanism analysis assisted data analysis fitting and data-driven explanation of unknown physical relations in mechanism analysis are proposed. Based on this model, big data and artificial intelligence technology are used to find the optimal combination of the best technical parameters and the control strategy under given environmental conditions factors. The modeling method was verified by taking the mobile phone frame dispensing as an example. The experimental results show that the dual-drive modeling method can quickly and accurately complete the modeling and control tasks, and obviously improve the product quality. High practical value and application opportunity are verified.
Dynamic Prediction of Heart Beating Rhythms Based on a Novel Model
Authors: Wang Xinya , Xu Yeyin , Chen Yuanhao
Published: January 2025

In this paper, an improved model of a cardiac conduction system with consideration of main pacemakers and heart muscles is proposed. The pacemakers consist of Sinoatrial node, atrioventricular node and His-Purkinje are simulated through three modified van der Pol oscillators with time delayed velocity coupling. The atrial and ventricular muscles are modeled by four coupled Hindmarsh-Rose (HR) neuron models which are also stimulated by pacemakers. The synthetic electrocardiogram (ECG) constructed through a combination of electric signals of atrial and ventricular muscles. An implicit mapping topology for the complex cardiac firings is established. Bifurcation criterion is defined to predict the period-doubled waveforms and the corresponding stability is defined by eigenvalue analysis. The cardiac firing results are presented to provide the normal and pathological rhythms in the cardiac conduction system. The presented study gives a new model to explore the nonlinear dynamics of heart beating.
Improving Human Reliability Analysis in Probabilistic Risk Analysis: A Novel Method for Analyzing and Modifying Performance Shaping Factor Dependencies in SPAR-H
Authors: Liu Xin , Yan Shengyuan , Zhang Xiaodan , Ahmed Waqas
Published: January 2025

The Standardized Plant Analysis Risk-Human Reliability Analysis (SPAR-H) method is widely applied in human reliability analysis (HRA) within the nuclear industry. Through expert judgment and predefined multipliers, SPAR-H calculates human error probabilities (HEPs) by quantifying the impacts exerted by performance shaping factors (PSFs). These multipliers adjust the nominal HEPs to account for specific situational factors within nuclear power plant operations. However, SPAR-H’s neglect of dependencies among PSFs often leads to unrealistic HEP estimates, underscoring a critical limitation of this approach. This study introduces a novel method that both qualitatively and quantitatively analyzes PSF dependencies within the SPAR-H framework to enhance the accuracy of HEP estimations. The method first uses denoising autoencoders (DAEs) to remove noise and extract relevant features from expert judgment data, then employs the decision-making trial and evaluation laboratory (DEMATEL) approach to analyze the influence relationships among the PSFs, and finally proposes a relative weight calculation method to modify the PSF multipliers. The findings suggest that this method significantly minimizes redundant calculations arising from PSF overlaps within SPAR-H, yielding more reliable and accurate HEP estimates.
Processing and Structure-Property Relation of Polypropylene/Nanosilica Nanocomposite Porous Structures With Solid-State Foaming
Authors: Almufarraji Said , Al Jahwari Farooq , Pervez Tasneem , Al-Kharusi Moosa
Published: January 2025

This study examined the development of polypropylene (PP)/nanosilica nanocomposite porous structures using solid-state foaming for advanced damping applications. By employing nanosilica, which is known for enhancing mechanical properties, and nitrogen as the blowing agent, this research aimed to create finely controlled porous structures within the PP matrix. The optimized extrusion process ensured a homogeneous nanoparticle dispersion that is important for consistent mechanical properties. Our findings demonstrated that adjusting foaming parameters, such as pressure up to 5000 psi, temperature at approximately 164°C, and nitrogen saturation time significantly affected the porosity and cell morphology. Specifically, the optimized conditions led to an average pore size reduction to 60 microns and a compression strength at 0.4% strain to 0.69 MPa with 0.1 wt% nanosilica. The foaming process resulted in a substantial weight reduction of approximately 86.43%, indicating a significant decrease in the material density which enhanced the composite’s potential application in lightweight structures and damping applications.
Advancements in Computational Modeling of Mechanical Properties of TPMS Lattice Structures
Authors: Abdelaal Ahmed F. , Al-Athel Khaled , Abubakar Abba , Akhtar Syed Sohail
Published: January 2025

Additive Manufacturing (AM) has revolutionized the fabrication of lattice structures, offering unparalleled customization of mechanical, thermal, and fluid-dynamic properties compared to traditional subtractive techniques. These intricate lattice configurations play a crucial role across diverse industries, such as medical, automotive, and aerospace, serving various functions including lightweight componentry, expansive surface area structures, and robust energy absorption systems. AM’s inherent flexibility allows for the production of highly intricate parts, including periodic lattice structures seamlessly integrated into complex surface geometries, thereby pushing the boundaries of conventional manufacturing methodologies. Within the realm of AM and lattice structure engineering, the utilization of Triply Periodic Minimal Surfaces (TPMS) stands out for its ability to confer unique mechanical characteristics. Recent research has focused on enhancing mechanical properties by introducing density gradients across TPMS lattice structures. However, a critical gap remains in understanding how these innovative designs influence compressive behavior. This study aims to address this gap by conducting a comprehensive comparative analysis of TPMS lattice structures fabricated via AM. Our investigation seeks to elucidate the influence of different TPMS structures on structural response under compressive loading conditions. our aim is to advance the understanding of AM-based lattice structure design and contribute to the development of high-performance components.
Surface Quality Enhancement of Additively Manufactured Parts Through Hybrid Additive Manufacturing Incremental Forming Approach
Authors: Tiwari Mithilesh Kumar , Ponappa K. , Tandon Puneet
Published: January 2025

Hybrid manufacturing (HM), integration of multiple manufacturing technologies, has revolutionized production methods. This paper introduces one such hybrid manufacturing method, Hybrid Additive Manufacturing Incremental Forming (HAMIF) approach, that seamlessly merges additive manufacturing (AM) and incremental forming (IF) in a single setup to enhance surface quality of additively printed parts. The experimental trials are conducted using a Tin alloy on the in-house developed HAMIF setup to fabricate specimens of AM sand HAMIF process. These specimens have undergone surface roughness testing using the Mitutoyo SURFTEST-SJ-500. Results demonstrated a remarkable improvement, reducing average surface roughness (Ra) from 0.3514 μm to 0.0555 μm. The optical microscopy analysis emphasizes the superiority of the HAMIF process in surface roughness and unidirectional grain formation, outperforming AM methods. The compacting effect induced during the HAMIF process reduces porosity and minor cracks, elevating surface quality. This offers a transformative solution for industries by advancing production capabilities and ensuring high precision of finished components. The HAMIF approach emerges as a promising avenue for augmenting surface quality in additively manufactured parts, presenting a significant step towards efficient and effective manufacturing processes.
Multiscale Investigation of Interfacial Adhesion Strength of Epoxy Resin Adhesives Over a Wide Range of Loading Rate
Authors: Takagi Aoi , Kasuya Yuto , Ogawa Masayoshi , Hosoya Yuichi , Yonezu Akio
Published: January 2025

For a reduction of aircraft structural weights, adhesive bonding has attracted attention to joint dissimilar materials. It often uses polymetric resin and it is well known that the strength of resin adhesives depends on the loading rate. Therefore, it is expected that the bonding strength of resin adhesive joints also shows a loading rate dependence. To investigate the effect of loading rate on bonding strength of epoxy resin adhesive with aluminum alloy, this study conducted three experimental methods with different loading rate: quasi-static test, Split Hopkinson Pressure Bar (SHPB) test, and Laser Shock-wave Adhesion Test (LaSAT). LaSAT utilizes an elastic stress wave (laser induced shockwave) generated by laser ablation to delaminate the adhesive from substrate at very high loading velocity. As a result, it is found that interfacial bonding strength significantly depended on loading rate. In addition, fracture toughness of the same adhesive joints was also investigated, and its loading rate dependency was discussed. Finally, in order to clarify the mechanism of the loading rate dependence, we investigated the deformation of the molecular chains using molecular dynamics (MD) and Finite Element Method (FEM) with cohesive zone modeling was employed to simulate a crack propagation for wide ranges of loading rate.
Manufacturing of Polymer/Magnesium Composite Scaffolds Via Stereolithography
Authors: Afridi Ambreen , Nuthana Kalva Sumama , Al Rashid Ans , Koç Muammer
Published: January 2025

Tissue scaffolds are developed/employed as a transitory framework to support the affected tissues and gradually degrade over the healing process. Finding the optimum material and technique for fabricating bone scaffolds has been the main focus, as implants must sustain structural strains, promote tissue proliferation, cell growth, and vascularization, and ensure biocompatibility. In this regard, polymers and their composites have found widespread use in fabricating three-dimensional (3D) porous scaffolds due to their remarkable properties. Stereolithography (SLA) is an additive manufacturing (AM) technique used to manufacture intricate and complex bone scaffolds using polymers or composites that can be customized according to patient-specific anatomical needs — shape, size, and mechanical properties. This study explores the potential of incorporating Magnesium (Mg) nanoparticles into photocurable resin for bone implants manufactured through SLA. Magnesium, a renowned metal for its biocompatibility, biodegradability, osteoconductivity, and mechanical attributes, is suitable for tissue engineering. A photocurable resin was blended with different concentrations (wt.%) of Mg alloy, followed by AM and photocuring, to assess their printability and the impact of optimization on the 3D-printed structures. Physicochemical characterization was conducted to evaluate the effects of magnesium incorporation on the thermal stability and degradation properties of resin-Mg composites.
Ball Screw Surface Faults Modeling and Detection for Electromechanical Flight Control Actuators
Authors: Bertolino Antonio Carlo , De Martin Andrea , Guida Roberto , Bencivinni Gabriele , Sorli Massimo
Published: January 2025

Ball screw faults are the major contributors to the known safety limitations of electromechanical actuators (EMA), which hinder their wide adoption as the main technology for primary flight controls in the aerospace sector. To overcome this issue, a promising approach is represented by the construction of a Prognostic and Health Management (PHM) framework around a simple architecture EMA to monitor its health state. A high-fidelity model of the entire servosystem represents a valuable tool for generating synthetic databases with a variety of simulated defects to train PHM routines. This paper introduced a detailed dynamic model of an EMA, designed to facilitate model-based PHM routines, composed of a three-phase motor description and a high-fidelity multibody model of the ball screw, capable of representing the full dynamics of each internal sphere independently. This allowed the description of a localized defect model implemented on the nut raceway to simulate superficial defects of various entities. The impact of such faults on the system’s response is explored by analyzing the NA-MEMD based HHT spectra of ball screw kinematic signals and internal contact forces on the various spheres. The results verified the efficacy of the proposed model and open avenues for more comprehensive analyses and future investigations on defect detectability and isolation.