bluuebunny/crossref_metadata_2025 huggingface dataset:
Identification of Carbon Diffusivity of S9310 Utilizing Correlated Numerical and Experimental Investigations
Authors: Xu Dong , Kim Jeongho , Frame Lesley D. , Tang Jiong
Published: February 2024

The characterization of carbon diffusion behavior in austenite is essential for the design and implementation of heat-treating processes. Traditional carbon diffusion models may not accurately predict the carbon diffusion profile of alloy steels such as S9310. Indeed, the local carbon concentration of the alloy affects the rate of carburization, and thus carburization parameters should be considered as a function of carbon concentration. In this research, we first establish a systematic approach of modeling the low-pressure carburizing (vacuum carburizing) of S9310. By assessing the finite element simulation results and comparing them with experimental data, we preselect a carbon diffusion model architecture. In this model architecture, the carburization parameters are functions of both temperature and carbon concentration. We then carry out parametric identification by correlating numerical analysis with experimental result. Specifically, an optimization problem is formulated which identifies the coefficients in the carbon diffusion model by minimizing the difference between the finite element simulation and the experimental data in the parameter space under different operating conditions. The proposed carbon diffusion model can generally lead to better matching between numerical simulation and experiment. The outcome of this research can benefit the carburization process of S9310.
Development of Nickel-ZIF-8 Doped Nitrogen Reduced Graphene Oxide Catalytic Materials for PEM Fuel Cell
Authors: Shirzadi Jahromi Hassan , Saxena Shivi , Sridhar Sudharsan , Ghantasala Muralidhar K. , Guda Ramakrishna , Rozhkova Elena A.
Published: February 2024

This paper presents the results of our investigation on new catalyst materials for Proton-exchange membrane (PEM) fuel cells. The sluggish kinetics of the oxygen reduction reaction (ORR) and poor electrochemical durability of platinum-based catalysts necessitated the study of new materials. Recently, pyrolytic transition metal nitrogen-carbon material (M-N-C) based catalysts have gained considerable attention for their unique electronic structure and other physical properties, which can facilitate better ionic and electronic conductivities. Specifically, nickel-nitrogen-carbon (Ni-N-C) catalysts have demonstrated favorable catalytic activity and durability due to their fast electron transfer rates and improved kinetic reaction rates. This study describes a facile method for synthesizing Nitrogen-doped and pristine reduced graphene oxide (N-rGO and rGO) with Metal-Organic Framework (MOF) material, in making N-rGO-Ni-ZIFx and rGO-Ni-ZIFx Several characterization techniques, including FTIR, Raman spectroscopy, XRD, SEM, and EDS, were employed to assess the physical and chemical properties that impact the electrochemical performance of the synthesized materials. Based on the results obtained, it can be inferred that the inclusion of the transition metal and the process of high-temperature pyrolysis (at 600°C) have a considerable influence on the improvement of ORR activity. The N-rGO-Ni-ZIFx-600 sample exhibits superior ORR activity in acidic media, displaying comparable redox peaks to those observed with the commercially available 40 wt% Pt/C catalyst. The correlation of different properties with their respective electrochemical activity is discussed in this paper.
Raster Angle and Infill Percentage Influence on Selected Mechanical Properties of 3D Printed Polyethylene Terephthalate Glycol (PETG) and High Impact Polystyrene (HIPS)
Authors: Adams Aaron , Coates Cameron , Carlson Eugene , Tiller Andrew
Published: February 2024

This work investigated the influence of raster angle and infill percentage on selected mechanical properties of two commonly used 3D Printed materials: Polyethylene Terephthalate Glycol (PETG) and High Impact Polystyrene (HIPS) at room temperature. Their Elastic Modulus, Yield Strength, and Toughness were experimentally determined and compared for infill densities of 5%, 25%, 50%, 75%, and 100%, and raster angles of 0/90, 45/45, and 30/60. The materials were printed using Fused Deposition Modeling per ASTM D638-22 standards, with a layer thickness of 0.3 mm, an initial layer speed of 35 mm/s, and an infill speed of 50 mm/s. The initial layer speed and infill speeds were 35 mm/s and 50 mm/s, respectively.

The team concluded that PETG material, on average, outperformed HIPS when looking at Young’s Modulus of the printed samples. There are few instances where HIPS has a higher Young’s Modulus, i.e., 45-45 at infill 100%, 45-45 at infill 50%, and 30-60 at infill 100%. The PETG samples often exceeded the toughness of HIPS as well. As seen in the tables, there are a few cases in which HIPS has much higher toughness than the same raster and infill percentage as PETG. For instance, HIPS samples at 0-90 angles and infill percentages of 50% and 75%. Overall, the team concluded that PETG, on average, outperforms HIPS in both Young’s Modulus and toughness during the testing. PETG would be suitable for most situations, whereas HIPS would fail more often if substituted for PETG.
Design and Development of Shape Memory Polymer-Based Mechanical Thrombectomy Device
Authors: O’Brien Rory , Moritz Vicente , McDonald Paul , Devine Declan , Srivastava Rupal
Published: February 2024

In the biomedical industry, research and application of shape memory polymers (SMP) have mainly been focused on drug-delivery implants, stents, orthopaedic devices, tissue engineering, and wound closure. Little focus has been given to using SMP as delivery catheters or access devices, which can benefit from greater flexibility and larger deformation relative to metals. This work aims at designing and developing a thrombectomy device prototype using an SMP at the distal tip of a microcatheter, which would recover to a desired shape to act as a retrieval mechanism, removing a thrombus from an occluded artery in an acute ischemic stroke. The catheter was built using a polytetrafluoroethylene (PTFE) liner substrate, braided reinforcement, a Pebax jacket layer, and a coiled copper wire heating element. A shape memory polyurethane (SMPU) was extruded and reflowed over the copper coil. The SMPU was shape-set into a helical shape and was then formed into a temporary straight shape. Thermomechanical testing of the SMPU demonstrated the effect of temperature on the mechanical properties, as when the polymer was heated above the transition temperatures, the mechanical behaviour changed, resulting in a lower stress but a greater strain rate. Applying a direct current to heat the copper coil and cause a thermal stimulus in the SMPU successfully induced a shape recovery of the distal tip to its original helical shape. Within this frame of reference, this work describes an SMPU tubing material with a straight secondary shape that can recover its coiled primary shape once thermally stimulated. The prototype further strengthens the experimental success.
Thermal Simulations of a Composite Grid Structure Boom for Small Satellites
Authors: Scigliano Roberto , De Simone Valeria , Totaro Giovanni
Published: February 2024

Italian Aerospace Research Centre (CIRA) has been working on composite grid structure for many years in the context of many EU / ESA challenging research programs like the Interstage 2/3 of the Vega C launcher. Small satellite industry demands more and more low mass structure to increase electronic payload. Grid structure seems to answer this request, but it is crucial to be able to predict numerically the performance of such structure. Indeed, such new structures are usually made of very thin and light materials which complicates the on-ground tests prior the launch. This paper presents a finite element modelling of a composite grid boom working on a LEO small satellite. In particular, a preliminary thermal assessment and a subsequent thermo-structural analysis to estimate the material safety w.r.t the designed orbit has been performed.
SWARM Applications Using Commercial Robots
Authors: Augustine Emmanuel , Shin Minchul
Published: February 2024

This research aims to develop a robot swarm system for investigating highly uncertain terrains in space. The system consists of multiple robots that can self-assemble, equipped with an onboard microcontroller. The project aims to develop algorithms for edge-following, gradient formation, localization, self-assembly, and connection to enable cooperative operations within the swarm. Bluetooth and time-of-flight sensors will be used for communication and distance measurement, respectively. The development of the algorithms involves mathematical modeling, simulation, and experimental testing. The results section will present preliminary findings of the experiments, highlighting the potential performance of the swarm system in various tasks. The proposed work contributes to the field of robotics and space exploration and offers scientific merits and educational opportunities.
Effect of Stress Triaxiality on Creep Deformation of Polyaramid-Reinforced Elastic Cements
Authors: Contreras Elizabeth Q. , Heinold Thomas , Martinez Roland F. , Johnson Kenneth D.
Published: February 2024

New methods for long-term performance evaluation based upon tri-axial load cell measurements are presented, quantitatively analyzing the reliability of new polyaramid-reinforced cement material by measuring cumulative fatigue damage to predict long-term failure. Compressive strength, Young’s modulus, and Poisson’s ratio measurements under dynamic force loading conditions result in the overall design of innovative polyaramid additives applied as non-metallic alternatives for the improvement of mechanical properties of high sulfate resistant Portland cement (HSR). In this study, strain-controlled cyclic tests to measure mechanical properties showed aramid-reinforced cements with 1.6% to 4.5% and 11% permanent strain (maximum) when compared to neat cement (with no admixture) at 30% permanent strain. Enhancement to cement mechanical properties is attributed to the unique response by novel polyaramid-reinforced samples under extreme strain-stress cyclic conditions up to 40 MPa. From this data, various new polyaramid-reinforced cements showed energy storage (low YM) and low strain rate, potentially prolonging the lifespan of HSR Portland cement without sacrificing compressive strength.
Optimization of Heat Exchanger Network via Pinch Technology: a Case Study of a Dairy Facility in Italy
Authors: Abbate Simona , Di Bartolomeo Marco , Giordano Lorena , Benedetti Miriam , Carapellucci Roberto
Published: February 2024

Process integration via pinch technology is widely regarded as an effective approach to boost industrial sustainability and competitiveness by reducing process-related energy and material consumption and environmental impacts. So far, such approach has been mainly applied to energy-intensive processes. As a result, industrial sectors like the food industry still offer wide margins for energy efficiency improvement via pinch analysis. As well known, food manufacturing requires many process operations, such as pasteurization, sterilization, and drying, which involve the heat transfer between products and heating/cooling media. Therefore, the design and optimization of heat exchanger network is crucial to minimize external heating and cooling requirements and improve the recovery of waste heat streams. In this paper, a flexible open-source model is proposed for the design or retrofit of industrial heat exchanger networks (HENs) via pinch-analysis. The model is used to investigate a real dairy process for cream production with the aim to identify the energy saving opportunities and assess the potential techno-economic and environmental benefits. The study found out that the design of the heat exchangers network under conditions of maximum energy recovery results in a significant reduction of 95.8 kW in the thermal power exchanged with external utilities. This improvement provides a reduction in the thermal power of hot and cold utilities by 48.5% and 44.9% respectively compared to the reference case.
Stiffness Degradation in CFRP Laminates Subjected to Fatigue Loading
Authors: Prakash Raghu V.
Published: February 2024

Reinforced polymer composite materials are widely used in aerospace, marine or other civilian structures, as it offers the advantage of tailor-suiting to the design requirements. During service, they undergo damage due to service loading, environment as well as accidental bird hit (in case of aircraft), and tool drops during maintenance. Low velocity damage causes a barely visible impact damage (BVID), which is largely conspicuous has the potential to become a serious concern, if the structure undergoes fatigue loading subsequently in-service; the damage progression results in the loss of residual strength and stiffness of the component.

As a part of this study, the stiffness degradation for a woven mat carbon fiber (500 gsm having a nominal thickness of 0.42 mm) polymer composite specimen where the mat is laid in: a) 0–90 orientation and b) quasi-isotropic configuration [0–±45/90]s is examined after it has been subjected to a low velocity drop-impact of 53 J. After the drop impact, these specimens are subjected to constant amplitude loading (0–90 orientation) and to a programmed version of FALSTAFF (Fighter Aircraft Loading Standard for Fatigue) spectrum.

The unloading stiffness of the specimen was estimated from the load versus displacement data that was recorded at periodic intervals of 10000 cycles for the experiments under constant amplitude loading and after every block of FALSTAFF loading, i.e., after 1242 cycles of programmed load application. It is observed that the stiffness of the specimen degrades with the progression of damage. The stiffness degradation is found to have characteristic three stage response and can be corresponding to the three stages of damage progression. Infrared thermographic record of temperature response during fatigue testing was done to understand the damage progression. It was noted that the stiffness degradation was the highest under constant amplitude loading, followed by the spectrum loading.
Local Pursuit Strategy-Inspired Cooperative Formation Flight and Collision Avoidance for UAV Cluster
Authors: Wang Yi , Li Ni , Wang Ban , He Xuemin , Zhu Yongning , Zhou Ming
Published: February 2024

The unmanned aerial vehicles (UAV) cluster, compared to a single UAV, has better application potential in implementing complex and dangerous tasks. In recent research, cooperative formation control strategy and obstacle avoidance have always been focused to secure the safety of flight and task implementation. In this research, we propose the Local Pursuit (LP) strategy-inspired cooperative flight and collision avoidance model inspired by foraging ants, which consists of a formation control module and an obstacle avoidance module. In the formation control module, under the guidance of LP strategy, the follower UAVs will always point their velocity towards the leader UAV (which can be virtual) like ants following the ant ahead. Meanwhile, the velocity and formation position of each follower UAV can be adjusted by the ‘speed control parameter (SCP)’ related to the speed of the follower and the constant bias between the leader and the follower which is determined by the desired formation. Considering there are cases that some areas threatening the safety of the UAV need to be avoided, which can be regarded as external obstacles, an obstacle avoidance module based on velocity alignment with “shill” agents (virtual UAVs moving outward from obstacles to real UAV) is added for effective obstacle avoidance. The proposed method has limited parameters that need to be tuned. Finally, to show the efficiency of the proposed method, the simulations of UAV cluster formation flight and obstacle avoidance by using the proposed method are conducted through MATLAB.
Extrusion Mechanisms for Printing Thermosetting Prepolymers
Authors: Danish Muhammad , Mishra Ravi , Junaid Abid Ali , Emon Omar Faruk
Published: February 2024

The Direct Ink Writing (DIW) additive manufacturing method has been widely used in advanced printing applications, although it is often considered a complex and expensive system to construct. This study investigated two extrusion mechanisms that can be integrated with a gantry system for printing functional thermosetting inks. The first mechanism employs a lead screw directly connected to a bipolar stepper motor, which converts the rotary motion of the motor shaft into a linear motion. The lead screw is used to push the plunger of a syringe loaded with viscous thermosetting prepolymers. The second mechanism employs a gear system to transmit the motion from the motor shaft to the lead screw. The mechanical fixtures to hold the motor, lead screw, gears, and other components were designed and fabricated via 3D printing. Different gear ratios were examined for the gear-based system. An acrylate-based photocurable resin was thickened using fumed silica to induce non-Newtonian shear-thinning property. The study focused on various print parameters, including print speed, extrusion rate, linewidth, and ink viscosity, and tailored G-code commands were used to print different inks. The printed structures were photopolymerized using ultraviolet (UV) light. The printed outcomes were evaluated, and two extrusion mechanisms yielded comparable results. It is believed that the proposed system will make 3D printing of functional inks more accessible.
Autonomous Vehicle Guidance Using Neural Network and Random Forest Model
Authors: Gadhvi Tirth , Shankar Praveen
Published: February 2024

In this paper, a guidance strategy for autonomous vehicles aimed at preventing collisions caused by faulty sensor data is presented. A kinematic bicycle model is utilized to generate a vehicle motion dataset for training the prediction models. The algorithm employs a random forest prediction model, utilizing a neural network generated dataset to minimize errors in planning the motion. As a case study for implementing the guidance algorithm, a freeway entrance ramp scenario was simulated utilizing MATLAB. The guidance strategy addresses the limitations of GPS-based autonomous vehicle navigation systems, which may experience inaccuracies due to atmospheric conditions and other factors, thereby preventing collisions under such conditions of error.
Machine Learning Accelerated Atomistic Simulations for 2D Materials With Defects
Authors: Sun Shijie , Singh Akash , Li Yumeng
Published: February 2024

2D materials generally show very different physical and chemical properties from 3D materials, which provide them promising applications in cutting-edge technology areas like aerospace, energy storage and electronics. To better understand and illustrate their unique properties, current research heavily relies on atomistic simulations, while successful simulations require the high reliability of interatomic interaction potentials that empirical potentials cannot provide. The ab initio calculations, for example density functional theory (DFT), are able to conduct high-fidelity simulations in essence, but with a high computational cost and largely limited simulation size. Recently machine learning potentials become a trend to interpolate the potential energy surface based on artificial neural networks (ANNs) with reference datasets from first principle calculations. Although machine learning potentials have been developed for many material systems including 2D materials, there is limited work published regarding structural defects. Using graphene as a model material, we demonstrate a new machine learning potential for 2D materials with defects. The reference energies are generated by DFT calculations. ANN with two hidden layers is used for the training, which has been demonstrated to be suitable for developing machine learning potential in our previous work. For ANN input, the atomic structures are coded using perturbation-invariant representations. After training, the weight and bias parameters are exported as our potential and then imported into LAMMPS software to conduct MD simulations. It is expected that our work provides fundamental support on investigating defective graphene and understanding defect effects to develop structure-property relationship. This will also promote the development of machine learning based simulation tools for the study and design of complex materials.
Analysis and Modeling of the Laser Bore Joint to Prevent Alignment Failures
Authors: Troise Mario , Sorli Davide , Gaidano Matteo , Melchiorre Matteo , Palmieri Pierpaolo , Mauro Stefano
Published: February 2024

The DEMOnstration (DEMO) reactor, the next-generation fusion power plant, requires plasma-facing components (PFC) to be periodically replaced during the reactor lifetime. However, a remote maintenance (RM) is needed due to neutron activation. A relevant RM operation is the replacement of piping supplying around the plasma chamber using a Service Joining System (SJS) for in-bore cutting and welding. Welding operation demands strict alignment requirements obtained with appropriate RM strategy. Therefore, alignment task involves a first phase of positioning during which the new pipes are brought close to their final position by a main system, and in second phase a robot system drives pipes extremity achieving precise coupling. This paper presents the multibody model of Laser Bore Joint (LBJ) of SJS focusing on flexible elements, named bellows, that provide compliance both in axial and radial direction during alignment tasks. The LBJ model is built in Adams environment and a suitable sensors layout is devised to assess the misalignment state in the case of failure in the first alignment phase. The secondary handling device is introduced and its control strategy is implemented in a co-simulation framework with the multibody system. Results underline the feasibility of proposed alignment procedure.
Toward Additive Manufacturing of Architected Materials: A Planar Analysis
Authors: Liu Jitian , Armand Mehran , Kutzer Michael D. M.
Published: February 2024

The term architected material describes a class of materials whose physical properties are determined both by material properties and geometry. These materials play an increasingly crucial role in various fields including research, medicine, and industry. Due to its ability to produce complex geometries, additive manufacturing (AM) technology has been widely adopted in the fabrication of architected materials. Nonetheless, in most scenarios, AM is only applicable to the geometries containing open voids. This effort investigates the feasibility of fabricating geometries that contain closed voids via support-free AM. This initial investigation considers planar part geometries produced using a three-degree-of-freedom (3-DoF) task space. Part geometry is defined as a two-dimensional (2D) polygon containing convex polygonal holes. Using this assumed part geometry, this work partitions the part using a set of polygons that are ordered using feasible layering directions and collision constraints. Because the 3-DoF task space enables re-orientation of the part during fabrication, the overhang constraints (defined relative to the gravitational vector) can be addressed by rotating the part. Results show a method of generating and ordering polygons that can be printed subject to collision and overhang constraints.
Preliminary Dynamical Model of the LISA/LISA-Pathfinder Release Mechanism
Authors: Tomasi Matteo , Zanoni Carlo , Vignotto Davide , Bortoluzzi Daniele , Dalla Ricca Edoardo
Published: February 2024

LISA Pathfinder (LPF) is a space mission launched in 2015 aimed at testing key technologies for LISA, the first gravitational wave observatory in space. The LPF payload includes two gravitational reference sensors (GRSs), each one hosting a floating test mass (TM). The grabbing, positioning and release mechanism (GPRM) injects the TM into the scientific free-fall state, satisfying strict position and velocity requirements at release. In LPF, the TMs acquired non-compliant velocity at the release, compatible with spurious impacts with the GPRM. The impacts could be caused by oscillations of the mechanism due to the impulsive retraction of a piezo-driven release tip.

Ground-based measurements of the GPRM dynamic response show vibrations triggered by the quick tip retraction together with a static deformation at steady state, so far unnoticed. In this work, we build a lumped parameters model, validate it by matching the experimental data, and use it to understand the mechanism dynamics. Moreover, we reshape an existing GPRM finite element model to the analysis of vibrations, in order to provide a physics-based tool to explore different designs and conditions. We present here the preliminary results of these activities.
Food Quality Inspection and Sorting Using Machine Vision, Machine Learning and Robotics
Authors: Drogalis Conor , Zampino Christopher , Chauhan Vedang
Published: February 2024

The integration of Industry 4.0 technologies, such as machine vision, machine learning, and robotics, has transformed the food industry by enabling more efficient, accurate, and productive food quality inspection. This scope of this work is to implement these technologies in the inspection of chocolate chip cookies in a lab based setting. The PC-based system includes a conveyor belt, webcam, low-cost robotic arm, grayscale sensors, and MATLAB and Arduino microcontroller for communication between the vision system and the robot. Machine vision captures images of cookies and processes these images for feature extraction, while machine learning algorithms classify cookies based on their visual features and identify defects. The use of Artificial Neural Networks for training and testing results in an overall accuracy of 95% and 90%, respectively. The sorting of cookies based on the machine learning classification is carried out using a robotic arm. The robotic arm receives signals from the ML algorithm to remove defective cookies from the conveyor into a rejected cookies bin. The closed-loop system effectively (98%) inspects food quality, reducing defective food from reaching consumers. Machine vision and machine learning techniques offer a promising approach to improving quality control in the food industry.
Using Validation Metrics to Assess RANS Turbulence Models Performance at Full Scale Reynolds Numbers
Authors: Eça Luis , Kerkvliet Maarten , Toxopeus Serge L.
Published: February 2024

One of the major advantages of Computational Fluid Dynamics (CFD) is the ability to simulate flows at full-scale Reynolds numbers, which for naval applications can reach values of 109. For this range of Reynolds numbers, the Reynolds-averaged Navier-Stokes (RANS) equations are still the most common mathematical model. The averaging procedure used to derive the RANS equations generates the Reynolds-stresses that are determined by a turbulence model. In the last 50 years several turbulence models have been proposed in the open literature ranging from the initial eddy-viscosity algebraic methods to Reynolds-stress models that solve 7 additional transport equations. The assessment of the modeling error of RANS simulations requires the existence of experimental data and so most of the reported exercises of modeling error assessment are performed at model-scale Reynolds numbers. Furthermore, many of these studies rely on simple graphical comparisons without the quantification of experimental, numerical and input uncertainties.

In this paper we apply the V&V20 validation metrics to quantitatively assess the modeling error of RANS using six different turbulence models in the simulation of the flow around the KVLCC2 at model-scale Reynolds number, for which experimental data are available at six cross-sections of the stern and near-wake region including the propeller plane. It is illustrated that graphical comparisons are less conclusive than the quantitative assessment of the modeling error taking into account uncertainties of experiments and simulations.

The same validation metrics are applied to quantify the differences between simulations performed with the same models at full-scale Reynolds number. The results show quantitatively that differences between the results obtained with the six turbulence models at full-scale Reynolds number are much smaller than those observed at model-scale Reynolds number. In the absence of experimental data at full-scale, such exercise suggests that the role of the turbulence model in full-scale flows around ships is not as important as in model-scale simulations.
Influence of Agility on the Innovation Capability of Organizations - An Empirical Study
Authors: Schoeck Moritz , Batora Mona , Mueller Johannes , Bursac Nikola , Albers Albert
Published: February 2024

In today’s dynamic market landscape, mechatronic product development faces challenges due to changing customer demands and unpredictable events. To secure organizations’ innovation capability in this environment, agile methods have gained prominence. Previously, the authors identified success factors and characteristics of agility and innovation capability through extensive literature research. This study now focuses on establishing cause-effect relationships between agility and innovation capability using these factors. An empirical study involving professionals from diverse industries explores how introducing agility in mechatronic product development can improve organizational innovation capability. The findings indicate that agility positively influences innovation capability to varying degrees. This research contributes valuable insights to enhance the innovation capability and agility of industrial organizations sustainably. By embracing agile approaches, organizations can thrive in the face of a dynamic market environment.
Characterization of Functionalized Nanodiamonds in Mineral Oils for Transformer Applications
Authors: Swiecichowski Patrick , Nevills Miles , Languri Ethan , Davidson Jim , Costa Lino , Kerns David
Published: February 2024

The use of transformers for varying the voltage in a power grid is heavily limited and determined by its thermal management. This thermal management is largely based on the mineral oil that surrounds the core of the transformer, this mineral oil dissipates the heat that is produced by the core of said transformer. The current mineral oil that is used is a dielectric, that restricts the ability to conduct electricity, and is widely used since the thermal properties of the mineral oil are high compared to the low cost of the mineral oil itself. The improvement in the heat transfer of the transformer not only increases its lifespan but also increases the capacity for the throughput of power. With electrification being an increasing focus, the demands on the power grids are only increasing as time passes. Nanodiamond-enhanced mineral oils present a potentially novel and surprisingly inexpensive solution to increase the heat transfer rate from transformers fins, leading to an increase in grid throughput capability. By using the nanodiamond-enhanced mineral oil, potentially little to no alterations to the current design of the transformer would be necessary. Because all that would need to be changed would be the mineral oil surrounding the core, this means that most transformers currently in use could also be enhanced, reducing the cost by not manufacturing another replacement transformer and just replacing the mineral oil inside. This is also a passive solution compared to active solutions such as circulating pumps for the oil dissipating the heat through an exchanger, so there is no added mechanical complexity or electrical consumption. This paper investigates the physical and thermal properties of functionalized nanodiamonds in mineral oils at various concentrations. A detailed discussion of multiple properties of the fluids will be performed including: how the introduction of the functionalized nano-diamonds to the mineral oil affects the thermal conductivity the mineral oil experiences, how the change in the mineral oil affects the viscosity and how this change in viscosity might impact the function of the transformer, how this change in the mineral oil affects the specific heat capacity and the potential impact this might have on the longevity and efficiency of the transformer system, and lastly, how the density of the mineral oil is impacted and what kind of implications or complications this might pose for the prolonged use in transformers. This paper will also take a look into the changes that adding the functionalized nano-diamonds to the mineral oil will have on the oil itself, microscopically, and the interactions it might experience by using Scanning Electron Microscopy, Dynamic Light Scattering, and X-ray Diffraction.
Spatially Resolved Ion Current Density Measurements With a Transient Insertion Langmuir Probe
Authors: Martin Christopher R. , Orr Jacob , Rahman S. M. Mahbobur , Untaroiu Alexandrina
Published: February 2024

This work presents a novel technique for constructing spatially resolved ion densities from Transient Insertion Langmuir Probe (TIL Probe) measurements in a flame. Similar to a tomographic transformation, this technique is used to deduce the spatial distribution of ions in a flame from many individual measurements that are integrated along a probe’s length. We demonstrate the approach in the oxyfuel cutting torch preheat flame, which presents two severe challenges for electrical measurements: (1) temperatures over 3,000K destroy most probes made from alloys with appropriate chemical stability, and (2) the relevant length scales are on the order 0.15 mm. Presented here are (1) a Fourier series formulation for the current density, (2) a least-square problem for calculating the coefficients, (3) criteria for the highest wavenumber allowed in the expansion, (4) description of an experiment used to measure probe currents in an oxyfuel cutting torch preheat flame, (5) solution for spatially resolved current density in the oxyfuel cutting torch flame.

Images of ion current density are produced with a resolution of 0.15 mm (0.0059 in), exhibiting peak current densities around 14 μA/mm. It is found that low-signal regions in the “shadow” of high-signal regions can suffer from signal-to-noise ratio problems due to natural fluctuations in the flame, and improvements are proposed to mitigate the effect. It is found that the numerical cost of setting up the resulting Hermitian-matrix linear problem far exceeds the numerical cost of inversion. High-level packages like Python and MATLAB are far too slow, so a multi-threaded algorithm is implemented in C, and the LAPACKE C library is used for efficient linear algebra support.
In-Situ Dynamic Strain Sensing Using Mechanized Air-Atomized Sprayed Flexible Nanocomposite Sensors
Authors: Li Pengfei , Xu Chao , Su Zhongqing
Published: February 2024

Nanocomposites are gaining popularity in the field of structural health monitoring due to their ability to sense structural dynamic strain. This paper introduces a breed of flexible nanocomposite sensors manufactured by mechanized air-atomized spray coating process. The employed method not only enables the automation and continuous production of nanocomposite coatings, raising efficiency in production, but also allows for precise control of spraying parameters to reduce the impact of human factors, ensuring coating uniformity and quality. Flexible nanocomposite sensors are fabricated by doping carbon black nanoparticles in polyvinylpyrrolidone powder with the mechanized air-atomized spray coating process. Experimental results indicate that the flexible nanocomposite sensors can effectively respond to vibration-induced dynamic strain. The flexibility and sensitivity of these sensors make them promising for use in various structural health monitoring applications.
A Project-Based Pedagogical Approach for Mechanical Design Course in Extremely Small Classes
Authors: Guo Guodong , Rodriguez Jonathan , Guerrero Dominga , Tapia Omar Alejandro
Published: February 2024

The uniqueness of the Texas A&M University High Education Center McAllen (HECM), being 380 miles from the main College Station campus, is its small learning and teaching environment. The center was first opened to students in Fall 2018 with only the engineering program offered. In its fifth year of operation, the total enrollment has rapidly grown to 340 full-time undergraduate students across 8 programs, of which 109 are engineering students. In the last five semesters, the enrollment in each of the junior/senior engineering courses is around 3, which is much less than the national average class size of 24, as of 2022. While the campus is striving to double the enrollment over the next five year, in its current stage, the small teaching/learning classes has created many challenges to both the instructors and the students in a modernized classroom installed with the newest education equipment. The author has had the honor to teach in such an environment in the pass two semesters (Fall 2022 and Spring 2023), and teach the course Mechanical Design Application I (MMET 363) in the two consecutive semesters. The condition of small class size has been successfully transformed into a strength to boost the learning efficiency of the students. In this paper, the authors share the experience of employing a project based pedagogical approach to enhance students engagement and learning efficiency. The author believes that, as many prestigious universities and high education institutes are eager to expand their service to local communities by building remote campuses, the approach described in the current research will provide invaluable reference into these efforts.
Satisfaction and Intercultural Competence During an Erasmus Program: a Case With Industrial Engineering Undergraduate Students at the University of Minho, Portugal
Authors: Carvalho Violeta , Rocha Carla , Campinos Jorge , Teixeira Senhorinha , Vieira Filipa D. , Rodrigues Cristina S.
Published: February 2024

Every year, European higher education institutions have numerous Erasmus opportunities for students who wish to embrace the experience of study abroad and intercultural exchange. The high involvement of the Portuguese University of Minho in the promotion of the Erasmus Program has resulted in many undergraduate and graduate students being interested in participating in the program. In light of this, the Erasmus coordination of the university’s Department of Production and Systems (DPS) has decided to develop a continuous improvement tool that brings together information from its Erasmus students in mobility “out” and shares individual experiences with future participants. To this end, three different online questionnaires were developed and applied before, during, and after the experience. Results from the second questionnaire applied during the Erasmus Program suggest difficulties with academic support from host professors and in relationships with host university staff. Despite that, results also suggest high levels of satisfaction and identification with the host university, positive host campus non-discrimination experiences, and good levels of intercultural competence, particularly in awareness. No significant relationships were identified considering respondent gender, type of class, or language of the class (only two exceptions were identified). The results show an overall positive “during Erasmus” experience.
High-G Survivable MEMS Three-Axis Accelerometer
Authors: Hader Grzegorz , Smyth Jeffrey
Published: February 2024

This paper investigates the design and analysis of a polysilicon MicroElectroMechanical Systems (MEMS) inertial sensor. The planar MEMS accelerometer design measures acceleration in all three axes using a single chip. The 400-micron square polysilicon planar chip is comprised of a circular proof mass (x-y axis) with four inter-digitated arms attached to an outer frame via four crab-like legs to measure in-plane accelerations. A cantilever beam is integrated within the circular proof mass to allow for out-ofplane (z-axis) measurements. The MEMS accelerometer can be fabricated using standard integrated circuit microfabrication techniques. The accelerometer’s response to a 12,500 g (axial) and 1,000 g (radial) dynamic gun-launch input load is analyzed using Simulink and the stresses are determined using the finite element analysis (FEA) software, Abaqus. Stress magnitudes on the proof mass at critical attachment locations from both the axial and radial load conditions are well below the yield strength of polysilicon, confirming survivability at tactical 155mm gun-launch. System dynamic modeling in Simulink shows the response of the in-plane (circular, x-y axis) and out-of-plane (cantilever beam, z-axis) proof masses due to the g-loads are within design limits, avoiding sensor breakage and the need for shock stops. Additional Simulink modeling with a voltage input provides insight into electromechanical response. The planar chip three-axis accelerometer design and analysis in this paper meets the requirements for use in military applications, where small size, weight, and power are critical parameters for volume constrained precision guided munitions.
Structural Analysis of Additively Manufactured Polymeric Auxetic Metamaterials
Authors: Raihan Gazi Abu , Chakravarty Uttam K.
Published: February 2024

The auxetic metamaterial is designed based on the geometric configuration rather than intrinsic material properties to tailor their superior behaviors which are not readily available on the naturally available material. Due to their counterintuitive response under static and dynamic loads, the potential applications of the polymeric auxetic structures are expanding in many engineering areas such as biomedical engineering, micro-electromechanical systems (MEMS), marine engineering, and aerospace engineering. In this paper, the structural properties of different auxetic structures are measured using finite element analysis (FEA). Static structural models have been used to calculate the Poisson’s ratio, and maximum stress and strain under different static load conditions. Modal analysis is conducted to measure the response of the auxetic structures under dynamic loading where mode shapes and the fundamental natural frequencies of the structure are measured. The Poisson’s ratio is found to have highest in the triangular auxetic structure compared to the other auxetic structures. The mode shapes correspond to the response of the auxetic structures under different fundamental frequencies and respond to the structures under free vibration in different directions.
Wall-Modeled Large Eddy Simulation of Flow Past an Ahmed Body With a 25° Slant Angle
Authors: Mayoral Salvador , Massis Anthony
Published: February 2024

External flows past automotive bodies exhibit separation bubbles and trailing longitudinal vortices. This paper assesses the ability of wall-modeled large eddy simulation (WMLES) to accurately predict the main flow features of automotive aerodynamic flows by investigating the flow past an Ahmed body with a 25° slant angle and a Reynolds number of 2.78 × 106. The wall-shear stress is modeled with the algebraic power-law model by Werner and Wengle (Turbulent Shear Flows, vol 8, pp 155–168, 1993). Simulations are performed with the open source finite volume code OpenFOAM using the PISO algorithm. Wall modeling is implemented in OpenFOAM using a third-party WMLES library, libWallModelledLES. Four wall-normal grid spacings are investigated, while the wall-model sampling height remains fixed. Results demonstrate that WMLES captures the general wake behavior by predicting the pair of counter-rotating separation bubbles behind the Ahmed body and WMLES accurately predicts the formation of the longitudinal counter-rotating vortex pair that is shed from the starting edge of the slanted face.
Creating Stronger Interfaces in Additively Manufactured Multimaterial Polymer Composites Under Shear Loading
Authors: Altuntaş Umut , Coker Demirkan , Yavas Denizhan
Published: February 2024

This study proposes a bio-inspired approach to enhance the shear strength of interfaces in multi-material composites that are created using additive manufacturing. The Fused Filament fabrication (FFF) technique is used to control the interface morphology and to establish a seamless connection between the hard (Polylactic Acid - PLA) and soft (Thermoplastic Polyurethane - TPU) materials via suture morphology. The study investigates the relationship between the protrusion length of the sutural structures and the overlap distance (i.e., FFF parameter) by conducting microscopic examinations. The interlaminar shear strength of the multi-material composites is tested using the short beam shear test, and the Digital Image Correlation (DIC) technique is used to monitor the interlaminar damage nucleation and evolution. The results demonstrate that the flexural stiffness of the soft-hard polymer composites is significantly affected by the interfacial morphology, with longer protrusion lengths leading to increased stiffness. Stiffness of the structure increased three times by proposed method. Furthermore, the interlaminar shear strength is found to increase with protrusion length, while the onset of non-linear deformation is postponed. Stress values which non linear deformation stats and stress values which crack initiates enhanced by five-six times with increased protrusion length. The main finding of this study is that longer protrusion lengths promote more effective and uniform stress distribution at the interfaces, resulting in a transition from heterogeneous to homogeneous material behavior.
Optical and Thermal Modeling of a Heat Pipe Evacuated Tube Solar Collector With Primary CPC-Involuted Reflector
Authors: Lim Celine S. L. , Sobhansarbandi Sarvenaz
Published: February 2024

Solar energy unquestionably plays a vital role for the future of clean energy production due to its availability all year round. Some prominent solar energy technologies, e.g. concentrating solar power (CSP), have the ability to focus/concentrate sunlight for large-scale commercial use. Meanwhile for smaller-scale residential use, solar water heating (SWH) systems are often installed to provide hot water for household applications, where the solar collectors are the main components of such systems. The type of solar collector of interest in this study is the heat pipe evacuated tube collector (HPETC). To enhance the system’s performance and functionality, this study investigates the incorporation of a primary compound parabolic concentrator (CPC)-involute reflector to a single HPETC. The heat flux analysis has been done through optical ray tracing methods from SolTrace and ANSYS Fluent. The heat flux intensity around the absorber tube was compared for different times of the day. Results from this section of the study shows that the use of a primary CPC-involute reflector increases the overall heat flux received by the absorber tube as well as yielding to uniform heat flux distribution. A transient CFD model was also developed by combining both SolTrace data with ANSYS Fluent, where the fin temperature of the system can be predicted. The CFD model developed was validated with experimental data, with a maximum deviation of 7.2%. The validated CFD model can be used for further optimization study of a HPETC with CPC-involute reflector.