bluuebunny/crossref_metadata_2025_split huggingface dataset:
ICE Performance Optimization With Double Supercharging With E-Booster
Authors: Capata Roberto , Calabria Alfonso , Donato Federico , Martellucci Leone 
Published: February 2024

Abstract
When it comes to the European Green Deal and Carbon Neutrality, we cannot ignore a fundamental element: the transport sector in the EU alone is responsible for 27% of greenhouse gas emissions and, between 1990 and today, aviation and maritime navigation have increased emissions by 50%. But the real lion’s share has been played by road transport, which alone contributes to 71.7% of emissions in transport, while railways have an extremely small impact, equal to about 1%. The present work aims to improve the performance of a commercial ICE through a double supercharging with eBooster to improve performance and reduce consumption, trying to reduce consumption, emissions, improve the overall efficiency of the vehicle and to make road transport sustainable. Thanks to this system it is possible to have a larger turbocharger that guarantees a greater power at high engine rotational speed without losing the torque at low rpm that will be guaranteed by the electric compressor. The operational conditions and parameters have been studied through a one-dimensional analysis via software. Through this simulation, different configurations were tested in order to obtain, in a preliminary way, the solution that maximizes the performance of the engine, thus saving in terms of costs and time on experimental tests. All simulations are carried out at full load with the same stoichiometric ratio of the mixture and ignition time, within a speed range between 2500 and 8500 rpm. Initially, a model with turbocharger available on the market has been studied, simulated and proposed, operating with good efficiency at a higher engine rotational speed. The choice to use a commercial compressor has been dictated by the possibility of replicating the operational maps of the device and using them in the simulations. Once this phase was optimized, it has proceeded to study which electrical device to introduce. After the addition of the electric compressor, an optimization of the system has been conducted. This simulation allows to compare different dimensions of the connection (piping, manifolds, valves, etc.) trying to exploit the pressure waves that are inside generated to improve the filling of the engine. Finally, through the analysis of the pressures inside the intake and exhaust ducts and the cylinder internal pressure, an ideal timing for this system has been set. Through the carried-out simulations, it was possible to underline that the larger turbocharger increases the engine efficiency, both from the point of view of power and fuel consumption, and thanks to the electric compressor it is possible to have a favorable torque curve at low rotational speed.
Power Take-Off Design Study for a Small-Scale Oscillating Surge Wave Energy Converter for Powering the Blue Economy Applications
Authors: Wills Jackson , Tom Nathan , Sirnivas Senu 
Published: February 2024

Abstract
The power take-off (PTO) is an integral part of wave energy conversion, and the design process is nontrivial. Better PTOs, and better processes for selecting and designing PTO architectures for various applications, would benefit devices that assist in powering the blue economy by decreasing time and money spent on PTO design and increasing the overall energy capture performance of these devices. This paper chronicles the selection process of a PTO for a small-scale surge-type wave energy converter (WEC) for the purpose of informing future PTO selection processes. Three PTO architectures are evaluated in WEC-Sim: a hydraulic check valve PTO, a hydraulic active valving PTO, and a directly electrified PTO. Simple models of each PTO are constructed. Because a model for the small-scale device was initially unavailable, the PTOs are simulated on a large-scale device. The results are scaled down using Froude scaling and compared to results from directly simulating a small-scale model. Strong assumptions are made because this work is early in the design stages, and a coarse look at PTO options was desired. Specifically, the effectiveness of controls is investigated, along with the efficiency of energy conversion. However, energy capture is only part of the consideration; there are also logistic concerns to be considered when selecting a PTO. For example, components for large-scale WECs are so large and expensive that it may make sense to custom-build PTO components, but small-scale WECs would benefit from off-the-shelf availability because the cost of customization would be a significant portion of the total capital cost of deployment at a small scale. Submersible, off-the-shelf components are much easier to source for hydraulic PTOs. Because of highly effective controls, efficient energy conversion, and availability of marine-grade components, an active valving hydraulic PTO is selected for this small-scale surge-type WEC.
Damage-Induced Softening of the Sclera: A Pseudo-Elastic Modeling Approach
Authors: Colmenarez Jose A. , Zhai Yingnan , Mendoza Valentina O. , Dong Pengfei , Nunes Kenia , Suh Donny , Gu Linxia 
Published: February 2024

Abstract
The biomechanical properties of the sclera such as the stiffness, anisotropic behavior, and non-linear stress-strain relationship have been extensively investigated for the pathogenesis study of ocular diseases. Even so, scarce mechanical investigations have been conducted on the damage in the sclera when subjected to large and repetitive deformations. Hence, the aim of this study is to quantify the extent of microstructural damage of the posterior and anterior sclera under loadings beyond the physiological range, through mechanical testing and model fitting. We performed uniaxial mechanical tests on scleral strips dissected from African green monkeys. Samples were subjected to strain-driven cycles of 5%, 10%, 15%, and 20% to evaluate the damage behavior commonly known as the Mullins effect. Experimental results showed qualitative changes in the stress-stretch curves when higher loading cycles were applied. A pseudo-elastic model accurately captured the curve trends across all tested samples, as indicated by a determination coefficient above 0.96 and a subsequent finite element analysis (FEA) validation. Damage evolution and resultant permanent set demonstrated that considerable microstructural failure was attainable at small strain levels, and that the inherent plasticity had a similar contribution to stress-softening as the Mullins effect. Computed material and damage properties are expected to provide a broader understanding of the underlying mechanisms of ocular diseases and the development of more effective approaches for their treatment.
Piezoelectric Blood Pressure Sensor for Implantable Devices
Authors: Katey Bright , Voiculescu Ioana , Li Fang , Untaroiu Alexandrina 
Published: February 2024

Abstract
The paper presents the model and simulation of a piezoelectric pressure sensor intended to be used for a ventricular assist device for children and adults affected by the Single Functional Ventricle Congenital Heart Defect (CHD). This syndrome is the condition of the heart, where one of the ventricles, typically the right one, is either underdeveloped or not developed at the time of birth. To address this problem, we propose a mechanical cavo-pulmonary assist device with a dual-propeller pump, which is self-expanding. This is implanted into the total cavopulmonary junction (TCPC). The propellers’ scope is to regulate the blood flow directed to the lungs. The pressure sensor is an integral component of this sophisticated biotechnology device. It will be used to control the blood pressure by sending a signal to the motor and propeller pump to adjust its operating condition when the blood pressure is below the physiological levels. The pressure sensor is designed from a piezoelectric material which gives it a self-powering functionality.
To enhance the sensitivity of the pressure sensor, arrays of micro-pillars will be fabricated on piezoelectric materials. Finite element analysis (FEA) with Ansys was used to model the pressure sensor, without and with micro-pillars and we demonstrated that the micro-pillars have the capability to increase the pressure sensor sensitivity.
Using Local Concentration to Model the Progress of Acoustophoretic Assembly of Microspheres in Planar Standing Waves
Authors: Wang Y. Jenny , Anthony Brian W. 
Published: February 2024

Abstract
Acoustophoretic assembly uses a standing acoustic field to move dispersed small particles into a geometric pattern. The technique relies on the acoustic radiation force, which arises from the interaction between the acoustic field and the particles, and drives the particles towards areas of low acoustophoretic potential. Acoustophoretic assembly shows potential for a wide range of applications, including organizing filler materials in composites, creating metamaterials, and fabricating functional biological tissue. However, the method has not yet been incorporated into large-scale manufacturing processes. One barrier is the incomplete understanding of the assembly process. While an ideal final pattern geometry can be calculated from the acoustic field and the material properties, there are currently no widespread metrics for measuring the progress of the pattern formation. As a result, it is difficult to know how long the acoustic field should be applied during manufacturing.
Our approach uses the local particle concentration to model the acoustophoretic assembly process. When the acoustic field is applied, the acoustophoretic patterns coalesce as a whole from the initial state of randomly dispersed particles. Over time, the pattern becomes more distinct as the particles become more tightly grouped together. Thus, the process of acoustophoretic assembly can be considered a change in the local concentration of particles.
We show that an expression for the time-dependent local particle concentration can be derived from the force balance on the particles and a control volume analysis. The analysis is applied to microspheres in a planar acoustic standing wave, and an analytical expression is obtained. To validate the theoretical results, experiments were carried out using polystyrene microspheres in a glycerol-water mixture.
As expected, the particle concentration increases over time at regions with the lowest acoustophoretic potential, while the concentration decreases at regions with the highest acoustophoretic potential. We use the local concentration to define measurements for the quality of the assembled microsphere pattern. When the acoustic field is initially applied, the quality of the pattern changes quickly. At longer times, the quality of the pattern plateaus, and there is a diminishing return to pattern quality with each additional unit of time. This suggests that a cut-off time for pattern assembly can be implemented based on the acoustic and material properties.
Online Development Plan for an Applied Thermodynamics Course
Authors: Fadda Dani , Vinay Roopa , Rios Oziel 
Published: February 2024

Abstract
Online course development in higher education requires careful planning by faculty and instructional designers so materials are offered in a pre-meditated and thought-out way. An applied thermodynamics class is developed for online offering in the Fall semester of 2023 using the backward design method. This method allows faculty to create a development plan for their course before creating online content. The purpose of this paper is to illustrate that developing classes for online delivery requires careful attention to best practices that can capture the student’s attention and enhance their learning experience. The outcome of this work is a structured design experience, which is preferred and completely different from the rush to online teaching, which occurred during the COVID-19 pandemic.
Measurements of Natural Ventilation Within a Model Sports Stadium Using Magnetic Resonance Imaging and Planar Laser Induced Fluorescence
Authors: Ellwein Bryn , Gehl Jack , Iliff Scott , Ederle Pierce , Benson Michael , Banko Andrew 
Published: February 2024

Abstract
The natural ventilation dynamics of a model sports stadium are investigated experimentally. Specifically, a laboratory scale idealized sports stadium model is considered with generic ventilation features such as an asymmetric roof opening, roof slits, and entrance and egress tunnels. Time-resolved 2D concentration measurements external to the stadium are conducted using planar laser induced fluorescence (PLIF). Time-averaged 3D measurements of the flow velocity field internal and external to the stadium are performed using magnetic resonance imaging techniques. Both experimental techniques utilize the same water channel facility operated at fully turbulent Reynolds numbers based on the stadium height. A passive scalar contaminant is injected in the vicinity of the stadium to understand how contaminant infiltrates and exfiltrates the structure. The freestream wind angle is varied to quantify how alignment of various geometric features with the prevailing wind direction alters the internal flow structure within the stadium and couples to the contaminant transport. Results show that both the time-averaged and time-resolved concentration fields exhibit important sensitivity to the wind direction. The conclusions suggest that the novel combination of laser-based and medical imaging techniques provides a unique means to understand complex natural ventilation patterns with application to urban air quality and emergency response.
Singularity Based Method for Small Perturbation Unsteady Aerodynamics Using Higher Fidelity Steady State Pressure Profiles
Authors: Bottai Auriane , Jonson Michael L. , Campbell Robert L. 
Published: February 2024

Abstract
A low-cost, singularity-based method that builds upon the classic potential flow solution procedures is presented in this paper. The classic potential flow solution method distributes elementary solutions to the Laplace’s equation such as sources, vortices or doublets, on the aerodynamic surface. The strengths of those singularities are calculated to satisfy the non-penetration boundary condition and the flow smoothness at the trailing edge. The potential flow predictions are improved to include some compressibility and viscous effects by superposing additional singularities, which strengths are computed to match pressure profiles obtained from a higher resolution conmputational fluid dynamics (CFD) solver. Four variants of the procedure are presented and discussed. Classic potential solution methods can be based on the camber-line (e.g. Lumped Vortex Method in 2D for airfoil) or on the actual airfoil (respectively wing) surface (e.g. source-double panel method). Likewise, the four variants differ by the types of singularities used and/or the aerodynamic surface where the boundary condition is applied: Method 1 optimizes the camber-line shape so that when distributing discrete vortices along that curve, the correct pressure jump across it is obtained. Method 2 duplicates and offsets the geometric camber-line into an “upper” and a “lower” camber curves. Singularities are then distributed on those curves to match the pressure distribution across the airfoil upper and lower surfaces. Method 3 overloads the airfoil surface panels with multiple singularities to meet the pressure requirements. Finally, Method 4 combines continous and discrete singularities to achieve that goal. The methods are surveyed upon three airfoils: NACA006 (thin, symmetric airfoil), NACA4412 (thin, cambered airfoil) and a two-element airfoil, S207. The methods are compared in terms of accuracy in predicting pressure coefficient, aerodynamic loads and applicability for future unsteady simulations. Based on this steady-state survey, Method 4 is the most accurate and stable, with the appropriate choice of singularities. One key element for small perturbation analysis is to capture accurately the reference position, particularly the mean wake on which the vortices are shed, which method 4 is found to be capable of predicting.
Prediction of Delamination Location in Composite Structures With Different Ply Orientations: A Framework Integrating Finite Element Simulation and Deep Learning
Authors: He Junyan , Zhuang Linqi , Chaurasia Adarsh , Najafi Ali 
Published: February 2024

Abstract
In this paper, a framework integrating guided-wave-based finite element (FE) simulation and deep learning is developed to predict the location of internal delamination within a composite plate with different layup configurations. The data needed for training the prediction model are obtained through guided-wave-based FE simulations. Convolutional neural network (CNN) models are then built and trained to predict the location of the existing delamination. The possibility of using transfer learning is explored to account for composite plates with different layup combinations while minimizing additional data needed for CNN model training. It is found that once a baseline CNN model is trained by the data extracted from a specific composite layup case, transfer learning can significantly reduce the amount of data required to achieve similar levels of prediction accuracy for other scenarios with different layup orientations, thus greatly improving the efficiency and versatility of the proposed framework.
An Experimental Investigation of the Relationship Between Evaporator and Condenser Sizes With Oscillating Heat Pipe Start-Up
Authors: Miesner Spencer , Bautista Neyda , Wolk Kieran , Furst Ben , Daimaru Takuro , Sunada Eric , Roberts Scott , Bellardo John , Kuo Jim 
Published: February 2024

Abstract
Oscillating Heat Pipes (OHPs) are unique two-phase heat transfer devices with many advantages over standard and more widely adopted thermal control devices. Specifically, OHPs are able to operate passively, over a wide temperature range, and under high heat fluxes, with few design constraints. OHPs operate based on the process of evaporating and condensing a working fluid on opposite ends of a series of serpentine channels. The pressure difference causes an oscillating behavior of the fluid to travel along the direction of the channels enabling a high heat transfer rate. The capability of this technology has garnered much attention and interest for a variety of applications in different fields. While as a thermal management device, OHP technology shows much promise, there is still much to be understood about the fundamental principles of its operation. One of the most important aspects of OHP operation that is still not well understood is the phenomena known as “start-up”. Start-up is when the proper conditions of an OHP are created such that the operating, oscillatory process of an OHP is enabled to begin. In this work, experimental testing is performed to investigate the relationship between evaporator and condenser length on OHP start-up. In this study, combinations of small, medium, and large length evaporators and condensers were used on a 42-turn OHP with 1 mm square channels, charged with R134a to 50% fill ratio with the goal to quantify the minimum heat that would initiate start-up. Before this test could be performed, issues in consistency of the start-up of OHP had to be resolved. A method to “reset” the liquid-vapor distribution to overcome any adverse history from previous OHP operation developed is discussed. Then, a zero-heat input method of confirming a liquid-vapor distribution favorable to start-up is outlined. After developing this method to achieve a consistent start-up heat input in the OHP, tests were performed for nine different configurations of large, medium, and small evaporator and condensers, to determine their relationship with the minimum heat required to start-up an OHP. It was observed that both the size of the evaporator and condenser both influence the start-up heat load. That is, a large condenser and evaporator can reduce the heat load required to start-up. Additionally, the size of a condenser is much more influential than the size of the evaporator. The overarching discovery is that the process of start-up relies heavily on the history of the OHP i.e., the initial liquid-vapor distribution of the working fluid in the channels. In measuring start-up, it is important to recognize and address how the current state of the OHP can lead to inconsistent results.
Real Time Tire Wear Detection Using Intelligent Tires
Authors: Gupta Utkarsh , Gorantiwar Anish , Taheri Saied 
Published: February 2024

Abstract
Tires, the only vehicle component in contact with the road, are crucial in determining vehicle dynamics. However, as the tires travel substantially, different wear patterns such as feather, spotty, and camber wear are introduced in different parts of the tire’s tread due to contact with the road surface, improper tire inflation pressure, and tire alignment issues. This tire wear phenomenon affects vehicle performance and is detrimental to vehicle-road safety. This research has developed a framework for tire wear classification based on the “Intelligent Tires” concept. This intelligent tire comprises tri-axis accelerometers mounted on the tire’s inner liner for data corresponding to the tire-road contact interface. A vehicle was instrumented with different proprioceptive and exteroceptive sensors for testing and data collection. Tires with different tread depths have been tested under various test conditions of velocity, tire inflation pressure, road surface, and tire normal load. Multiple signal processing techniques in time, frequency, and spatial domains have been leveraged for feature extraction. These features serve as inputs to machine learning based classification algorithms to distinguish between normal and worn-out tires. Thus, the developed system capitalizes on intelligent tire data to predict the state of the tire as normal or worn-out, with real-time capabilities.
A Causal Approach to Model Validation and Calibration
Authors: Mandelli Diego , Gonzales Ronald , Wang Congjian , Abdo Mohammad , Welker Zachary , Balestra Paolo , Qin Sunming , Petrov Victor 
Published: February 2024

Abstract
All current developed methods for model validation are based on standard statistical analysis (to measure statistical differences between data populations) or machine learning (to identify response surface from data) methods. Both methods have to be purely data driven, that is they provide quantitative comparison measures between data sets (e.g., simulated vs. measured data) without explicitly considering the hypothesis behind them (e.g., boundary conditions) and the structure of the employed models. This can generate the erroneous conclusion that, when two data populations are close enough, the models that have generated them are similar. In addition, when simulated and experimental data differ beyond the acceptance criteria, model calibration techniques are used to tweak simulation model parameters to reduce the gap between simulated and experimental data. This gives the false expectation that a simulation model matches reality. The goal of this paper is to move away from current purely data-driven methods for validation and calibration toward more robust model-driven methods based on causal inference. The presented methods capture the causal relationships between data elements (e.g., simulated and experimental data) rather than looking at their associations, and they employ these relationships to measure differences between simulated and measured data. These causal differences then directly inform the calibration process rather than relying on the analyst educated guess.