bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of Liner Deformation Behaviour in Transtibial Prosthesis
Authors: Regalla Srinivasa Prakash , Prashant Kirange Piyush , Dhake Harshal Vinayak , Shrivastava Prakash Narayan 
Published: January 2022

Abstract
The problems associated with the prostheses for transtibial amputees are related mainly to fit and comfort. There has been a steady effort to improve the below-knee prosthesis’s wearability, stability, and durability. The liner in the below-knee prosthesis plays a crucial role in ensuring these quality characteristics. Isotropic liner material either acts hard and results in discomfort or deforms too much and results in eventual loosening of the prosthetic socket. The material hyper-elastic behavior and thickness are both critical in the design of the liner with optimum comfort. A generalized deformation model considers the interaction of the socket, liner, muscle, and tissue becomes cumbersome. In the literature, numerous hyper-elastic models have been applied. However, studies on the suitability and application of hyper-elastic materials for liner material have not been sufficiently carried out. In this paper, the usefulness of liner materials in terms of their ability to allow sufficient elastic deformation in the normal direction for the cushioning effect while undergoing limited shear deformation has been investigated. The hyper-elastic liner and rigid socket pair have been idealized as adhesively bonded flat layers of suitable thicknesses subjected to various normal and shear load combinations. The deformations for a normal load and varied range of shear loads have been compared to conclude on the best-suited material model. The low shear deformation observed for all three liner materials implies that the shear loading will not affect the adhesive bond between the liner and socket and hence will not cause loosening with prolonged usage of the prosthetics. The deformation observed was maximum with Ogden 3-parameter hyper-elastic model, whereas it was least in the case when Mooney Rivlin 3-parameter hyper-elastic model. The results obtained for the Mooney-Rivlin 3-parameter model and Neo-Hookean model are very close to each other.
Using a Modified Frequency Domain Method Coupled to a Physics Based Model With Non-Uniform Heat Generation to Evaluate the Entropy of Reaction in a Li[NixCoyMnz]O2/Graphite Lithium Ion Battery
Authors: Hammond Jonathan , McCreary Chase , Abbasalinejad Armin , Kim Sun Ung 
Published: January 2022

Abstract
The entropy of reaction is necessary to estimate how much heat could be generated by a battery. Calculating heat generation is critical both for safety reasons and to improve the longevity and performance of the cell. Traditional methods of measuring the entropy of reaction are painstakingly slow and require environmental control machinery. Previously we modified a frequency domain method using a physics-based model and demonstrated that the entropy could be measured at a significantly faster pace. In this paper, we measured the entropy of reaction of a customized pouch cell with two different methods: the modified frequency domain method and the traditional method. Results from the new method were compared against measurements taken on coin cells of the same chemistry using a traditional method. The model validation shows a high degree of accuracy, roughly 50 μV/K, using the new method.
Predicting Steam-Gasification Output Using Artificial Neural Networks
Authors: Shi Yunye , Yepes Maya Diego , Ratner Albert 
Published: January 2022

Abstract
Steam gasification has been identified to be one of the most important technologies to produce syngas for biofuel synthesis, due to the high H2 concentration it can reach, which is significantly higher compared with conventional air gasification processes. Double-stage downdraft gasification has proven to be efficient with a secondary steam injection. Various kinds of models, including computational fluid dynamics (CFD), thermo-equilibrium, kinetic rate, and artificial neural network (ANN) have been developed for studying these processes.
Equilibrium models assume of chemical reaction equilibrium, in which the transfer phenomenon and the reaction kinetics of primary reactions are considered. In CFD models, the mass, momentum, and energy equations are solved simultaneously along the consideration of the gasifier design to predict parameters such as temperature or species concentrations. To overcome the limitations posed by these models, artificial intelligence tools such as ANNs are reliable for the prediction of nonlinear system data. The application of ANN in gasification processes have been reported by several researchers. ANN based models have been developed for predicting syngas yields and gas composition in air gasification systems. However, to the author’s knowledge, no study has focused in the prediction, using ANN, of a double-stage steam gasification system.
In the current study, the effect of different temperatures along the gasification process (T0-T7), equivalence ratio, and steam-to-air ratio were studied in an artificial neural network model to predict the gas composition (CO, CH4, and H2) and the lower heating value (LHV) of the syngas. Miscanthus grass is selected as the fuel. The ultimate analysis of the fuel is excluded in the input because the insignificant impact on syngas composition especially H2 production. Feed forward back propagation (FFBP) neural networks were employed for the training of the networks. Then the model with optimal parameters were selected to test against experimental data for validation purposes. Further, the unused data are tested for model accuracy. It was observed that the developed models are able to predict the CO, CH4, H2, and LHV with good accuracy when comparing with experimental data. The FFBP showed excellent performance. A higher coefficient of determination (R2) and lower mean square error (MSE) is achieved by FFBP. The results obtained indicate that ANNs are powerful tools to facilitate system design, operation and control of double-stage downdraft gasifiers with various operating conditions. Utilizing ANN models, one can predict reasonable output parameters without unnecessary failure.
Power Estimation of an Experimental Ocean Current Turbine Based on the Conformal Mapping and Blade Element Momentum Theory
Authors: Sadeqi S. , Xiros N. , Aktosun E. , VanZwieten J. , Sultan C. , Ioup J. , Rouhi S. 
Published: January 2022

Abstract
Conformal mapping techniques have been used in many applications in the two-dimensional environments of engineering and physics, especially in the two-dimensional incompressible flow field that was introduced by Prandtl and Tietjens. These methods show reasonable results in the case of comprehensive analysis of the local coefficients of complex airfoils. The mathematical form of conformal mapping always locally preserves angles of the complex functions but it may change the length of the complex model. This research is based on the design of turbine blades as hydrofoils divided into different individual hydrofoils with decreasing thickness from root to tip. The geometric shapes of these hydrofoils come from the original FX77W121 airfoil shape and from interpolating between the FX77W121, FX77W153, and FX77W258 airfoil shapes. The last three digits of this airfoil family approximate the thickness ratio times 1000 (FX77153 =&gt; 15.3 % thickness ratio). Of the different airfoil shapes specified for the optimal rotor, there are 23 unique shapes.[15, 16, 17, 18, 19, 20, 21, 22, 24, 25, 28] This study describes the advantage of using at least one complex variable technique of transformation conformal mapping in two dimensions.
Conformal mapping techniques are used to form a database for sectional lift and drag coefficients based on turbine blade design to be used in Blade Element Momentum (BEM) theory to predict the performance of a three bladed single rotor horizontal axis ocean current turbine (1.6-meter diameter) by considering the characteristics of the sea-water. In addition, by considering the fact that in the real ocean, the underwater ocean current turbines encounter different velocities, the maximum brake power will be investigated for different incoming current velocities. The conformal mapping technique is used to calculate the local lift coefficients of different hydrofoils with respect to different angles of attack: −180 ≤ AOA ≤ +180. These results will be compared to those from other methods obtained recently by our research group. This method considers the potential flow analysis module that follows a higher-order panel method based on the geometric properties of each hydrofoil cross section. The velocity and pressure fields are obtained directly by the applications of Bernoulli’s principle, then the lift coefficients are calculated from the results of the integration of the pressure field along the hydrofoil surface for any angle of attack. Ultimately, the results of this research will be used for further investigation of the design and construction of a small-scale experimental ocean current turbine to be tested in the towing tank at the University of New Orleans.
Transient Two-Phase Flow Pressure Drop During Droplet Emergence and Growth in Gas Flow Channels
Authors: Mortazavi Mehdi , Watkins Cade , Murchie Colin 
Published: January 2022

Abstract
The water produced during the operation of proton exchange membrane fuel cells can pass the electrode and emerge from the surface of the gas diffusion layer (GDL), forming liquid-gas two-phase flow in the channel. It is of great importance to be able to precisely quantify the water content in the channel. One method to do so is to measure the pressure drop in the channel and correlate the two-phase flow pressure drop to the accumulated water in the channel. The topic of two-phase flow pressure drop in PEM fuel cell flow channels is investigated in the literature. However, the main focus has been put on the pressure drop in the steady operating condition of the cell. The current study evaluates variation of the pressure drop in the channel while a droplet is emerged from the surface of the GDL. This corresponds to the early operation of the cell. The pressure drop data during droplet growth was acquired in a transparent ex-situ test section while images of droplets were taken in real time with a highspeed camera. The combination of pressure drop data and the size of the droplet obtained from images were used to obtain the drag force applied on the growing droplet. Experimental results showed that the droplet detachment height decreased from 1.54 mm to 1.14 when the superficial gas velocity increased from 4.17 m/s to 10.76 m/s. This decrease in the droplet detachment size reduced the drag force needed to detach the droplet by overcoming the pinning forces. For the same increase in the superficial gas velocity, the drag force decreased for around 50%. Moreover, evaluation of droplet profiles at 10.76 m/s superficial gas velocity indicated that contact line expanded in the downstream of the droplet and the advancing contact angle increased for around 40° from droplet emergence to its detachment.
Mechanical Design and Development of a Suborbital Payload for Real-Time Data Acquisition and Structural Health Monitoring
Authors: Cvetic-Thomas Dillon , Tattershall Amy , Jackson Eli , Robergs Dane , Nwokocha Funmilola , Zagrai Andrei 
Published: January 2022

Abstract
Real-time data acquisition and structural health monitoring (SHM) are in any aerospace black box. To facilitate the development of such technologies, test payload architectures must be designed to safely deliver experimental components to the environments they are expected to perform in. The purpose of this project was to design, analyze, assemble, and launch a payload enclosure system as part of a collaborative experiment involving SHM by New Mexico Tech and distributed data acquisition by Immortal Data Inc. Particular attention was given to the integration of the hardware pertaining to the SHM experiment. This experiment monitors the condition of a cantilever beam throughout the flight using an electro-mechanical impedance method. The enclosure mount was designed to tolerate the vibrational, thermal, and g-loads experience in suborbital flight. With these criteria in mind, ULTEM 1010, an industrial strength 3D printing material, was chosen due to its significant yield strength and low density when compared to other 3D printing material and aluminum candidates. To determine whether or not the tolerances and requirements are sufficiently met, finite element analysis of the payload structure was performed in COMSOL Multiphysics and Solidworks. Stresses due to acceleration loads, de-spinning events, and ground impact were evaluated and safety factors were determined. To enable the electro-mechanical impedance diagnostics, a thin piezoelectric wafer sensor was bonded to the beam and connected to a miniaturized impedance analyzer. This system allowed for local storage of the electro-mechanical impedance data. Validation of this experimental setup was performed in laboratory conditions in which the impedance of the beam was measured in several frequency bands. Based on dynamic characteristics of the beam, low frequency bandwidth was selected for impedance analysis. Numerical studies confirm the enclosure design’s validity and the possibility of electro-mechanical impedance diagnostics of the payload.
Design of a Robotic Vehicle for ASME Student Design Competition 2021
Authors: Kochanczyk Wojciech , Chauhan Vedang 
Published: January 2022

Abstract
Robotics is a very active and diverse field with new applications found daily for emerging designs. This year ASME SDC emphasizes one such application with small RC robotic vehicles. These vehicles are primarily cargo carriers with the ability to harness wind and solar renewable energy sources to recharge their limited battery. Analog to modern electric battery-powered cars the robot utilizes a single AAA battery which was the biggest challenge of the competition. To satisfy all the requirements posed by the competition, a brand new vehicle platform was developed including both wind and solar charging capabilities. As part of the development process a new drive train, control system, wind turbine, and robot frame was developed. For performance maximization, all outsourced, as well as custom-designed components, were extensively researched and tested. Using test data and CAD software the final design was created including all the components selected during testing. This produced a successful prototype satisfying all competition requirements and being accepted to take part in SDC 2021. The maximum score achieved by the robot reached 0.4488 points using the given scoring matrix, however, it did not qualify for the final rounds of the competition. This project indicated several ideas that may improve the performance of small robots, such as the effective use of solar panels, the creation of systems with low power requirements, as well as the use of RC toys to develop more complex robotic vehicles.
Performance of Iterative Network Uncertainty Quantification for Multicomponent System Qualification
Authors: Rojas Edward , Tencer John 
Published: January 2022

Abstract
In order to impact design decisions and realize the full promise of high-fidelity computational tools, simulation results must be integrated at the earliest stages in the design process. This is particularly challenging when dealing with uncertainty and optimizing for system-level performance metrics as full-system models (often notoriously expensive and time-consuming to develop) are generally required to propagate uncertainties to system-level quantities of interest. Methods for propagating parameter and boundary condition uncertainty in networks of interconnected components hold promise for enabling design under uncertainty in real-world applications. These methods preclude the need for time consuming mesh generation of full-system geometries when changes are made to components or subassemblies. Additionally, they explicitly tie full-system model predictions to component/subassembly validation data which is valuable for qualification. This is accomplished by taking advantage of the fact that many engineered systems are inherently modular, being comprised of a hierarchy of components and subassemblies which are individually modified or replaced to define new system designs. We leverage this hierarchical structure to enable rapid model development and the incorporation of uncertainty quantification and rigorous sensitivity analysis earlier in the design process.
The resulting formulation of the uncertainty propagation problem is iterative. We express the system model as a network of interconnected component models which exchange stochastic solution information at component boundaries. We utilize Jacobi iteration with Anderson acceleration to converge stochastic representations of system level quantities of interest through successive evaluations of component or subassembly forward problems. We publish our open-source tools for uncertainty propagation in networks remarking that these tools are extensible and can be used with any simulation tool (including arbitrary surrogate modeling tools) through the construction of a simple Python interface class. Additional interface classes for a variety of simulation tools are currently under active development.
The performance of the uncertainty quantification method is determined by the number of iterations needed to achieve a desired level of accuracy. Performance of these networks for simple canonical systems from both a heat transfer and solid mechanics perspective are investigated; the models are examined with thermal and mechanical Dirichlet and Neumann type boundary conditions separately imposed and the impact of varying governing equations and boundary condition type on the performance of the networks is analyzed. The form of the boundary conditions is observed to have a large impact on the convergence rate with Neumann-type boundary conditions corresponding to significant performance degradation compared to the Dirichlet boundary conditions. Nonmonotonicity is observed in the solution convergence in some cases.
Modelling Economic Life Cycle Investment in Natural Gas Pipelines and Power Plants Availability for a Nigerian National Gas Company
Authors: Abhulimen Kingsley E. 
Published: January 2022

Abstract
This paper presents an economic life cycle assessments based on the linear process model to justify investment opportunities in a National State Gas Pipelines and Power Plants Projects. The model predicts investments demand vectors of technology, human capital resource utilization, raw materials availability and environment impact categories. Thus the carbon foot print and acidification for each stage of the life cycle investment in the process design stages of economic capital resource decision matrix to the environment impact intervention matrix were simulated in a MATLAB and Excel spreadsheet environment. Therefore the economic capital utilization and environmental sustainability of the demands vectors of each stage were evaluated, categorized, ranked and correlated within targets retrospectively for investment in each stage of National Gas Company projects. The acidification (Nox, and Sox) pollution averaged 30.48ppm below the acceptable thresholds of 67.97ppm and the carbon foot prints were almost near negligible for all stages which signals an important landmark decision criteria for investments in the projects. The net impact value to shift in economic matrix demand vector sensitivity analysis using the statistical random simulations shows a correlation within 7% range deviation and the environmental impact categories were below the 25% threshold values.
Influence of Film Cooling Holes Partial Blockage on Cooling Effectiveness
Authors: Zhang Junhong , Dong Wenxin , Lin Jiewei , Dai Huwei , Wang Xibo 
Published: January 2022

Abstract
To study the effect of blockage on the film cooling performance, film cooling plate models with cylindrical hole, compound hole, and fan-shaped hole under the all-round blockage, leading-edge blockage, and trailing-edge blockage were established respectively. The anti-blockage performance of three kinds of the hole was compared. The result shows that the cooling performance of cylindrical holes is the worst due to the appearance of counter-rotating vortex pair (CRVP) under blockage. The cooling effectiveness decreases with the increase of the blockage ratio. With the re-attachment effect, the cooling effectiveness of downstream increases by 11% on the contrary. The cooling effectiveness of the compound hole decreases obviously with the all-round and trailing-edge blockages, meanwhile, the peak cooling effectiveness and the coolant coverage area decrease. However, the cooling effectiveness increases by 15% when the leading-edge is blocked. For fan-shaped hole, the change of velocity gradient affects the development of the anti-CRVP, which disappears under the all-round blockage and reduces the cooling effectiveness greatly. The change of cooling performance of leading-edge and trailing-edge is very slight no more than 5%. In conclusion, the fan-shaped hole shows the best anti-blockage capability under the trailing-edge blockage condition and the all-round blockage condition with a high blow ratio, while the compound hole performs better in other conditions.