bluuebunny/crossref_metadata_2025_split huggingface dataset:
Design and Assembly of a New Methane Generation System for Energy Conversion From Biowaste
Authors: Alhalwachi Ali , Moreno-Flores Omar , Davis Shelbie , Torrey Matthew , Altamimi Khalid , Duan Shawn 
Published: February 2021

Abstract
According to executive order 18-01 and 20-01 signed by the Washington State Governor, all newly constructed public buildings and facilities shall be designed to be net-zero energy capable. To respond to the governor’s order, the Washington State Department of Transportation (WSDOT) has asked for the design of a system that can use biowaste that accumulates at their safety rest stop areas to generate electricity to power the facilities. The goal of this project seeks to assist WSDOT by designing, building, and testing the capability of a small-scale methane energy generator that can be scaled to fit the needs of any rest area. There are a small number of methane generators in existence [1.]. However, they are not designed to satisfy the needs of net-zero energy facilities and safety rest areas. In this work, a net-zero methane generation system is presented to show how it can convert biowaste into methane for electricity at rest areas. The model is composed of two tanks to store the biomaterial, a filtration system to remove hydrogen sulfide (H2S) and carbon dioxide (CO2), a generator that runs on methane gas, and a photovoltaic system that powers temperature sensing devices. Through testing, it was shown that this system could generate energy through the use of bovine waste. Further improvements are needed to increase methane production and make operation more efficient. Future testing on human waste from a safety rest area will also be necessary before proving that the system can meet energy generation requirements.
Modeling Odor Optimization of Vehicles Based on Data-Driven Goal Programming
Authors: Hou Linzao , Zhang Jun , Li Mian , Zheng Ruixiang 
Published: February 2021

Abstract
In recent years, there is an increase in customer requirement on the comfort of vehicles. As a result, reducing the odor inside the vehicles has become an important and elusive task. Extensive experimental results show that the odor inside vehicles mainly comes from VOC (volatile organic compounds) emitted by the interior ornaments and parts. Given there are many VOC components affecting the odor, determining which VOC components are essential to the odor becomes a main difficulty in optimizing the odor in vehicles. In this paper, we proposed a new approach to optimize the odor of VOC in vehicles based on data-driven modeling and goal programming. To this end, we first collected mass spectrograms of vehicle parts and their odor ratings, where the mass spectrograms are obtained by mass spectrometer and ratings are scored by olfactory engineers. Then we used these data to build a data-driven model based on Weber-Fechner Law. The data-driven model is solved using lasso regression. Based on the data-driven model, we found out the contributions of the VOC components to the odor rating, which enables us to focus on certain specific VOC components that contribute much to the odor ratings. By strategically reducing those specific VOC components using goal programming, we finally obtained an optimized design with a better odor rating. To be specific, when performing the optimization, instead of minimizing the VOC odor rating, we set an ideal odor rating as the goal and formulated the optimization as a goal programming problem. To validate our approach, we collected 179 VOC mass spectrograms to train and test our data-driven model. The average accuracy of predicting odor ratings from mass spectrograms can reach 85% ∼ 90%. This data-driven model implies the contributions of VOC components on different mass weights to the odor rating, and the selected high-contribution mass weights can give reasonable optimization scheme to reduce the VOC gas odor.
Development and Evaluation of PVA-H 3D Printed Blood Vessel Biomodels With Several Stiffness
Authors: Kobayashi Naohiro , Shimizu Yasutomo , Nagano Ryota , Tupin Simon , Ito Makoto , Ohta Makoto 
Published: February 2021

Abstract
Biomodels, which are models of tissues such as blood vessels, have recently come into high demand for surgical training or medical device assessment use. Since the stiffness of blood vessels is not uniform, reproducing this nonuniformity would be advantageous to producing more realistic models, and to do this, we used a poly (vinyl alcohol) hydrogel (PVA-H) 3D printer. As a material, recently PVA-H has received increasing attention. This printing technique may be suitable for fabricating models composed of parts exhibiting different levels of stiffness (multipart models).
However, the PVA-H 3D printer uses outer molds as supports. Outer mold removal as a post-process might affect the mechanical properties of the models or other post-processes such as ethanol substitution, and this requires investigation. Quality checks on the mechanical properties of the final product are also necessary.
In this study, the effect of outer molds on the efficiency of ethanol substitution was estimated by measuring specimen weights. Additionally, the effect of the heat generated when molds were removed with an ultrasonic cleaner on the Young’s modulus of models was tested using tensile tests. Moreover, multipart pieces were fabricated, and their mechanical properties were measured.
The findings were that ethanol substitution was able to be completed by conventional methods. Furthermore, the heat generation did not change the Young’s modulus of the models. Also, it was possible to fabricate multipart PVA-H models, and their level of stiffness followed the theoretical equation that assumes constant stiffness and independency of each part. The PVA-H 3D printer, therefore, has the potential to fabricate multipart models that will enable better surgical training and device assessments.
Effect of the Number of Stages on the Performance of Savonius Vertical Axis Wind Turbines: Part II — Using Twisted Blades
Authors: Saad Ahmed S. , Ookawara Shinichi , Elwardany Ahmed , El-Sharkawy Ibrahim I. , Ahmed Mahmoud 
Published: February 2021

Abstract
Wind energy comprises one of several renewable resources of energy engineered to contain the global energy crisis. Although horizontal axis wind turbines (HAWTs) have proven to be effective in low turbulence and steady wind conditions, vertical axis wind turbines (VAWTs) potentially have the advantage in highly variable and turbulent regions. The Savonius vertical axis wind turbine has several advantages such as simple design, low manufacturing costs, low operating wind speed, low noise, and Omni-directional capability. However, the Savonius rotor requires further design optimization to improve its aerodynamic performance before becoming competitive with other turbine designs.
Thus, the main objective of the current study is to numerically investigate the aerodynamic performance of a multistage Savonius rotor to enhance the power coefficient and the ability of self-starting. In the current study, one-, two-, three-, and four-stage Savonius rotors with twisted blades are investigated. In a two-stage rotor, one single-stage rotor is mounted over another single-stage with a phase angle of 90°. In a three-stage rotor, the three single-stage rotors are mounted one above the other with a phase angle of 60° relative to one another while with a phase angle of 45° for the four stage-rotor. The blades of the studied Savonius rotor are twisted with a twist angle (φ) of 45°.
This is the first contribution to understand how multi-stages influence the aerodynamic performance of the twisted-bladed Savonius rotor. Moreover, variations of torque and power coefficients are computed for all the studied rotors with various numbers of stages. The developed numerical model is simulated using ANSYS Fluent and validated using the available experimental and numerical results. Results showed that the coefficients of torque (CT) and power (CP) increase with rising the number of stages. Increasing the number of stages from 1 to 2 significantly increases the CT and CP of the rotor. However, with a further increase in the number of stages to 3 and 4 stages, both the CT and CP remains almost the same as the rotor with 2 stages. The maximum coefficient of torque (CT, max) and power (CP, max) for a two-stage rotor are 0.42 and 0.253, respectively. The gain in the coefficient of power obtained by using the two-stage Savonius rotor with twisted blades is 53.5% compared to the conventional single-stage which has a coefficient of power 0.165 at a wind velocity of 6 m/s. Moreover, using multi-stages and twisted blades significantly smooth the variations in the generated torque and produce positive values at all rotor angles resulted in improving the self-starting ability of the Savonius rotor.
An Experimental Study on the Analysis of Operating Conditions in the PEMFC Flow Channel by Observing Temperature/Humidity Field
Authors: Han Jaesu , Yu Dongjin , Yu Sangseok 
Published: February 2021

Abstract
Proton Exchange Membrane Fuel Cell (PEMFC) has advantages that other energy sources don’t have, and recently, it has been spotlighted in many industries such as transportation and power generation. However, although much research has been conducted on PEMFC, studies on operating conditions of bipolar plates in cells have been insufficient. Most of the studies that have been conducted so far are obtained by setting a few points on the edge or the latter line of the bipolar plate when acquiring data such as the operating temperature or relative humidity of the cell, so the research is extremely limited. In order to maximize the performance of PEMFC and preserve its durability, it is very important to control operating temperature and humidity optimally. Typically, water contents inside membrane electrolyte is determined by externally delivered water vapor and electrically reacted water vapor. Since water vapor is delivered and exhausted through bipolar plate, the vapor concentration in the bipolar plate is a clue to understand operating characteristics of PEMFC. Even though vapor concentration is a key to improve the performance, it is very difficult to measure direct distribution on the membrane electrode assembly. Therefore, this study attempted to observe the behavior of vapor flow inside the bipolar plate. By mounting several sensors in the flow path of the bipolar plate, it is possible to measure the temperature and humidity field data in the flow path, so that it is possible to observe the actual operating environment in the stack under various operating conditions and to establish a control strategy. Especially, this approach not only makes it possible to analyze the static water content in a steady state where no change in load occurs, but also enables dynamic observation of transient characteristics in the flow path when the current density changes. Several temperature and humidity sensors were installed on the bipolar plates of the cathode and anode respectively, and reliability and performance evaluations were performed through experiments. Reliability was evaluated by setting up a relatively accurate comparison sensor among the existing sensors that were not used in this study, and analyzed the effects of flow disturbance in the flow path by comparing with the polarization curve in the general cell. After the sensor calibration, an experiment was performed to obtain temperature and humidity data as the current density changed. As a result, it was possible to quantitatively analyze the water content delivered from the outside or generated inside the stack.
Robustness Optimization of Product Assembly Architecture for Personalization
Authors: Tan Changbai , Freiheit Theodor , Barton Kira , Banu Mihaela , Hu S. Jack 
Published: February 2021

Abstract
Personalization has received extensive attention as a new manufacturing paradigm to address increased market demand for personalized products. An open product architecture that assembling common, customized, and personalized modules is regarded as a key enabler for product personalization, which can deliver one-of-a-kind products for individual customers at near mass production efficiency. Offering the best product architecture should consider the variations in design variables and parameters that influence the performance of a product architecture. This is especially true when designing open architecture for personalized products as many uncertain design quantities need to be considered in early product design stage.
A robustness optimization method is proposed to simultaneously optimize product variety, module variant selection, and configuration of personalized module variants for a personalized assembly architecture. First, a profit model is developed to measure the performance of a product architecture, which incorporates individual customer preferences and manufacturing cost. A three-step process is proposed to model heterogeneous customer preferences: conjoint analysis of the preferences of a sample of customers from target market, market segmentation by a multi-variate normal mixture method, and simulation of personal preferences for a broader market by Monte-Carlo simulation. Thus, the simulated individual customer preferences are used to predict the sales and profit of product offerings. Second, the variation of profit associated with a product family architecture due to the uncertainty in customer preference and manufacturing cost estimates is formulated by a sensitivity analysis. A robustness index is defined by combining the objectives of maximizing profit and minimizing its variation. Lastly, a robustness optimization model is established to optimize product architecture by maximizing its robustness index. The proposed method is demonstrated with a personalized bicycle architecture design example.
A 3D Finite Element Analysis Study of the Jawbones Response to Osseodensification and Conventional Drilling
Authors: Alaqeely Razan , AlDosari Mohammad , Babay Nadir , Abdulbari Al-Hussain , Ba Hadi Ala , Ben Yahia Faycal , Abdulghani Mohannad 
Published: February 2021

Abstract
Osseodensification is used to densify natural bone and increase dental implant stability. This work aims to compare, using finite element analysis, the stress generated on different jawbone areas between conventional drilling (OD) and osseodensification drilling (CD). Cone-beam CT scans of four different edentulous patients were obtained. Implant insertion and removal in the four bone models were simulated for the two different drilling techniques. Materials distribution was set as homogeneous throughout each part. In the OD technique, a new densified region was formed with new material properties based on a relation between density and elasticity. Material distribution of the densified regions was assumed to be a non-homogenous linear pattern and its gradual variation complies with the graph-related slope equations. Von-Mises stress for cortical and trabecular bone was significantly higher in the CD model in comparison to their values in the OD, as densified regions have absorbed most of the stresses and restricted their propagation. The same phenomenon was observed in the implant pull-out bone model. The OD technique was found to affect the primary stability of dental implants positively. The bone types present in different jawbone regions react differently to this technique according to the percentage of trabecular bone to cortical bone.
A Creative Vibration Energy Harvesting System to Support a Self-Powered Internet of Thing (IoT) Network in Smart Bridge Monitoring
Authors: Farhangdoust Saman , Mederos Claudia , Farkiani Behrouz , Mehrabi Armin , Taheri Hossein , Younesian Davood 
Published: February 2021

Abstract
This paper presents a creative energy harvesting system using a bimorph piezoelectric cantilever-beam to power wireless sensors in an IoT network for the Sunshine Skyway Bridge. The bimorph piezoelectric energy harvester (BPEH) comprises a cantilever beam as a substrate sandwiched between two piezoelectric layers to remarkably harness ambient vibrations of an inclined stay cable and convert them into electrical energy when the cable is subjected to a harmonic acceleration. To investigate and design the bridge energy harvesting system, a field measurement was required for collecting cable vibration data. The results of a non-contact laser vibrometer is used to remotely measure the dynamic characteristics of the inclined cables. A finite element study is employed to simulate a 3-D model of the proposed BPEH by COMSOL Multiphasics. The FE modelling results showed that the average power generated by the BPEH excited by a harmonic acceleration of 1 m/s2 at 1 Hz is up to 614 μW which satisfies the minimum electric power required for the sensor node in the proposed IoT network. In this research a LoRaWAN architecture is also developed to utilize the BPEH as a sustainable and sufficient power resource for an IoT platform which uses wireless sensor networks installed on the bridge stay cables to collect and remotely transfer bridge health monitoring data over the bridge in a low-power manner.
Web Based Application for Quick and Handy Health Condition Monitoring System for a Reliable Wind Power Generation
Authors: Kumar Verma Amar , Radhika Sudha , Surampudi Naren 
Published: February 2021

Abstract
Health condition monitoring in wind turbine motor plays an extremely important role, as these devices are highly in demand in the energy sector, especially in renewable energy and are vulnerable to both mechanical and electrical failures, more often. As such, timely identification of internal faults in these electrical devices goes a long way in productive operations by reducing the maintenance time and costs, i.e. such internal faults, if identified at an early stage, repaired or replaced timely will aid in reliable renewable energy supply. Taking this into consideration, automated continuous monitoring of wind turbine machine is a key to making this process more effective. A web application is built in the proposed research enabling quick monitoring of faults in wind turbine motor from a remote access workstation, like a control room. An experimental setup of wind turbine motor is made and data set of stator currents from both healthy and faulty conditions as well as the power spectral density from the motors were used for condition monitoring with a web interface application. Insulation failure in stator winding is a most commonly occurring electrical failure in machines. As such in the current research stator current features from the experimental machine are used for requirement analysis under both healthy and faulty operating conditions. Among the stator insulation failure most commonly occurring stator turn-to-turn faults are taken into consideration in the current research with percentage of insulation failure varying between 25% to 75%. Fault identification is done with the help of wavelet based artificial neural network analysis at the back end and the interface displays the details in the form of dashboards, with the program mainly featuring three dashboards for the unit, stator, rotor, and components in total. Using interactive visualizations, the user will be able to obtain more in-depth knowledge about the suspected faults in the system and its components, and help to take the necessary action. i.e. whether the wind turbine motor needed to be repaired or replaced depending on the vulnerability of the fault. The application also has been experimented with handheld devices by hosting the application on local host and tunneling it over the web. Interactive visualization also includes information about the working conditions of the electrical machine, such as balanced, unbalanced, and failure conditions. Thus internal electrical fault in a wind turbine induction machine can be remotely analyzed, checked and cure can be suggested with a proper online health condition monitoring system.
Thermal Analysis of Large Area Additive Manufacturing Resistance Heating Composites for Out of Oven/Autoclave Applications
Authors: Billah Kazi Md Masum , Hassen Ahmed Arabi , Nasirov Aslan , Haye Gregory , Heineman Jesse , Kunc Vlastimil , Kim Seokpum 
Published: February 2021

Abstract
Additive Manufacturing (AM) of carbon fiber (CF) reinforced composite has received growing attention because of the design flexibility, superior mechanical properties, improved thermal properties, and weight reduction. Autoclave tooling was proven to be a successful application for large scale AM technology. The capital cost, and cost associated with heating, and cycle time in a conventional autoclave process is relatively high. Thus, an innovative design of AM mold with an efficient heating scheme is essential. This study represents an innovative method of the resistive heating of composite molds which does not require a room size oven for heating during the curing processing. Therefore, it has the potential to reduce the operating cost drastically. For the design validation and feasibility study, we performed a numerical analysis of the wire embedded and AM mold parts. The goal of this study is to determine and optimize the thermal behavior of the printed mold with embedded wire technology. It is anticipated that the larger distance between the embedded wires along the printing direction (z-direction) increase the cold spot, on the other hand, a close distance of the wire can create the unwanted localize heating, thus melting. Constant thermal properties of the 20 wt.% short CF reinforced acrylonitrile butadiene styrene (ABS) was used for the simulation purpose. Thermal characterization was set to 100°C to avoid the thermal deformation or bulging on the part surface.
Gravity Compensation Walker: Structure and Safety
Authors: Felmlee Robert , Smith Jordan , Macaulay Michael , Leamer Dakota , Budd Ethan , Steinbrink Scott , Piovesan Davide , Crowe Mary 
Published: February 2021

Abstract
Morbid obesity is a widespread problem in the united states. The rate of falls and injures is much higher for obese individuals when compared to individuals of normative weight. Obesity can also impose excessive load to the hip and knee joints during the sit-to stand transition, which is conducive to osteoarthritis and increased sedentariety.
In order to help individuals with the aforementioned problems, a sit to stand assistive device can be created that compensates for the subject’s lack of propulsive force. This device can reduce the chances of falling while trying to stand and help professionals when aiding these individuals in the healthcare setting. Users can interact with the propulsive loading provided by the device, which can be customizable to their needs. This product is one of the few sit to stand passive, assistive devices allowing the individual to use lower body strength and very minimal upper body strength. The objectives of our device are to be adjustable, help individuals stand without falling forward, be relatively inexpensive, easy to use, and safe for a hospital environment. Structural and stability analysis of the device is here presented, to assess the safety of its use.