bluuebunny/crossref_metadata_2025 huggingface dataset:
GaPA: An Application to Assist Novice Users With 3D Printing
Authors: Scherick James , Touchette Collin , Gulbin Matthew , Coady Parker , Radhakrishnan Pradeep , Brown David C.
Published: January 2022

This research is motivated by the fact that the 3D printing process can be daunting for novices, particularly students in academic institutions. Creating high quality G-Code for prospective 3D parts requires knowledge of a multitude of potentially confusing settings, including printing materials, infill density, and printer resolution. Novices also need to know how to properly orient a 3D part before slicing and may end up printing their part in a way that makes it inferior to an alternative. Currently, many existing slicing tools overwhelm the user with customizable settings, making it difficult for many novice users to navigate those tools. Besides, the vast amount of information available in various publications and online forums requires the user to spend a lot of time trying to process and utilize them effectively. To help users generate G-Code that can ensure a higher quality 3D printed part, we have developed a software application called G-Code and Printing Automation (GaPA) that guides users through the 3D printing and slicing process, using a guided sequential process. The application accepts a user’s CAD model in the form of a STL file and then asks the user about the part’s purpose via a short set of multiple-choice questions. A heuristic ranking algorithm determines each of the part’s possible printing orientations and printer settings, according to the user’s desired purpose for the part and data from literature. GaPA automates the slicing process by integrating part and process knowledge and highlights the pros and cons of the generated orientations. The paper will discuss the development of the algorithm and the software, challenges and planned future work.
Ontology for Product Lifecycle Management in the Oil & Gas Turbomachinery Industry
Authors: Failla Lorenzo , Rossoni Marco , Vallesi Michele , Colombo Giorgio
Published: January 2022

In the industrial contexts of the digital era, data, information and knowledge should seamlessly flow throughout the product lifecycle, and be available at any time and to any agent acting in the value creation stream. PLM is one of the enabler of this scenario, striving to scale the “cobbler” model — where people, information, resources and processes are perfectly integrated — to modern industrial realities operating with multi-disciplinary teams and world-wide dispersed internal and external resources. Yet, despite many industrial realities has invested in the institutionalization of a PLM system, still approx. 60% of time in the value creation process is wasted in searching and waiting for data, data translation, working with wrong data or reinvention of the existing knowledge. After having analyzed the above scenario in the context of a real big industrial reality operating in the turbo-machinery production for Oil & Gas and Engery markets, the present paper aims to propose a solution introducing a working approach based on the modeling of the knowledge domain relevant to a product and its data model by an OWL-DL ontology, and to present the relevant preliminary results. The final target will be the establishment of an ontology-based domain model as the foundation for a digital, human-machine interoperable, product knowledge and data lifecycle management system to bridge the diverse agents operating in the Product Lifecycle Management.
Research on Fatigue Monitoring Method of Carbon Fiber Fully Wound Cylinder With Aluminum Liner Based on Strain Gauge
Authors: Xu Yansheng , Yu Yue
Published: January 2022

Aiming at the fatigue failure of composite pressure vessel, a fatigue monitoring method based on strain gauge for carbon fiber fully wound cylinder with aluminum liner is proposed. The fatigue test was carried out with 20MPa as the maximum pressure until the gas cylinder failed. The temperature signals were collected, in order to eliminate the influence of temperature factors on the test results in the fatigue process of gas cylinders, and the temperature effects were separated by regression analysis, and the real strain changes of carbon fiber wrapped gas cylinders with aluminum inner liner were obtained. Through the analysis of the test results and the verification of other detection methods, it is proved that the strain gauge has a certain feasibility for the fatigue monitoring of carbon fiber fully wound cylinder with aluminum liner.
Sustainable Solution of Thickening the Sludge From Wastewater Treatment by a Rotor With Bars
Authors: Radulescu Victorita
Published: January 2022

In the second stage of the treatment plants there are tanks for the formation of suspensions with a high concentration of solids. This paper presents a rotor solution with vertical bars to produce a rapid concentration of sludge, thus reducing the size of the tanks. The solution is tested in two different areas of activity. The solution reduces the moisture content of the sludge from 94% to 87%. The design was based on the hypothesis that the currents produced by the vortices detached from the bar rotor, accelerate under certain conditions, the thickening of the sludge. It moves in the sides, becoming sediment in a short time. Based on the experimental measurements, a numerical simulation of the rotor was performed to ensure the required vortices. Measurements were made to determine the optimal height and density of the bars. The thickening/settling time was reduced by 14% compared to the conventional systems currently used in wastewater treatment plants in Romania. The experimental tests were performed in the wastewater treatment plant of the Brazi Oil Refinery. The method is also being tested now in the mining industry, at the treatment plant at the Lupeni mine, Jiu Valley.
Effect of Cyclic Corrosion and Joining Method on the Strength of Multimaterial Double Lap Joints
Authors: Gerini Romagnoli Marco , Yang Chao , Nassar Sayed A.
Published: January 2022

The effect of cyclic corrosion on the static performance of multi-material double lap joints is investigated. Carbon-Fiber-Reinforced thermoplastic composite substrates are joined to Aluminum substrates using bonding-only, bolting-only, or by hybrid bonding-and-bolting methods. Polyurethane-based or epoxy-based structural adhesives are used. Surface roughness is maintained constant and evaluated with an optical profilometer. The quasi-static performance of baseline joints is assessed, and the results from the various joining methods are compared. Cyclic corrosion testing of Double Lap joints is performed in accordance with a GMW14872 3-stage laboratory standards for 30 one-full-day cycles. Quasi-static lap shear tests of test samples are performed at various stages of corrosion cycling, and progressive strength degradation is observed for bonded-only and hybrid bonded-and-bolted joints. Bolted-only joints do not show significant performance loss. Results, discussion, and conclusions are provided.
Plastic Deformation Behavior at High Strain Rate by Using High Velocity Micro-Particle Collisions
Authors: Komine Ryoma , Furutani Takumi , Sakai Yugo , Yonezu Akio
Published: January 2022

It is well known that plastic deformation behavior of metallic material depends on the length-scale and time-scale due to dislocation motions in material. The plasticity affected by scale down and higher strain rate is still open to discuss. In other words, both size effect and strain rate effect are critical issue for plasticity. Macro-scale experiment of bulk materials for higher strain rate have been well established. On the other hand, experiment of the micro and nano scales with higher strain rate has not been established. This study developed an experimental method to conduct micro-particle collisions, causing high strain rate deformation on the target materials surface. This is called laser-induced projectile impact test (LIPIT), which is impact indentation test. Due to laser ablation, we could successfully project micro-particles, resulting in particle collision with the material surface at higher strain rate. By changing the laser energy, the indentation crater depth can be significantly changed. We established a testing method which is capable of higher strain rate at micro-scale. In addition, finite element method (FEM) was carried out to simulate the plastic deformation behavior due to particle collision at higher strain rate, so that we investigate plastic deformation at the micro scale under higher strain rate.
Solar Distillation Systems Enriched With Machine Learning Techniques: A Review
Authors: Prasanna Y. S. , Deshmukh Sandip S.
Published: January 2022

Solar stills have the advantage of using solar radiation as they are the simple thermal energy source for saline water and industrial water desalination. This paper focuses on a detailed review of how a solar distillation system performance evaluation can be made with ongoing higher-end Machine learning techniques explicitly helpful in optimising and evaluating the still performance. Complete research on the implementation of ML models is made in this study to draw the feasibility of implementing the appropriate supervised or unsupervised machine learning methods. A comparison of the two of deep learning models applied in the advancement of the solar distillation process is explained in this study. The need for performance assessment of solar distillation system with Machine Learning Techniques is analyzed, and further significant features and components of ML and DL Methods are clearly explained. Keeping the importance of the study in front, a comparative analysis is made from the observations found in the literature review. We conclude that the Classification ML Techniques with ANN are the most appropriate models to predict the solar distillate while the ANN-MLP, ANN-FF models are more accurate than the other models. Instead of a traditional statistical approach, a DNN Hybrid model with more hidden layers can be used in optimising the water depth.
Soft Piezoelectric Composites: Synthesis, Electro-Elastic Property Characterization, and Non-Linear Constitutive Modeling
Authors: Lowe Robert L. , Beckett Joseph G. , Cooley Christopher G. , Bai Zongwu , Kladitis Paul E.
Published: January 2022

Soft piezoelectric composites (SPCs) show great promise as next-generation energy harvesting materials, with the potential to outperform piezoelectric polymers with limited elastic stretchability (e.g., PVDF) and traditional brittle piezoelectric ceramics (e.g., PZT). Presently, however, SPCs remain an emerging class of materials, with relatively few comprehensive investigations holistically exploring their synthesis, electro-mechanical property characterization, large-strain constitutive modeling, and non-linear mechanics and dynamics. In this paper, we take first steps toward addressing this compelling research opportunity. A three-component SPC is synthesized, consisting of an ultra-stretchable Ecoflex silicone rubber matrix, micron-sized PMN-PT piezoelectric particles, and CNTs that serve as inter-particle conductive “bridges.” Mechanical, electrical, and coupled electro-mechanical properties are quantified. A thermodynamically consistent, fully non-linear, finite-strain constitutive model is presented, based on a gentle adaptation of an existing transversely isotropic non-linear electro-elastic constitutive framework. Use of the particle orientation vector as an independent variable leads to two-way coupling between mechanics and electricity not present in the isotropic counterpart of this constitutive model. A prototype free energy function with the electric field as the independent variable is proposed that captures the essential physics. This free energy leads to a compact set of non-linear, finite-strain constitutive equations whose mathematical forms have direct analogue to the linear, small-strain theory of piezoelectricity.
Process Mapping of Additively-Manufactured Metallic Wicks Through Surrogate Modeling
Authors: Borumand Mohammad , Esfandiarpour Borujeni Sima , Nannapaneni Saideep , Ausherman Moriah , Madiraddy Guru , Sealy Michael , Hwang Gisuk
Published: January 2022

Tailored wick structures are essential to develop efficient two-phase thermal management systems in various engineering applications, however, manufacturing a geometrically-complex wick is challenging using conventional manufacturing processes due to limited manufacturability and poor cost effectiveness. Additive manufacturing is an ideal alternative, however, the state-of-the-art metal three-dimensional printers have poor manufacturability when depositing pre-designed porous wicks with pore sizes below 100 μm. In this paper, a powder bed fusion 3D printer (Matsuura Lumex Avance-25) was employed to fabricate metallic wicks through partial sintering for pore sizes below 100 μm with data-driven control of process parameters. Hatch spacing and scan speed were selected as the two main AM process parameters to adjust. Due to the unavailability of process maps between the process parameters and properties of printed metallic wick structures, different surrogate-based models were employed to identify the combinations of the two process parameters that result in improved manufacturability of wick structures. Since the generation of training points for surrogate model training through experimentation is expensive and time-consuming, Bayesian optimization was used for sequential and intelligent selection of training points that provide maximum information gain regarding the relationships between the process parameters and the manufacturability of a 3D printed wick structure. The relationship between the required number of training points and model prediction accuracy was investigated. The AM parameters’ ranges were discretized using six values of hatch spacing and seven values of scan speed, which resulted in a total of 42 combinations across the two parameters. Preliminary results conclude that 80% prediction accuracy is achievable with approximately forty training points (only 10% of total combinations). This study provides insights into the selection of optimal process parameters for the desired additively-manufactured wick structure performance.
Effect of Heat Treatment on Microstructure and Hardness of Graphene Nanoplatelets Reinforced Al-Zn-Mg-Cu Alloy Composite
Authors: Sharma Ankit , Pratyush Akula Sai , M. Srinitesh , Gupta Amit Kumar , Sujith Ravindran
Published: January 2022

Excellent mechanical, electrical, and thermal properties of the sp2 hybridized carbon allotrope derivative of graphene nanoplatelets (GNP) make it a suitable reinforcement candidate for the metal matrix composite. Due to the superior properties of Al – Zn – Mg – Cu alloy, it is used as an armor material for decades in defense industries. In this study, Al – Zn – Mg – Cu alloy/GNP reinforced composite with varying weight fraction of 0, 0.5% & 1% GNP was fabricated via hot-pressing sintering. Initial investigation shows that the composites were densified, and the relative density was 99.64% after the fabrication process. Two-stage heat treatment was performed on the Al alloy, forming a stable η (MgZn2) phase. The DSC plots show the dissolution of the unstable η´ (Mg4Zn7) phase into the stable η (MgZn2) phase in between 450 °C – 480 °C and homogenized due to artificial aging process with the α-Al phase. Investigation showed an increment in the hardness of the heat-treated 0.5% GNP reinforced composite by 15.44%, and 8.92% in the heat-treated 1% GNP reinforced composite compared to their non-heat treated composites. The Field Emission Scanning Electron Microscopic images of samples before heat treatment show agglomeration of GNP and heterogeneous nucleation, and images after heat treatment show that GNP has been dispersed into the grains and grain boundaries alongside the eutectic phases, which restrict the dislocation motion and strengthen the matrix by grain boundary strengthening.
Framework for Automated Robotic Arm Manipulation in Variable Industrial Environments
Authors: Pradhan Anvay A. , Martin Will C. , Danesi Ruiz Juliana , Deierling Phillip E.
Published: January 2022

In this paper, we present a generalized, holistic method for automated robotic arm handling of manufactured components in an industrial setting using computer vision. In particular, we address scenarios in which a high volume of manufactured parts are moving along a conveyor belt at random locations and orientations with multiple robotic arms available for manipulation. We also present specific, tested solutions to all stages of the framework as well as some alternative methods based on the literature review. The framework consists of three stages: (1) visual data capture, (2) data interpretation, and (3) command generation and output to robotic arms. In the visual data capture stage, a multi-component computer vision system takes in a live camera feed and exports it to an external processor. In the data interpretation stage, this video feed is interpreted using tools like 3D point clouds and object detection/tracking models to provide useful information such as object number, location, velocity, and orientation. Lastly, the command generation and output to the robotic arms stage takes the information acquired from the analysis in the data interpretation stage and turns it into instructions for robot control. While a full-scale, cohesive system has yet to be tested, our solutions to each stage show the feasibility of implementing such a system in an industrial setting.
Damage Quantification of High-Rate Impacts Using Hybrid Deep Learning Models
Authors: Todisco Mark , Mao Zhu
Published: January 2022

The ability to classify the damage of a structure caused by high-rate, high-acceleration impacts has been of scientific interest for many years. These dynamic events are often nonstationary with broadband spectral energy, making damage classification in this setting significantly more challenging. Recently, structural health monitoring (SHM) has benefitted from data-driven techniques, such as deep learning, that can overcome unclear system dynamics. This paper presents a hybrid damage classification method that fuses deep, shallow, unsupervised, and supervised machine learning (ML) algorithms, and classifies the damage levels of a structure. A deep unsupervised Convolutional Variational Autoencoder (CVAE) first extracts features containing the structure’s damage information. A shallow supervised support vector machine (SVM) classifier then uses the extracted damage information to predict the structure’s damage level. This hybrid damage classification method is applied to a highly instrumented electronic assembly subjected to high-rate high-acceleration drop tower impacts. Using the extremely limited and sparse data collected from these experiments, the hybrid SHM method infers the electronic assembly’s damage level with an accuracy of 73.0% and an F1 score of 72.9%. This technique can also be extended to remaining useful life (RUL) prediction.
Derivation of Loading Surfaces for a Nitinol Triply Periodic Minimal Surface Unit Cell Subjected to Cyclic Loading
Authors: Carcavilla Adriano Cebrián , Zaki Wael
Published: January 2022

This paper intends to describe the process of derivation of loading surfaces with respect to phase transformation, when a structure is subjected to cyclic loading. This structure is realized as a Schwarz Primitive unit cell, for which only 1/16th part is considered, due to the symmetry conditions. Displacement boundary conditions are applied to realize the periodicity of the unit cell, thus simulating the presence of adjacent unit cells. A homogenization of the stress fields is done, so as to obtain volume-averaged values that represent the whole domain. One limitation of the employed constitutive model is not considering plasticity. The large stresses observed in the results would be alleviate in a real application by plastic deformation. Another limitation of the model is not considering a thermomechanical coupling. Therefore, the heat that would be generated depending on the frequency employed is not taken into account. Thus, the frequency of the applied displacements only plays a role in the simulation time. One hypothesis is that the curves in a stress space will shrink as more cycles are performed, due to a higher martensite volume fraction. This is a consequence of functional fatigue. The curves are indeed observed to shrink in an axisymmetric way, due to the lack of phenomena to shift the curves along any of the axis.
A New Approach to Develop an Intelligent Manufacturing System Using Virtual Tools
Authors: Guerra-Zubiaga David , Morton Corey , Stacey Derrick , Peach Virginia , Ham Chan , Escobar Escobar Diego , Hitchcock Noah
Published: January 2022

Intelligent automation could be applied to continuous processes and discrete manufacturing. This research is presenting a new approach exploring intelligent automation on discrete manufacturing. A degree of smart integrated manufacturing is presented according to industry 4.0 trends. In this research a digital twin is explored incorporating some new manufacturing paradigms such as Industrial Internet of Things (IIoT), Cloud Manufacturing (CM) and Machine Learning (ML) in the creation of new intelligent manufacturing systems. A virtual simulation of B&R’s SuperTrak with magnetic shuttle technology is presented as a digital twin concept and specific aspects of IIoT, CM and ML are connected to extend smart manufacturing aspects providing the intelligent automation on discrete manufacturing. The aim of this research is to present a new approach to develop an intelligent manufacturing system using virtual tools.
Computational Fluid Dynamics to Study the Origin of Secondary Flows in Square Ducts With Straightened Elbow Concept Governed by Artificial Body Force
Authors: Ayala Orlando , Humphries Thurston , Youells Tyler , Thomas Jahshawn , Ayala Manuel
Published: January 2022

The 90° pipe bend is perhaps the most frequently used fitting in piping systems. The secondary flow and associated losses occurring in such bends are therefore of considerable engineering importance. However, although many investigators have studied the problem, it is still unclear how secondary flows develop, and get triggered. The curvature of the 90-degree elbow induces centrifugal force, causing the development of such secondary flow. The intensity of the secondary flow is dependent on the radius of the bend curvature (R) and Reynolds number (Re). The objective of this study is to gain an understanding of how of the triggering mechanism and development of this flow which should depend on R and Re. A commercial tool, COMSOL Multiphysics, is used to model the flow in a fully straight duct under the action of a “centrifugal” body force was studied. The domain of study was divided in three duct sections, the inlet duct, the “elbow” duct (where the “centrifugal” body force was applied), and the outlet duct. Special attention was paid to the secondary flows in the “elbow” duct near the elbow inlet. The study is conducted for different laminar Reynolds numbers (Re = 10 and 100), and different radius of curvatures (R/D = 2 and 5). It was found both the pressure gradient in the flow transversal direction and the flow “radial” advection appear to be responsible for the initiation of secondary flow phenomena and its propagation. When using slip wall conditions, the secondary flow gets weaker, or even its swirling motion disappears. It also appears to be that the full formation of the secondary flow of the vortex type occurs at the same “arc length” distance, regardless of the representative “radius of curvature.”
Characterization of the Leading-Edge Erosion of Wind Turbine Blades by Sand Particles Impingement
Authors: Alajmi Abdullah F. , Ramulu M.
Published: January 2022

Solid particle erosion experiments have been conducted on the leading-edge of a wind turbine blade with silica sand as the abrasive material. Two variables have been investigated in this experiment: the angle of attack at which particles impact the leading-edge and the erosion duration. For the angle of attack, four angles of attack have been used, namely: −5°, 0°, 5°, and 10°, and for erosion duration, 180 seconds and 360 seconds were used. Two parameters have been used to analyze the erosion behavior: the amount of material removed and the erosion scars’ depth. Then, to record the change in the airfoil profile, a 3-D scanner was used before and after the erosion experiments. It has been found that, on average, the highest erosion rate and depth of erosion scars occurred at 0°, which resulted in the most alteration in the 2D profile of the airfoil, while the least damage observed was caused by 10° angle of attack. The erosion scars created by the four angles of attack were superposed to create an erosion scar similar to that created by sandstorms, extrapolated along the blade, and the total mass loss was calculated. Then, a model to estimate the amount of material removed from the leading edge of wind turbine blades using the depth of erosion scars was proposed. Finally, a preliminary aerodynamic analysis has been conducted in terms of lift and drag coefficients before and after erosion. It has been found that with the increase of intensity in erosion, the change in the aerodynamic performance increases.
Bioreactor Temperature Control System Using PID Controller
Authors: Alimberti Richard , Chauhan Vedang , Jaiswal Devina
Published: January 2022

Bioreactors are engineered physiological environment that can be used to study and grow tissue and organ systems in vitro. They are used to subject the cells to physiologically relevant stimulus such as tensile or compressive stress, bending, torsion or fluid flow. An optimal internal environment of a bioreactor should remain sterile while maintaining the viability of tissue, cells and biomolecules at 37°C (normal body temperature) with a tolerance of + or −0.1 °C. This study presents an Arduino microcontroller-based temperature-controlled system using an autotuning proportional integral derivative (PID) control for a small-scale bioreactor. A table top bioreactor temperature control system was designed, fabricated and assembled with laser cut acrylic enclosure. The closed-loop control system maintained the set temperature of 37°C using a tuned PID controller that used a high precision TMP117 sensor for feedback, and controlled the heating element accordingly. The system achieved the desired performance characteristics such as a fast rise time, settling time, low overshoot and low steady state error. Once the system achieved the steady state, it maintained the temperature at 37 ± 0.1 °C. Since the temperature control can vary and monitor fine changes in the environment, the system can be used to study an impact of temperature variations on cell response such as growth and differentiation.
Analysis of Process Physics in Electron Beam Melting
Authors: Hedreen Mark , Doyle Curtis , Bol Eric , Kelley Garrett , Ramulu M.
Published: January 2022

Electron Beam Melting (EBM) is a novel additive manufacturing process capable of producing production-quality metal components. The physics of EBM are complex, involving highly non-linear heat and mass transfer effects. Understanding these physical phenomena is key to producing quality components.

In this study, a variety of analytical and numerical models are demonstrated to characterize the relationship between material properties, process parameters, and the resulting physical behavior during printing, with Ti-6Al-4V and Inconel 718 as test cases. The thermal and fluid flow behaviors are analyzed with several dimensionless numbers and the sensitivity to various factors is discussed. Radiative and evaporative heat loss are calculated, taking into account the effects of activity coefficient on vapor pressures in an alloy system. Compositional losses during printing are calculated and a method to optimize composition is discussed.
Verification and Validation of a Small Wind Tunnel Data Acquisition System
Authors: Doom Alex J. , Hollingsworth Elena , Bishop Riley , Fisher Wesley , Mazzoni Brian , Manohar Chidurala
Published: January 2022

This paper discusses the design, validation, and verification of a wind tunnel data acquisition system that measures the pressure distribution around a cylinder and airfoil and calculates the resulting lift and drag forces acting on the object in cross flow. Typical aerodynamic research is conducted using wind tunnels with large test sections and high air speeds, which can be expensive and unattainable for many universities. A traceable path of validation can improve the results of experimentation on small test section and low speed wind tunnels by providing important information on the accuracy, uncertainty, and error involved in the system. It is concluded that CFD verification and validation not only improves experimentation but is the key to conducting quality research with limited resources.
The High Cycle Fatigue Behavior of Surface Treated Electron Beam Melted Titanium Ti6Al4V
Authors: Mojib Melody , Soyama Hitoshi , Sanders Daniel , Arola Dwayne , Ramulu M.
Published: January 2022

With the growth of Additive Manufacturing (AM) or 3D printing, the need for long lasting metal components for high-stress applications is becoming increasingly crucial. One of the biggest limitations is the low fatigue life of AM components due to a variety of factors including build orientation, surface roughness, and internal defects. To address the low fatigue behavior of metal AM components, there is an increase in interest in performing surface treatments such as machining or polishing on additive manufactured components. With AM’s unique potential to produce complex shapes, the ability to perform conventional surface processes on printed parts becomes difficult and limited. Preliminary effects of tool-less post processing techniques on fatigue life titanium Ti6Al4V specimens has been explored in this study with specimens undergoing hot isostatic pressing (HIP), in addition to a surface treatment process including cavitation peen, laser peen, shot peen or cavitation abrasive surface finishing. Uniaxial high cycle fatigue testing has been performed on untreated, HIP, and HIP + surface treated cylindrical electron beam melting (EBM) specimens. The location of crack initiation has been determined under high magnification and the location of internal defects are evaluated using micro-Computer Tomography (μCT). The location of crack initiation in all specimens was attributed to the sharp voids due to the rough surface or the subsurface defects which remained after post processing. The shot peen and polished titanium specimens exhibited the greatest increase in fatigue life due to the improvement in roughness and introduction of high compressive stresses.
Robotic-Based Repair of Concrete Structures: A Surface Crack Filler Robot
Authors: Stevens Melinda , Arellano Samuel , Rodriguez Diego , Wilson James , Gutierrez Zady , Trudell Noah , Momeni Hamed , Ebrahimkhanlou Arvin
Published: January 2022

Surface cracks in concrete structures are often indicators of more substantial damage and may negatively affect the durability of a structure. To ensure the soundness of these structures, surface cracks should be quickly detected; this project proposes a robot with the ability to detect, map, and fill surface cracks. The robot will use a Bayesian network to fuse the multi-sensor data provided via an RGB camera, a stereo infrared depth sensor, and a LIDAR sensor. It will also be fitted with a newly designed piston-driven syringe system to inject a concrete filler material in a controlled manner. A non-captive lead screw and stepper motor drive the piston along with the syringe, and an arm with two degrees of freedom will allow the robot to position the injector along a crack accurately. To control the arm, the Bayesian network and sensor systems will work in unison to determine when a crack has been filled in a satisfying manner, ensuring a degree of uniformity and consistency in the repaired concrete surface.
A Novel Image-Based Method for In Situ Characterization of the Pore Size Distribution and Dimensional Accuracy of Bone Tissue Scaffolds
Authors: Abdelgaber Yousef , Klemstine Cole , Lawrence Logan , Day James B. , Claudio Pier Paolo , Salary Roozbeh (Ross)
Published: January 2022

Pneumatic micro-extrusion (PME) is a high-resolution direct-write additive manufacturing method, which has been widely utilized for the fabrication of biological tissues, structures, and organs. The PME process allows for non-contact, multi-material deposition of a wide range of functional bio-inks for tissue engineering applications. However, the PME process is inherently complex, governed by complex multi-physics phenomena. Consequently, investigation of the effects of significant process parameters and their interactions on scaffold functional properties would be inevitable.

The overarching goal of this research work is to fabricate defect-free, porous bone scaffolds for the treatment of large osseous fractures. In pursuit of this goal, the objective of the work is to forward an image-based method for the characterization of the pore size distribution as well as the dimensional properties of bone tissue scaffolds, fabricated using the PME process. The developed method will allow for detection of scaffold pores, thus quantification of pore size distribution, and ultimately assessment of the dimensional accuracy of bone tissue scaffolds. The method was validated based on specimens obtained from a single factor experiment. The specimens were composed of PCL, fabricated using the PME process. The results of this study pave the way for fabrication of complex bone scaffolds with accurate dimensional properties for the treatment of bone fractures and defects.
Study of Flow Field Configuration Effect in Cooling Systems
Authors: Carbajal Gerardo
Published: January 2022

A three-dimensional numerical simulation was performed to increase a cooling system’s performance using different flow field configurations. In this study, the cooling system consists of three fluid configurations and contains ten batteries and eleven channels. The fluid flow configurations are the U-configuration, the Z-configuration, and the I-configuration. The battery was modeled assuming a solid material with constant physical properties, and the air is the working fluid in the cooling system. The numerical simulation results showed a better uniform temperature distribution with the I-configuration than the other two configurations. The numerical solution of the coupled fluid-energy equations corresponding to the three configurations indicates a significant effect of the relative flow distribution in the local transfer of energy from the batteries to the airflow: therefore, affecting the temperature distribution of the system’s components. This study assumed four heat inputs and mainly focused on the effect of fluid flow in evaluating the core temperature of the batteries. The worst performance in terms of temperature rise in the system corresponded to the U-configuration. The I-configuration presented the lowest average temperature in the battery’s core; the temperature field was also more uniform than the other two configurations. The U-configuration delivered the lowest pressure drop, and the Z-configuration the highest pressure drop. The results confirmed that it is possible to improve the cooling process by selecting the suitable flow field configuration of the system.
Investigation on Surface Integrity in Axial Ultrasonic Vibration-Assisted Milling In-Situ TiB2/7050Al MMCs
Authors: Liu Xiao-fen , Wang Wen-hu , Jiang Rui-song , Xiong Yi-feng , Shan Chen-wei , Li Jun-chen
Published: January 2022

The particle reinforced metal matrix composites (PRMMCs) are a new kind promising materials with attracting attentions due to its superior properties such as improved strength, low density, excellent low-temperature performance and increased wear resistance. However, it was a difficult-to-cut material due to the existence of hard ceramic particles. Ultrasonic vibration-assisted machining method has attracted many attentions in machining difficult-to-cut materials.

In this study, an experimental investigation was conducted on the effect of cutting and vibration parameters on the machined surface integrity of ultrasonic vibration-assisted milling in-situ TiB2/7050Al metal matrix composites. After all experiments, surface integrity such as surface roughness, residual stress, hardness and machined defects and so on were comparatively analyzed between conventional and ultrasonic vibration-assisted cutting methods. It was found that the machined surface roughness of ultrasonic vibration-assisted milling was a little larger than that of conventional milling while the compressive residual stress of the former was greater than that of the latter. It could be found that it could obtain better machined performance when vibration frequency is 30 kHz and amplitude is 4 μm in the range of given experimental parameters.
Surface Evaporation of Sessile Water Droplet on a Hydrophobic Surface
Authors: Lee Minwoo , Park Chanwoo
Published: January 2022

In this paper, the surface evaporation of a sessile water droplet on hydrophobic solid substrates was numerically and experimentally investigated. The droplet evaporation is governed by multi-dimensional heat and mass transport and interfacial processes of three (gas, liquid, and solid) phases. A Computational Fluid Dynamics (CFD) simulation was performed to analyze the simultaneous heat and mass transfer in the surface evaporation of a sessile water droplet by considering the Marangoni and/or free convection. The results from the CFD simulation were validated using experimental results for the water droplet evaporation on a hydrophobic-coated silicon substrate. It was found that the droplet evaporation rate is greatly increased by a thermocapillary-driven flow (Marangoni convection) in the droplet with small liquid volumes of less than 2.4 μL on the hydrophobic substrate, while the contribution of the free convection is negligible. The peak mass flux of droplet evaporation was always observed along the three-phase contact line.
Implementation of Triply Poly Minimal Surfaces in Design of Phononic Crystals and Acoustic Metamaterials
Authors: Saatchi Daniel , Oh Il-Kwon
Published: January 2022

Triply Poly Minimal Surfaces (TPMS) are three dimensional periodic lattice structures with a trigonometric relationship in their unit cell that can be implemented for acoustic applications including acoustic metamaterials and Phononic crystals. The necessity and demand in the ultrasound and acoustic industry for new materials pave the way to investigate further mechanical wave research into the different shape of engineered metamaterials that usually does not exist in nature for different purposes. This paper presents a design pipeline for Schwarz Primitive acoustic metamaterial from the mathematically driven stage of computational design of the unit cell with the utilization of finite element method to simulate the Phononic bandgaps, acoustic pressure, wave propagations, sound pressure levels, and sound transmission loss. The effect of periodic, Floquet, symmetry, & dipole boundary conditions as well as the effect of the upstream and downstream numerical domain extension on the final transmission loss signal in the simulations are compared. These numerical evaluations are important for future experimental acoustic measurement in the different impedance tubes with different microphone positions and sample setups. Finally, the initial stage of additive manufacturing using Stereolithography 3D printing technology for the fabrication of TPMS sample to compare the numerical data with experimental acoustic data is addressed as well as its potential applications to use in the different industries.
Helium Degassing Filter for Mercury Process Gas Liquid Separator
Authors: Weinmeister Justin , Ottinger Dustin , Barbier Charlotte
Published: January 2022

Testing was conducted to find a suitable filter to help separate helium gas from the Spallation Neutron Source’s mercury process loop. This filter is proposed for installation on the gas-liquid separator (GLS) vent line to prevent a column of liquid mercury from flowing outside of the process loop shielding in the service bay. The filter’s desired properties are to prevent the passage of liquid mercury, provide minimal resistance to helium flow, resist radiation, operate for the lifetime of the target, be replaceable, and have a reliable construction. Testing concluded that the Mott Corporation POU-10-S series of filters provided the best performance available. The filters could stop most liquid mercury passage while allowing helium passage at nominal pressures above the GLS in standard conditions. This result has several implications for the design of the GLS vent system.
Review of Fault Detection and Diagnosis Studies on Residential HVAC Systems
Authors: Ejenakevwe Kevwe A. , Song Li
Published: January 2022

Heating, Ventilation and Air Conditioning (HVAC) control and energy usage management has been identified as a promising way of improving building energy efficiency and thus contributing to solving the energy challenges of the world. However, a critical aspect of reducing HVAC energy usage is fault detection and diagnosis (FDD). Several studies have been conducted on FDD in HVAC systems with less focus on residential HVAC systems. One reason identified for this reduced attention with residential HVAC is that state-of-the-art FDD tools greatly depend on data available through the building automation system (BAS), and this detailed data is not typically available in the residential sector. Meanwhile, using sensors for developing FDD-enabled HVAC systems is not cost-efficient due to the cost associated with required sensors compared to the energy savings realized, thus making residential FDD less attractive. However, studies have shown that faults cause an additional 20.7TWh of energy consumption from residential HVACs across the US, annually. Thus, this paper gives a critical review of various studies that have been done on FDD in residential HVAC systems and proposes a data analytical approach, which if actualized, could reduce the sensor requirements for FDD in residential HVAC, thus addressing the cost barrier.
Modal Interaction in a Levitation Force MEMS Based Resonator
Authors: Zamanzadeh Mohammadreza , Meijer H. G. E. , Jafarsadeghi-Pournaki Ilgar , Ouakad H. M.
Published: January 2022

This work aims to examine the possibility of internal resonances (modal interactions) among the vibration modes of a levitation force Micro-electro-mechanical Systems (MEMS) based resonator. The actuating levitation force is generated through a special arrangement consisting of two stationary side electrodes (both electrically charged) and a middle grounded unit consisting of the stationary electrode located beneath a moving electrode (micro-beam). Both “cantilever” (CL) and “clamped-clamped” (CC) microbeams are analysed as the moving element of this especial design in which the applied voltage pushes away the micro beam from the underneath substrate. All possible commensurable relations between the frequencies are inspected. We use the numerical bifurcation toolbox MatCont to capture the computed frequency response branches and examine their stability. A period-doubling bifurcation for the possible onset of chaotic attractors is inspected as well. A preliminary eigenvalue problem analysis suggests the internal resonance may exist in both (CC and CL) cases. However, an extended dynamical analysis shows that just a 3-to-1 modal interaction (between the first and third modes) in the CC arrangement is possible. The effects of dominant force-related terms are plotted through associated plots. These diagrams demonstrated that this design exhibits a rich internal resonance behavior that can be controlled with different geometrical and actuating parameters. Overall, this effort provides a systematic methodology and simple guidelines for indepth exploration of internal resonances in levitation force-based microbeams. The outcomes of this work could also assist in the development of MEMS sensors based on the internal resonance phenomenon.
Design for Additive Manufacturing: A Framework to Collect and Reuse Engineering Knowledge Towards a CAD-Based Tool
Authors: Favi Claudio , Mandolini Marco , Campi Federico , Cicconi Paolo , Germani Michele
Published: January 2022

Within the context of modern industries, additive manufacturing (AM) plays a critical role. Design for AM (DfAM) requires defining design actions related to the product’s geometry under development. DfAM affects design choices such as the type of process, the material, the geometry, and the model’s features. Knowledge-based engineering (KBE) is promising for integrating DfAM principles in the early phases of product development. Still, few limitations are noticed, such as the real interoperability between DfAM and 3D CAD systems, leading to the application of proper DfAM rules downstream of the 3D modeling. This paper aims to describe a method to formalize AM engineering knowledge used as a repository to develop a CAD-integrated decision support tool by acknowledging the current gap. The method uses, as input, geometrical data retrieved by the feature analysis of the 3D CAD model (feature recognition approach) and manufacturing information related to AM processes. The method will allow closing the gap between the design and production departments by creating a knowledge-based system. The outcome of this system does not concern the possibility of predicting the AM process parameters. The system will support engineers in delivering product designs compliant with AM processes. Based on this system, a CAD-integrated DfAM tool can be developed in the future.
Nuclear Power: On PRA and Protective System Maintenance
Authors: Kee Ernie , Wortman Martin
Published: January 2022

The processes used in managing protective system equipment failures in the commercial nuclear power setting are reviewed. We assert that efficacy of protection is governed by maintenance policy that includes system modification, maintenance inter-arrivals as a function of time, and upset inter-arrivals as a function of time; we further assert that such a maintenance policy is the one used in nuclear power plant protective systems. Observations described in this article bear on the impact of time-dependent activities, associated with maintenance policy, as they relate to endogenous and exogenous upset inter-arrival times. We describe why methods evaluating maintenance policy reliant on combinatorial logic, such as Probabilistic Risk Assessment (PRA), fault trees, or event trees, may lead to ineffective maintenance policy decision-making for protective system efficacy, and we show why this is true. Recommendations for maintaining effective protections, and connections to engineering maintenance practice and regulations are made based on the implications that come from our observations. The importance of the issues described is that relationship of design, maintenance, and repair policies must be properly understood and taken into account by process owners, operators, and investors as well as regulators, who manage protections in hazardous processes.