bluuebunny/crossref_metadata_2025_split huggingface dataset:
Engine Combustion System Optimization Using Computational Fluid Dynamics and Machine Learning: A Methodological Approach
Authors: Badra Jihad A. , Khaled Fethi , Tang Meng , Pei Yuanjiang , Kodavasal Janardhan , Pal Pinaki , Owoyele Opeoluwa , Fuetterer Carsten , Mattia Brenner , Aamir Farooq 
Published: August 2020

Abstract
Gasoline compression ignition (GCI) engines are considered an attractive alternative to traditional spark-ignition and diesel engines. In this work, a Machine Learning-Grid Gradient Ascent (ML-GGA) approach was developed to optimize the performance of internal combustion engines. ML offers a pathway to transform complex physical processes that occur in a combustion engine into compact informational processes. The developed ML-GGA model was compared with a recently developed Machine Learning-Genetic Algorithm (ML-GA). Detailed investigations of optimization solver parameters and variable limit extension were performed in the present ML-GGA model to improve the accuracy and robustness of the optimization process. Detailed descriptions of the different procedures, optimization tools, and criteria that must be followed for a successful output are provided here. The developed ML-GGA approach was used to optimize the operating conditions (case 1) and the piston bowl design (case 2) of a heavy-duty diesel engine running on a gasoline fuel with a research octane number (RON) of 80. The ML-GGA approach yielded &gt;2% improvements in the merit function, compared with the optimum obtained from a thorough computational fluid dynamics (CFD) guided system optimization. The predictions from the ML-GGA approach were validated with engine CFD simulations. This study demonstrates the potential of ML-GGA to significantly reduce the time needed for optimization problems, without loss in accuracy compared with traditional approaches.
A Wire-Driven Multifunctional Manipulator for Single Incision Laparoscopic Surgery
Authors: Chowdhury A. M. Masum Bulbul , Cullado Michael J. , Shen Tao 
Published: August 2020

Abstract
Minimally Invasive Surgery (MIS) has gained popularity in current abdominal surgical procedures due to its reduced skin incision length, shortened recovery time and decreased postoperative complications. One trend is to enhance these benefits by developing technologies to expand the application of single incision laparoscopic surgery (SILS) which has even less incision and incision-related complication. However, the practical application of SILS has been constrained by many complexities, including fundamental procedure issues (e. g. limited space), as well as the issues related to surgical tools, such as lack of actuation force, weak tool tips, poor visualization and lack of dexterous multitasking tools. Due to this lack of multitasking tools, the surgical tools or robots have to be retracted, exchanged and reset multiple times during the surgery, increasing the surgical time, the risk of injury and the surgeon’s level of fatigue. This paper focuses on developing a multifunctional manipulator with an automatic tool changing capability to boost practical application of SILS. The manipulator uses a wire-driven method that minimizes the potential damage from sterilization since the electronic actuation and sensing components are located remotely from the end-effector which needs heat or chemical sterilization before surgery. The feasibility of the tool tip changing method has been demonstrated by experiments.
Classification of Left Atrial Appendage Morphology Using Deep Learning
Authors: Holm Mikayle A. , Deakyne Alex , Gaasedelen Erik , Upchurch Weston , Iaizzo Paul A. 
Published: August 2020

Abstract
Atrial fibrillation, a common cardiac arrhythmia, can lead to blood clots in the left atrial appendage (LAA) of the heart, increasing the risk of stroke. Understanding the LAA morphology can indicate the likelihood of a blood clot. Therefore, a classification convolutional neural network was implemented to predict the LAA morphology. Using 2D images of 3D models created from MRI scans of fixed human hearts and a pre-trained network, an 8.7% error rate was achieved. The network can be improved with more data or expanded to classify the LAA from the automatically segmented DICOM datasets and measure the LAA ostia.
Minimizing Cotton Ball Retention in Neurological Procedures
Authors: Bechtold Raphael , Garlow Benjamin , Liu Renee , Tandon Arushi , Szewc Alexandra , Zhu William , Musmanno Olivia , Gorelick Noah , Suk Ian , Huang Judy , Brem Henry , Manbachi Amir , Coles George 
Published: August 2020

Abstract
Neurosurgical operations are long and intensive medical procedures, during which the surgeon must constantly have an unobscured view of the brain in order to be able to properly operate, and thus must use a variety of tools to clear obstructions (like blood and fluid) from the operating area. Currently, cotton balls are the most versatile and effective option to accomplish this as they absorb fluids, are soft enough to safely manipulate the brain, act as a barrier between other tools and the brain, and function as a spacer to keep anatomies of the brain open and visible during the operation. While cotton balls allow neurosurgeons to effectively improve visibility of the operating area, they may also be accidentally left in the brain upon completion of the surgery. This can lead to a wide range of post-operative risks including dangerous immune responses, additional medical care or surgical operations, and even death. This project seeks to develop a unique medical device that utilizes ultrasound technology in order to minimize cotton retention after neurosurgical procedures in order to reduce undesired post-operative risks, and maximize visibility.
Improving Footwear Options for Persons With Lower Limb Amputations
Authors: Nickel Eric , Voss Gregory , Slater Billie , Mueller Emily , Hansen Andrew 
Published: August 2020

Abstract
Men and women with lower limb amputations struggle with managing the balance between prosthesis alignment and shoe heel rise. A novel prosthetic ankle-feet system is being developed to support a wider range of footwear options for men and women with lower limb amputations. Each rigid foot is customized to fit the footwear of choice and can be rapidly attached to (or released from) an ankle unit which remains attached to the prosthesis.
The ankle unit has a mass of 318g and is small enough to fit in the design volume of a 22cm foot across a range of heel rises. The ankle uses elastomeric bumpers arranged in a wiper design to maximize space efficiency.
Structural testing has shown that the 3D printed custom Nylon 12 feet withstood 4584N of forefoot loading without failure based on the ISO 10328 loading parameters, indicating suitable strength to support safe human use in the laboratory. The feet have a mass of 446g.
Feedback from two women Veterans with lower limb amputations reinforced the importance of improving access to shoes with different heel rises. Future activities will include cyclic fatigue testing, additional weight reduction, and incorporating suggested design refinements.
A Novel Nonparametric Technique for Segmenting Multimode Hyperspectral Images Obtained From Non-Melanoma Skin Cancer Lesions
Authors: Geweid Gamal G. N. , Vasefi Fartash , Tavakolian Kouhyar 
Published: August 2020

Abstract
Keratinocyte Carcinoma, more traditionally known as Non-melanoma skin cancer (NMSC), is the most common cancer in humans. Incidence continues to increase despite increased public awareness of the harmful effects of solar radiation. In this paper, a non-parametric technique based on image registration will be applied to the multimode hyperspectral imaging system to segment Basal Cell Carcinoma (BCC) and Squamous cell carcinoma lesions (SCC). The aim is to enhance Mohs surgery by determining the actual borderlines of the desired area in the patient’s images, leading to increased efficiency and efficacy of the Mohs surgery. The proposed algorithm was applied to four sets of different Multimode hyperspectral Images with Non-Melanoma Skin. The experimental findings showed that the proposed algorithm is effective in Non-Melanoma skin detection. This could lead to improved image-guided excision of cancerous lesions with potential applications in robotic interventions.
Using Computational Modeling Derived From Micro CT Scanning for the Post-Implant Analyses of Various Cardiac Devices
Authors: Valenzuela Thomas , Zhingre Sanchez Jorge , Holm Mikayle , Iles Tinen , Iaizzo Paul 
Published: August 2020

Abstract
There are few medical devices currently utilized that have not had, at the very least, a second iteration. Medical device companies continually strive to improve their product to make it the best on the market. Medical devices are often optimized by defining the size of the device, making it more efficient and/or improving the device to tissue interface. Using the capabilities of the Visible Heart® Laboratories various cardiac devices can be implanted in reanimated swine and human hearts for the assessment of the various aforementioned parameters. After the implantation of these devices and assessment in functional anatomies, specimens were perfusion-fixed and then a micro-CT scanner was utilized to take high-resolution scans of the resultant device and tissue interfaces. These scans are used to generate high-resolution (∼20 microns) 3D models of the numerous implanted devices, measurement analyses, device simulations, and the creation of virtual reality scenes. All can then be used for detailed visual analyses. These abilities to render high-resolution models will allow medical device designers to closely evaluate their designs, in order to optimize their next iterations.
Current and Voltage Choice for North American Railroad Electrifications: 1895-1931
Authors: Allen John G. 
Published: August 2020

Abstract
The variety of currents and voltages adopted by North American railroads between 1895 and 1931 is sometimes seen as confusing. Railroads faced choices between direct current (DC) and alternating current (AC), as well as among different voltages. But closer analysis shows a clear order to the specifications chosen.
The technology options available at the time and the intended functions of these installations explain the specifications that railroads chose. Railroads electrifying fell into three basic groups: 1. Early adopters (usually requiring electrification for tunnels), 2. Railroads electrifying after 1910 for commuter service, and 3. Railroads that electrified for, or at least with freight service in mind.
Each of these faced very different sets of options, and made their choice of electrical specifications accordingly. There were four basic combinations of current and voltage: 1. Low-voltage DC delivered via third rail, 2. Medium-voltage DC, 3. Higher-voltage DC, and 4. AC (almost always single-phase at 11,000 Volts, 25 Hertz).
For railroads in a given category, the practicable choices were in fact limited to one or two options. Contrary to what is sometimes thought, the different electrical specifications reflected an underlying logic, not disorder.
Crash Energy Management Design for the LACMTA HR4000 Heavy Rail Vehicle
Authors: Wang Anbo , Liu Yanwen , Liu Xiaofang , Kirkpatrick Steven W. , Phan Virginia , Bocchieri Robert T. 
Published: August 2020

Abstract
The LACMTA HR4000 heavy rail vehicle was designed to meet the ASME RT-2 Safety Standard for Structural Requirements for Heavy Rail Transit Vehicles. The crash energy management (CEM) structures designed for this vehicle also provide unique performance characteristics through use of a staged combination of CEM technologies. The resulting design, using easily replaceable components, provides reduced repair costs for lower speed collisions, minimizes the number of cars damaged during a collision, while exceeding the RT-2 standard for safety to the operator. None of the CEM technologies used are novel, but their integrated design provides a unique performance in heavy rail vehicle design.
This paper provides an overview of the CEM design development. First, a general description of the CEM system function is provided, including the various CEM technologies used and how they interact during a collision. Then the 1-dimensional and 3-dimensional nonlinear dynamic models developed for optimizing the design are discussed. The CEM test program performed to demonstrate the system function and validate the modeling is described. Finally, the performance of the CEM system in train-to-train collision analyses is presented. Underframe testing was conducted for validation of the simulations.
An Evaluation of Passenger Mass Effects in Crashworthiness Analyses of Heavy Rail Vehicles
Authors: Kirkpatrick Steven W. , Bocchieri Robert T. , Zeigle Alexander , Liu Xiaofang , Liu Yanwen , Wang Anbo 
Published: August 2020

Abstract
The ASME RT-2 Safety Standard for Structural Requirements for Heavy Rail Transit Vehicles requires that crashworthiness analyses be performed for two primary collision scenarios. Both scenarios use a moving train colliding into a stopped train in their ready-to-run loading condition where no passenger mass is included in the analysis. This standard is now frequently cited in technical specifications for new vehicles by transit agencies in North America.
When evaluating a collision scenario, it is a logical extension to consider including passenger weights. A collision has a greater risk of injury if more passengers are onboard. In addition, additional passenger weight increases the kinetic energy at a specific collision speed, which can contribute to the collision severity. The difficulty of including the passenger load is that the passengers are loosely coupled to the train collision response and have independent collision behaviors based on the passenger configurations relative to the vehicle interior. The corresponding occupant decelerations can occur over different time frames than the vehicle deceleration.
This paper describes a 1-dimensional lumped mass method for incorporating passenger weight into crashworthiness analysis. Each car in the train, the large car body mass is given the ready-to-run weight. The additional passenger load is divided into separate masses that are coupled to the car body using nonlinear springs. The separate passenger masses and attributes for the springs are derived from the specific seating layout of a car. Passengers are grouped by the various seating configurations with different timescales for coupling their mass into the car body.
Several collision analyses were performed with this 1D model for the LACMTA HR4000 heavy rail vehicle at the speeds specified in ASME RT-2 (24 and 40 km/h) at both the ready-to-run weight and at the maximum passenger weight. The influence on the crash dynamics and overall permanent stroke of the crash energy management (CEM) structures at each car interface is discussed. For the seating configuration used, a small fraction of the passenger mass is seen to influence the crash dynamics. This is because of the relatively long time it takes to couple much of the passenger mass into the car body relative to the short duration of the primary crash pulse on a car. Consequently, the addition of a large passenger weight did not require a commensurate increase in energy absorption capacity for the CEM structures of vehicle.
Design and Analysis of Elastic-Plastic Collision Post for Railway Vehicles
Authors: Liu Hongtao , Wang Jianran , Liu Xiaofang , Wang Kefei , Luo Qi , Liu Yanwen , Fang Ziwen , Hong Haifeng 
Published: August 2020

Abstract
Collision posts have been required at the front end of railway vehicles to provide protection against intrusion under collision in the US market since 1940s, though it is still not a standard required structure in the Europe and Asia markets. In this paper, typical front-end frame with and without collision posts of railway vehicles are compared to illustrate the pros and cons of collision posts in railway vehicles. Then two different front-end frames with collision posts are introduced in detail to discuss how to take the advantages of collision posts and avoid the drawbacks in different applications. In the first design, the collision posts are placed in front of the energy absorbing elements. When collision happens, the collision posts will deform first before the energy absorbing elements act. As a result, the collision posts and many carbody and cab structures, such as the front-end frame, underframe, cab interior and operator console may under repair even the collision speed is low. However, more space can be utilized for the cab and passenger compartment since the collision posts can be located at the very front of the vehicle. In the second design, there are two stages of energy absorbing elements and the collision posts are placed in the middle. The first stage of energy absorbing elements can absorb low-speed collision energy without damaging other structures and can be replaced easily. To make up for the extra space taken by the first stage energy absorbing elements, the shape and dimension of the collision posts have to be optimized. For both designs, finite element analysis has been used to analyze and optimize the design. Then full-scale test specimens are manufactured and tested to further validate the design and analysis. Based on the design, analysis and test results, an overall evaluation of collision post’s role in passenger protection and vehicle design has been generated.
Optimization of Railroad Bearing Health Monitoring System for Wireless Utilization
Authors: Cuanang Jonas , Tarawneh Constantine , Amaro Martin , Lima Jennifer , Foltz Heinrich 
Published: August 2020

Abstract
In the railroad industry, systematic health inspections of freight railcar bearings are required. Bearings are subjected to high loads and run at high speeds, so over time the bearings may develop a defect that can potentially cause a derailment if left in service operation. Current bearing condition monitoring systems include Hot-Box Detectors (HBDs) and Trackside Acoustic Detection Systems (TADS™). The commonly used HBDs use non-contact infrared sensors to detect abnormal temperatures of bearings as they pass over the detector. Bearing temperatures that are about 94°C above ambient conditions will trigger an alarm indicating that the bearing must be removed from field service and inspected for defects. However, HBDs can be inconsistent, where 138 severely defective bearings from 2010 to 2019 were not detected. And from 2001 to 2007, Amsted Rail concluded that about 40% of presumably defective bearings detected by HBDs did not have any significant defects upon teardown and inspection. TADS™ use microphones to detect high-risk bearings by listening to their acoustic sound vibrations. Still, TADS™ are not very reliable since there are less than 30 active systems in the U.S. and Canada, and derailments may occur before bearings encounter any of these systems.
Researchers from the University Transportation Center for Railway Safety (UTCRS) have developed an advanced algorithm that can accurately and reliably monitor the condition of the bearings via temperature and vibration measurements. This algorithm uses the vibration measurements collected from accelerometers on the bearing adapters to determine if there is a defect, where the defect is within the bearing, and the approximate size of the defect. Laboratory testing is performed on the single bearing and four bearing test rigs housed at the University of Texas Rio Grande Valley (UTRGV). The algorithm uses a four second sample window of the recorded vibration data and can reliably identify the defective component inside the bearing with up to a 100% confidence level. However, about 20,000 data points are used for this analysis, which requires substantial computational power. This can limit the battery life of the wireless onboard condition monitoring system. So, reducing the vibration sample window to conduct an accurate analysis should result in a more optimal power-efficient algorithm. A wireless onboard condition monitoring module that collects one second of vibration data (5,200 samples) was manufactured and tested to compare its efficacy against a wired setup that uses a four second sample window. This study investigates the root-mean-square values of the bearing vibration and its power spectral density plots to create an optimized and accurate algorithm for wireless utilization.
Application of Virtualization to Implement the Automatic Train Supervision System of a Communications Based Train Control System
Authors: Chy John 
Published: August 2020

Abstract
Capacity improvement and obsolescence management are the primary reasons for deploying Communications Based Train Control (CBTC) technology to replace conventional track circuit-based signaling systems like in New York City Transit (NYCT), Baltimore Maryland Transit Administration (MTA) or the San Francisco Bay Area Rapid Transit District (BART). Resignaling projects without stopping revenue operations are highly complex and are referred as brownfield train control projects.
The Automatic Train Supervision (ATS) subsystem in a CBTC System is responsible for monitoring and regulating train operations. The ATS’ responsibilities include functions such as identifying trains, tracking and displaying trains, setting speed restrictions and work zones, automatic and manual routing capabilities. In addition, the ATS serves as the Human Machine Interface (HMI) between Train Controllers at the Operations Control Center (OCC).
One of the challenges in brownfield train control projects is fitting a CBTC ATS subsystem into an already existing Operations Control Center (OCC). The console in the operating theater will need to host both the existing system and the new CBTC ATS workstation. Similarly, the technical rooms may already be at capacity but still need to accommodate the CBTC system in addition to the legacy system for the transition period.
Transferring the OCC to a new building is often part of the modernization program and is the ideal method to mitigate space constraints. However, CBTC deployment is not always associated with transfer to a new larger building with a large OCC theater. Transfer to the new OCC with more space may be done before the CBTC deployment or at the same time as the CBTC revenue service. When there is no new larger OCC, solutions need to be investigated to accommodate both the legacy system and the new CBTC at the existing OCC.
Advancements in virtual technology provides a more efficient solution that reduces the amount of physical space an ATS needs in the OCC without compromising communication and processing speed or capabilities.
This paper describes the different equipment and functionalities of an ATS subsystem and the challenge of fitting each piece into an existing OCC while keeping the legacy system. The paper then discusses the basic technology behind networking, defining the concept of machine virtualization at a high level, and how all these technologies may be used to solve the ATS challenges faced during CBTC resignaling projects.