bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Energy Transition Pathway Towards Building Decarbonization – Coupling CHP Units With Renewable Energy and Energy Storage Systems
Authors: Naman Yasin , Zenouzi Mansour , Kowalski Gregory 
Published: February 2024

Abstract
Integration of combined heat and power (CHP) systems, also known as cogeneration, with renewable energy and energy storage along with electrification of buildings is an energy transition pathway to create resilient, efficient, and economic solutions towards decarbonization and a 100% renewable energy system. Designing and optimizing the size of a CHP system to satisfy both electrical power and thermal load of a given facility while minimizing fuel consumption and carbon dioxide production is a challenging problem. The thermal load can consist of a combination of heating, cooling, or hot water production. Integration of renewable energy sources and/or energy storage presents additional design challenges towards a more sustainable solution.
An interactive design software was developed by the authors to quickly estimate the performance of different configurations of CHP and renewable energy sources and it was tested for an office complex of 4 commercial buildings found in NREL’s dataset End-Use Load Profiles for the U.S. Building Stock. The software is intended to size CHP devices and calculate the Energy Utilization Factor (EUF), CO2 emissions and the rate of Entropy Production. New features were introduced to the software for this study, including a heat pump module and solar PV with electrical storage. The objective of this paper is to compare different configurations of renewable or low emissions technologies and design an appropriate solution for a test data set for a Typical Metrological Year (TMY). The software requires energy inputs separated by cooling load, heating load and electric demand as a time series and the software is used to optimize the plant size to match all the loads to the corresponding systems.
Application of Machine Learning in Process Analysis of the Friction-Stir Welding Technique
Authors: Ahmed Radif Uddin , Alam Chowdhury Sadid , Rahman M. Shafiqur 
Published: February 2024

Abstract
Friction Stir Welding (FSW) is a popular metal joining technique due to its solid-state deformation mechanism and high joining strength. The process is controlled by adjusting the process parameters, including rotational speed, translational speed, and axial force. However, the lack of proper settings and optimization of these parameters can result in a defective weld joint and unexpected failure. The traditional trial-and-error-based experimental and computational approaches for finding the optimal combination of parameters are expensive, time-consuming, and intricate. Machine Learning (ML), a data analysis technique, can be a useful alternative to optimize the process parameters in the FSW process. The tool rotational speed, translational speed, and axial force in FSW can be categorized as the input parameters or feature variables in the ML dataset. On the other hand, a performance parameter, such as the ultimate tensile strength of the welded joint, can be set as the output parameter or the target variable in the dataset. This study presents an ML modeling technique to predict the ultimate tensile strength for an FSW welded joint. A dataset is developed by collecting data for the three features and a target variable from experimental procedures. The skill of the trained ML model is estimated using the k-fold cross-validation procedure. The ML modeling findings for several supervised algorithms are evaluated based on the mean absolute error, root means squared error, relative absolute error, and root relative squared error. The sensitivity analysis is conducted by finding the global correlation coefficient. The ML model is validated by comparing its results with the experimental data and showing a good agreement between the ML model prediction and experimental results.
Slips, Trips and Falls Associated With Floor Mats and Runners
Authors: Kennedy Eugenia , Chen Michelle , Guttag Mark 
Published: February 2024

Abstract
Floor mats and runners are commonly used to protect floor surfaces, prevent exposure to slippery floor surfaces, remove dirt, grit and moisture from footwear and provide ergonomic relief to workers. Floor mats are often installed to prevent slip, trip and fall incidents. However, it has been estimated that annually about 38,000 adults over the age of 65 years old are treated in U.S. emergency departments for slip, trip and fall injuries associated with carpets and rugs. [1] Furthermore, it is estimated that 85% of worker injuries resulting in workers’ compensation claims are attributed to slipping on slick floors. [2] Incidence of falls reportedly increases with each decade of life. [3]
In 2012, an industry standard, “Standard Guide for Commercial Entrance Matting in Reducing Slips, Trips and Falls” was introduced to provide “Criteria for the selection, installation, inspection, care and maintenance of entrance mats and runners in commercial facilities to reduce slips, trips and falls. [4]
This paper will focus on identifying the hazards associated with floor coverings, reviewing the U.S. Consumer Product Safety Commission 2002 to 2022 injury data for all age groups to better understand the trends, quantifying risks associated with floor coverings, and exploring safety controls available to mitigate these risks. Furthermore, the number of incidents related to slips, trips and falls due to floor mats and runners before and after the introduction of the industry standard will be studied.
An Investigation of the Mechanical Properties of a Soft Metamaterial
Authors: Loop Walter , Su Ji , Chakravarty Uttam K. 
Published: February 2024

Abstract
When designing and manufacturing an air or space craft, material selection is very important. Each material selected for the vessel will have different purposes including strength or hull integrity, support, and insulation. No matter what the material’s purpose is, however, the material must be light in order to reduce the force required to achieve lift thus reducing the cost of fuel as fuel is one of the highest costs for air and space travel. Soft metamaterials could be an option to fill some of the roles in manufacturing of air and space craft. While soft metamaterials will not be able to replace steel that forms the hull or supporting structures, they have other possible applications. Soft metamaterials are highly resistant to plastic deformation and are effective acoustic dampeners. Soft metamaterials could be used to insulate the cockpit of a flying vessel to dampen noise and provide some protection from any impact forces that may occur. The objective of this paper is to explore the viability of the application of a soft metamaterial to the aerospace and space industry. The metamaterial in question is manufactured using a mixture of Eccoflex 00-30 and Dragonskin 20 by Smooth-On Inc. in a honeycomb composite structure. The final soft composite material is tested for its mechanical properties including its tensile strength, compressive strength, and its fatigue strength. For the tensile tests, the material is formed into an ASTM D638 shape and stretched until failure in accordance with the ASTM standards. After these physical tests are conducted, a finite element study is analyzed in ANSYS and the results are compared with the physical test results. The model used for the finite element analysis is the neo-Hookean model for elastic materials.
The Influence of Microstructure Models on the Mechanical Behavior of Nickel Coated Continuous Carbon Fiber Reinforced Aluminum Metal Matrix Composites
Authors: Aluko Olanrewaju , Aboelkassem Yasser 
Published: February 2024

Abstract
The microstructural design and modeling of composite materials plays a significant role in both computational and manufacturing innovations. The computational modeling provides the opportunity to rapidly access the influence of the constituents in the metal matrix composites (MMC) on the overall performance of the composite at a minimum cost. However, the continuum descriptions of mechanical behaviors of MMC via the atomistic-informed multiscale method are not fully available. A multiscale analysis of nickel coated continuous carbon fiber reinforced aluminum metal matrix composite is presented herein with different microstructural geometric models and volume fraction of micro constituents. The methodology involved different length scales ranging from nano to macro scales. In this hierarchical multi-scale modeling technique, the outputs of each lower scale are fed into the next higher scale as input data. Molecular Dynamics modeling was performed at the nano scales and polycrystalline materials model was done at meso scale. High-fidelity Generalized Method of Cells (GMC) micromechanical model was utilized at the macro length scale. The results are in agreement with the experimental data in the literature and also provide a better understanding of the link between the material variables and the composite performance.
Uncertainty Quantification in the Prediction of Remaining Useful Life Considering Multiple Failure Modes
Authors: Gandur Nazir Laureano , Ekwaro-Osire Stephen 
Published: February 2024

Abstract
Despite the substantive literature on remaining useful life (RUL) prediction, less attention is paid to the influence of epistemic uncertainty and aleatory uncertainty in multiple failure behaviors in the accuracy of RUL. The research question in this study was: can uncertainties be quantified in predicting the RUL of systems with multiple failure modes? The first objective was to quantify the uncertainties in the prediction of RUL, considering known multiple failure modes. This objective used vibration data from accelerated degradation experiments of rolling element bearings. The second objective was to calculate the uncertainties in the prediction of RUL, considering the multiple failure modes as unknown. The experimental data used in this objective was from run-to-failure tests of Li-ion batteries. An analysis was performed on how the uncertainties affect the RUL prediction in systems with known multiple failure modes and systems with multiple failure modes as unknown. A Bayesian neural network was used to quantify epistemic and aleatory uncertainty while predicting RUL. The results of the qualitative uncertainties on RUL in systems with multiple failure modes were presented and discussed. Also, the study yielded an RUL uncertainty quantification model for multiple failure modes. The proposed framework’s performance in the RUL prediction was demonstrated. Finally, the epistemic and aleatory uncertainties were quantified in the RUL of the system. It was shown that multiple failure modes have more sources of uncertainties, leading to an increase in the total uncertainty in the estimated RUL and a lower RUL value. The results in this paper may lead to the design of more reliable systems that exhibit multiple failure modes.
Hammering-Assisted Incremental Forming of Al Alloy 1050: Assessment Of Mechanical and Fracture Properties
Authors: Shahare Harshal Y. , Dubey Abhay Kumar , Kumar Pavan , Tandon Puneet 
Published: February 2024

Abstract
Incremental sheet forming (ISF) has gained popularity as a dieless manufacturing method for forming free-form shapes in small batches. Nonetheless, the traditional incremental sheet forming (ISF) process is characterized by poor surface quality and uneven thinning. Incremental sheet hammering (ISH), a hybrid process that integrates hammering into the ISF process, improves formability, surface quality, and mechanical properties. The ISH process creates impact marks and overlapping regions between two impacts during the forming operation, which helps achieve better surface quality. This research investigates the improvement in mechanical properties of the fabricated component using the ISH process when compared with the conventional ISF process. The experiments are performed on 2 mm thick sheets of AA1050, which are also used for the material characterization tests, including tensile and fracture toughness tests. The results show that the component formed via the ISH process has higher elongation of about 13%, resulting in higher ductility and strength. Additionally, the components fabricated with the ISH process show 4% higher fracture toughness while the mechanical strength is almost similar to those formed using the ISF process. The ISH process not only improves structural accuracy but also enhances the mechanical properties of the formed components.
Analytical Modeling of Metal Foam Composite Phase Change Materials (PCM) in Thermal Energy Storage Using Asymptotic Analysis
Authors: Xu Minghan , Akhtar Saad , Zueter Ahmad F. , Mohit Mohammaderfan , Sasmito Agus P. 
Published: February 2024

Abstract
The use of phase change materials (PCMs) for thermal energy storage can release or absorb a significant amount of latent heat during the freezing or melting process, offering a higher energy storage density. One of the main drawbacks of PCMs is their low thermal conductivity, resulting in poor thermal performance. Recent research has attempted to enhance heat transfer and increase the thermal conductivity of PCMs, including the use of metal foams. However, modeling the metal foam composite PCM using conventional methods is computationally expensive. This paper proposes an asymptotic solution for a Stefan-like problem subject to a convective boundary for outward solidification in a hollow cylinder, capable of predicting the freeze-melt cycle of the metal foam composite PCM. Specifically, three temporal regimes and four spatial layers are considered in the asymptotic analysis for each phase change process. The thermal conductivity is calculated by a theoretical three-dimensional tetrakaidecahedron model, while other thermophysical properties are obtained using the method of volume averaging. The results are verified with numerical data and validated against experimental data in the literature. The presented analytical modeling framework could have the potential to be applied to other types of composite PCMs with considerably lower computational costs compared with conventional methods.
Energy Aware Motion Planning for Underwater Gliders With Energy Harvesting Capabilities
Authors: Ordonez Camilo , Boylan Jonathan , Duval Samuel , Bradley Sara , Molnar Patrick , Nanclares Camilo , Johnson Michael , Osorio Julian , Ordonez Juan C. 
Published: February 2024

Abstract
This paper presents design, modeling, and simulation considerations for an underwater glider. The design section covers strategies for buoyancy control, packaging of electronics, and placement and integration of energy harvesting systems. The modeling efforts covers the glider dynamics and the energy harvesting, which relies on use of solar energy, phase changing materials, and thermoelectric units. The dynamics and energy harvesting models are integrated to a motion planning algorithm that uses a Sampling-Based Model Predictive Optimization approach to plan glider’s trajectories that satisfy imposed constraints and generate optimal trajectories. The power requirements for the missions considered are within the power generation range of the thermoelectric units.
Design and Development of ARDEL (Active-Assist Rehabilitation Device for Elbow)
Authors: Desai Shubhankar , Piovesan Davide , Dagli Chaitali 
Published: February 2024

Abstract
The paper presents a proposed design for an Active-assist Rehabilitation Device for Elbow (ARDEL) to increase elbow joint mobility in patients suffering from medical conditions such as stroke, lateral epicondylitis, and medial epicondylitis. The article highlights the importance of early rehabilitation intervention for stroke survivors to prevent permanent disabilities and deformities. The effectiveness of various elbow rehabilitation devices, including dynamic elbow braces, customized elbow braces, and robotic exoskeletons, has been discussed based on previous studies. The proposed ARDEL design is aimed at addressing the supervision requirement in active-assist exercises, which is widely used by therapists for elbow rehabilitation. The design uses a 3-D printed brace, which allows the patients to perform active-assist exercises with the assistance of the device. The article emphasizes the cost-effectiveness of the proposed design and its potential for widespread accessibility. The proposed design has the potential to improve the quality of life of patients suffering from elbow joint-related medical conditions.
Modeling Running via Optimal Control for Shoe Design
Authors: Fay Sarah C. , Hosoi A. E. 
Published: February 2024

Abstract
Shoe manufacturing technology is advancing faster than new shoe designs can viably be evaluated in human subject trials. To aid in the design process, this paper presents a model for estimating how new shoe properties will affect runner performance. This model assumes runners choose their gaits to optimize an intrinsic, unknown objective function. To learn this objective function, a simple two-dimensional mechanical model of runners was used to predict their gaits under different objectives, and the resulting gaits were compared to data from real running trials. The most realistic model gaits, i.e. the ones that best matched the data, were obtained when the model runners minimized the impulse they experience from the ground as well as the mechanical work done by their leg muscles. Using this objective function, the gait and thus performance of running under different shoe conditions can be predicted. The simple model is sufficiently sensitive to predict the difference in performance of shoes with disruptive designs but cannot distinguish between existing shoes whose properties are fairly similar. This model therefore is a viable tool for coarse-grain exploration of the design space and identifying promising behaviors of truly novel shoe materials and designs.
Detailed Engineering of the Automation of a Test Bench for Drilling Fluids and Cuttings Transport of Ecopetrol – ICP
Authors: Santiago Álvarez Julio Cesar , Jerez Pérez Samuel David , Roa Prada Sebastián , Moreno Olano Gonzalo Andres , Mantilla Hernández Hernán Dario , Saavedra Trujillo Nestor Fernando 
Published: February 2024

Abstract
During well drilling processes, the accumulation of cuttings downhole can cause several problems such as stuck pipe, increased torque, bit burnout and, most importantly, a considerable decrease in the drilling penetration rate, all leading to prolonged operating periods and increasing costs of up to 10% of the forecasted budget. Therefore, it is necessary to study, in a controlled environment, the behavior of the variables involved in the drilling process in order to improve the efficiency the operations involved.
The Instituto Colombiano del Petróleo, ICP, fluids and drilling cuttings transport test bench is composed of different systems, in which tests are carried out to simulate the behavior of fluid and drilling cuttings transport in different stages of the process of creating a well for oil extraction. Automation is key to achieve any efficiency improvement goal. This test bench lacks the automation systems needed to monitor and control of the variables involved in the process. Due to this, ICP has considered initiating the development of a project to automate the drilling fluids test bench, in order to perform a series of different tests autonomously, with the possibility of remote controlling and monitoring the operation of the test bench, in addition to achieve greater efficiency and traceability in data collection.
This work shows an early stage that involves the detailed engineering of automation and redesign of the existing system for the incorporation of rock cuttings into the hydraulic circuit of the test bench, which currently presents malfunctions. This is done through a sequential stages methodology which includes phases such as identification, definition, and investigation of the different subsystems that make up the test bench and their functioning, followed by the proposal, selection, and validation by means of Computational Fluid Dynamics, CFD, simulation of the redesign of the cuttings incorporation system to solve the current backflow failure. Once this stage is completed, the selection and documentation of the necessary instrumentation (actuators, sensors, and electronic control equipment) for the automation of the test bench is carried out through decision-making tools such as Quality Function Deployment, QFD, matrices. Then, the design, programming, and simulation in a virtual environment of the strategies for controlling the physical variables of the test bench and the Human-Machine Interface are developed, followed by the testing and integration of the entire solution. Thus, the detailed engineering stage of the project is concluded, obtaining all the necessary information and documentation to begin the implementation of the equipment for the automation of the Instituto Colombiano del Petróleo, ICP, fluids and drilling cuttings transport test bench.
Computational Study of Transport Phenomena Within a Poultry Incubator
Authors: Fernandes Melvy , Burgreen Greg , Drewry Jessica , Bhushan Shanti 
Published: February 2024

Abstract
The quality of hatchery conditions has a crucial impact on the health of hatched chicks. An insight into the spatiotemporal distribution of environmental factors like temperature, humidity, ventilation, and gas concentration within an incubator can be the key to reduce the risk of pathogen spread. Computational fluid dynamics (CFD) has the potential to provide a better understanding of such complex biological systems. The objective of this study is to create a computational model of the hatcher incubator by using Ansys Fluent software. The goal is to predict the spatiotemporal gradients such as temperature, velocity, and concentration of key species like water vapor (WV) and carbon dioxide (CO2), through transient simulations, assuming egg tray to be fixed. The preliminary results show non-uniform temperature and humidity distribution due to egg and tray obstructions affecting the airflow. The temperature between the eggs in a large incubator depends on proximity to the inlet, fan and the heat exchange between the eggs and the microenvironment. A parametric study is performed to understand the accumulation of moisture and CO2 depending on the fan speed, and to identify computationally cheaper numerical models for fan to reduce computational cost and allow long time simulations. Investigation of varying fan speeds (0–375 rpm) revealed higher fan speeds enhanced flow mixing and scalar variable distribution, emphasizing the significance of meticulous fan speed selection for creating an ideal incubation environment. MRF technique emerged as a cost effective alternative with 60% reduction in computational cost and its potential to allow larger time step establish them as the optimal blade modeling approach for future extended duration simulations.