bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Effect of Packing Fraction on the Thermal Performance of Shell-and-Tube-Based Latent Heat Energy Storage Systems
Authors: Soanker Abhinay , Oztekin Alparslan 
Published: February 2024

Abstract
This study examines the effect of packing fraction on shell- and tube-based latent heat energy storage units. To determine the performance of these systems, a three-dimensional transient numerical analysis has been carried out using Ansys, Fluent. This study address flow, heat transfer, melting, and solidification processes. The K-Omega SST model has accounted for turbulent flow regimes in the heat transfer fluid (HTF) and the phase-changing material (PCM). The HTF’s inlet temperature was set at 495K during the charging cycle, while it was set at 285K during the discharging cycle. A velocity boundary condition has been applied at the HTF inlet, with a Reynolds number of 5,000 considered. Furthermore, a symmetric boundary condition has been applied at the outer boundaries of the PCM to reduce the size of the shell and tube system.
The packing fraction values of 0.1, 0.2, 0.3, and 0.4 were considered while maintaining a constant volume of PCM across all cases. The performance characteristics, such as melting and solidification rates, total energy stored and discharged, and average PCM temperature, were analyzed. Although all four cases stored similar amounts of energy, the packing fraction 0.3 exhibited slightly higher thermal energy absorption at the end of the charging cycle, about 8.2% more than the 0.1 packing fraction. The packing fraction 0.4 demonstrated the fastest melting and solidification rates and the highest energy absorption and discharge rates at any given time. Meanwhile, the packing fraction 0.1 had a lower energy absorption rate but remained more consistent throughout the charging cycle when compared to higher packing cases.
Hollow Fiber Vacuum Membrane Distillation Modules With Cross-Flow and Parallel Flow Arrangements
Authors: Caspar Justin , Xue Guanyang , Asiri Mohammed , Oztekin Alparslan 
Published: February 2024

Abstract
2D Large Eddy Simulations (LES) were run to characterize the effect of a cross-flow configuration versus the same cross-section in parallel flow for hollow fibers with a packing fraction of 50%, Reynolds number 500, for vacuum membrane distillation modules. The enhanced nature of vortex shedding and flow separation was able to effectively mitigate temperature polarization in cross-flow in both the axial and radial directions. The flow remained attached to the fibers in the parallel configuration, leading to thick thermal and concentration boundary layers corresponding to high polarization. In the parallel configuration, there was 2% radial distribution in the flux, showing a near-uniform boundary layer thickness. In the cross-flow configuration, the radial distribution varied in time based on the transient nature of vortex shedding. The shedding mitigated radial temperature polarization by reducing the boundary layer thickness and mixing more thermal energy that would normally exit the module via the bulk solution back into the zone near the membrane, improving axial polarization. For a module length of 40mm, corresponding to 30 rows of packed fibers, there was a 50% improvement in the flux performance switching from parallel to cross-flow.
Design Optimization of Additively Manufactured Components Using Simulation-Based Analysis of Infill Structures
Authors: Asami Karim , Roth Sebastian , Krukenberg Michel , Emmelmann Claus 
Published: February 2024

Abstract
Additive manufacturing (AM) has revolutionized the manufacturing industry, allowing the production of complex, lightweight components with specific properties. This has created opportunities for customized parts with optimized performance and cost-efficiency compared to traditional manufacturing.
Infill structures are used to fill the voids inside the component during layer-by-layer manufacturing. These structures, such as grids and honeycombs, optimize mechanical properties, reduce weight, and save production time. However, investigating the mechanical properties of components with different infill structures is typically done experimentally, which is time-consuming and expensive.
This paper proposes a simulation-based approach to investigate the influence of infill structure parameters on the mechanical properties of components made from AISI 316L stainless steel. Two-dimensional grid and honeycomb infill structures are studied, considering infill degree, cell wall thickness and spatial orientation relative to the load direction. The study employs a parametric design approach to generate different infill structures for simulation and validation.
This paper provides a simulation-based methodology for varying and evaluating design parameters for AM processes using grid and honeycomb infill structures. The findings can be used to optimize lightweight component design for specific applications, improving performance and cost-efficiency. The study contributes to the field of Design for Additive Manufacturing (DfAM).
A Computational Study on Adaptive Multiobjective Optimization of Blowout Preventer Valve System
Authors: Song Fei , Caekebeke Laurent , Jagadesan Prabhu , Li Ke 
Published: February 2024

Abstract
A blowout preventer (BOP) is a large valve that acts as a critical well control unit against oil, gas, and water overflow and well blowout. The BOP valve body assembly contains the main pressure-containing parts. For example, in deepwater or coiled tubing drilling operations for oil and gas, the BOP can be subjected to sustained high pressure cycles. These cycles may cause the concentration of stresses in some regions, which could result in cracks or fatigue damage. Once the BOP fails during the emergency shut-in process, a blowout accident can occur, which may lead to casualties and major economic losses. To ensure the structural integrity under service loads, the BOP valve body should be designed to fulfill the stress requirements as defined by the American Petroleum Institute (API) Specification 16A, 17G and ASME (American Society of Mechanical Engineers) Boiler and Pressure Vessel Code Section VIII, Division 2. It is necessary to ensure that the BOP valve can safely withstand the working pressure. However, overengineering the BOP design is undesirable as well in terms of value engineering because it wastes both time and money. Therefore, there is a strong need to efficiently explore the full design space and identify the optimal solution that results in a compromise between the competing objectives under the constraints for the BOP valve design.
In this paper, a methodology is presented for integrating computer-aided design (CAD) nonlinear finite element analysis (FEA), and optimization package to enable adaptive multiobjective optimization and virtual verification and validation (V&V) for the BOP valve system. The BOP valve assembly is parameterized before being imported into an FEA solver. The FEA workflow is automated such that once a set of geometric parameters are given, the preprocessing, solving, and postprocessing steps can be completed automatically. Based on the automated FEA workflow with advanced optimizer (adaptive metamodel of optimal prognosis (AMOP) in Ansys™ OptiSLang), the BOP valve body design space is efficiently explored. The Pareto-optimal design points with respect to two completing design objectives on structural integrity and weight reduction are discovered. This process had never been done in the past. The optimal design set recommended from the optimization algorithm is finally sent to the three-dimensional nonlinear FEA solver for virtual V&V per the API Spec and ASME code compliance. The automated design optimization approach demonstrated in this paper could considerably enhance the product performance and reliability and, in the meantime, minimize product development cost.
Intelligent Facade Innovation (IFI): Using IIoT, Digital Twin, and Next-Gen Architecture Designs
Authors: Salamaga Diana , Guerra-Zubiaga David A. , Voicu Razvan Cristian 
Published: February 2024

Abstract
This paper explores a new methodology for integrating Internet of Things (IoT) on smart facades and implementing the digital twin concept in kinetic facades to advance the field of intelligent buildings and sustainable lean architecture. Advancements in climate-responsive building skins and analysis of the automatically adjustable kinetic facade with real-time solar tracking devices, temperature, humidity, occupancy, and air quality sensors are discussed in this article. While several papers have explored the implementation of Industry 4.0 trends on intelligent buildings, limited research has been conducted on the integration of IoT on smart facades and the implementation of digital twin concept. This research project aims to fill this gap by investigating the value of integrating IoT on smart facades and implementing the digital twin concept on kinetic facades. This research project contributes to the ongoing efforts to create a more sustainable and efficient built environment. This research will be valuable to researchers, architects, and engineers interested in advancing the field of next-generation architecture designs and principles.
Unmanned Aerial Vehicles (UAVs) in Smart Factories: Exploring the Potential for Energy Savings Through Wireless Communication Technologies
Authors: Hantouli Fadi , Guerra-Zubiaga David A. , Esmaeili Amin , Chakravarty Sumit , Perry LaShaundra , Forsberg Paul , Richards Gershom 
Published: February 2024

Abstract
The rise of Industry 4.0 and the increased use of intelligent technologies in factories has resulted in better automation and improved efficiency. Smart factories are using Unmanned Aerial Vehicles (UAVs) to achieve energy-saving objectives, but the potential of UAVs for energy savings has not been fully explored. This paper seeks to fill this gap by introducing the next generation of wireless communication technology that will be available for UAVs in smart factories. Data transmission is a critical component of smart factories, and it is essential that the wireless technology used for data transmission is reliable and flexible, so that data can be transmitted without disruption. In this article, we visualized a scenario using UAVs to inspect machine conditions in a smart factory through data collected from the UAVs and transmitted wirelessly to a station for further analysis. We discussed the importance of wireless technology in this application and compared the reliability and flexibility of a 6G network with a 5G network. We also examined how deep learning techniques can be used to improve the transmission of data further. The goal is to maximize the efficiency of the smart factory and ensure that data is transmitted.
An Adaptive Path Planning Approach for Digital Twin-Enabled Robot Arm Based on Inverse Kinematics and Deep Reinforcement Learning
Authors: Zhou Qi , Li Sikai , Qu Jingbo , Wu Jin , Xu Haomiao , Bi Youyi 
Published: February 2024

Abstract
Efficient path planning methods for robot arms are crucial to ensure the quality and safety of their completing various tasks. Compared to traditional manual instruction, Reinforcement Learning (RL) based path planning methods show better adaptability for complex working scenarios. However, the training of RL is usually time-consuming with limited success rate. To tackle this problem, we propose an adaptive path planning approach for robot arm based on Inverse Kinematics (IK) and Deep Reinforcement Learning (DRL) in a pick-and-place context. A judgement mechanism is developed to adaptively select IK or RL based method according to the results of early-stage collision detection. We separate the pick and place task into three sequential curriculums (approaching, grabbing and placing) with modified reward functions to speed up the training process and achieve a higher success rate. The proposed approach is validated with a physical robot arm supported by a high-fidelity digital twin model. The experiment results show that our proposed approach outperforms traditional RL based method with improved training speed and guaranteed performance in collision avoidance and path accuracy. This work contributes to the practical deployment of RL based path planning method for digital twin-enabled robot arm in smart manufacturing.
Simulation and Validation of Material Handling and Packaging Processes Using Vision-Guided Virtual and Physical Robots
Authors: Mascaro Seth , Mueninghoff Alexander , Chauhan Vedang , Guerra-Zubiaga David A. 
Published: February 2024

Abstract
Due to a shortage of labor, there has been a significant increase in the demand for automation and robotics in recent times. Industry 4.0 is heavily reliant on utilizing these robots to automate various processes in manufacturing to improve efficiency and reduce costs. The goal of this research is to implement automated product handling and packing using both virtual and physical robots and evaluate the performance of the system. The principal scope of this work is to automate the product handling and packaging process for a pharmaceutical company that produces pipets, thereby reducing labor expenses and enhancing operational efficiency. Additionally, this technology has the potential to transform the manufacturing industry by decreasing the need for human labor, improving product quality, and minimizing the risk of errors or contamination. The novelty of this research lies in the utilization of ROBOGUIDE simulation software to create and optimize a virtual workcell, along with a machine vision inspection system that identifies and locates products. The physical workcell is then constructed based on the simulation data, and the performance of the robot is validated using the results obtained from the physical robot. The robots’ performances are reported in terms of the cycle time and vision classification scores. Implementing automated product handling and packaging using virtual and physical robots is a promising technology that can enhance the efficiency, quality, and cost-effectiveness of the manufacturing industry.
Cryogenic Analysis Measuring Thermal Expansion Coefficient of Silicon Nitride and Sapphire via the Strain Gauge Method and Computational System Coupling
Authors: Lovelace Kirsten , Davis Ruth , Smith Sonya T. 
Published: February 2024

Abstract
Microchip reliability issues can be caused by mismatches in coefficients of thermal expansion (CTE) which can be mitigated by selecting materials with lower thermal expansion values. The strain gauge method was utilized to develop a simple thermal expansion measurement system. The objective of this research is to evaluate the coefficient of thermal expansion of sapphire and silicon nitride within the cryogenic temperature range of 299 K-4 K, as alternative options for substrate and printed circuit board (PCB) materials within integrated circuitry. This research focuses on validating experimental results with computational modeling at the liquid nitrogen temperature range of 77K and a brief overview of the mean CTE data at 4K.
Computational Verification of Analytical Modal Analysis Solution of Non-Symmetric 3RPR Parallel Kinematics Manipulator
Authors: Rosyid Abdur , El-Khasawneh Bashar , Alazzam Anas 
Published: February 2024

Abstract
The modal analysis of parallel kinematics manipulators is more complicated than that of serial kinematics manipulators due to the closed kinematic chains of the former. Using commercial finite element software, modal analysis of the manipulator should be typically set up for every single posture. Using commercial software for dynamic stiffness optimization is also less convenient than using an analytical formulation. This paper presents a verification of a proposed analytical solution by comparing it to the finite element solution. Two examples of 3RPR planar parallel kinematics manipulator were presented in the comparison. Similar to the analytical model, the finite element model uses beams to represent the manipulators’ links. First, the comparison between the analytical and finite element models was made to the individual links of the manipulator. Subsequently, the comparison was made to the assembled manipulator. Different ratios of the moving platform stiffness to the leg stiffness were used to investigate the dynamic behavior of the mechanism. It is shown that the derived analytical model for the modal analysis matches quite well with the finite element models. Furthermore, an example of dynamic stiffness optimization using the verified analytical solution was presented.
Development of an Elaborated Fuel Cell Stack Model for Drone Fuel Cell System With Liquid Cooling
Authors: Woo Jongbin , Kim Younghyeon , Yu Sangseok 
Published: February 2024

Abstract
Recently, the drone is tried to employ in the logistics industry that is known as cargo drone. Since a cargo drones requires high power density to allow large payload, hydrogen fuel cell is considered as power propulsion system for cargo drone. Typically, the fuel cell system of small drone is equipped with air cooled fuel cell system but the large payload of cargo drone requires liquid cooling fuel cell system. Since the high power density of cargo drone allows more weight for payload, the fuel cell should be operated with higher current density at the take-off. Those conditions result in serious amount of heat generation that should be maintained at reasonable set value for extended durability and high performance. Even though the liquid cooling of the fuel cells is very effective for controlling heat generation, the liquid cooling requires complicated system with heavy weight. Nonetheless, it is necessary to equip liquid cooling system as the system power requirement is large enough.
This study developed a 20kWe polymer electrolyte membrane fuel cell system model through AMESet, a model development program, and the cooling system was developed as a water cooling system in consideration of the heat generation of the stack. The cooling system consists of a water pump, a cooling fan, a radiator, and a three-way valve, and the optimal cooling strategy is derived by comparing the temperature control performance of the fuel cell system with the parasitic energy of the cooling system.
Optimization of the Design and Operation of Multi-Energy Systems Integrated With Energy Networks: Retrofit Design Problem
Authors: Dal Cin Enrico , Carraro Gianluca , Lazzaretto Andrea , Tsatsaronis George 
Published: February 2024

Abstract
In the literature there is a lack of tools able to optimize contextually the design and operation of a multi-energy system in its entirety, meaning with this both i) the number, type and size of the energy conversion and storage plants supplying the system, and ii) the geometry and capacity of the distribution networks delivering energy to the end users. Moreover, rarely the retrofit design problem is considered, meaning with “retrofit design” the addition of new capacity to components initially available in existing systems. Here, a general method is proposed to simultaneously optimize the retrofit design and operation of a multi-energy system and associated energy networks. The goal consists in finding the additional capacity to be added to already available components — energy conversion and storage plants, energy networks — and the new components to be installed, in order to comply with given reduction targets in carbon emissions, while keeping the life-cycle cost of the system at a minimum. A district composed of commercial and residential buildings operating in a microgrid is considered as a case study. Heat can be provided to the end users via a district heating network, while electricity can be either generated on site or imported from the national power grid. Results of the retrofit design problem show a contextual reduction of 35% in CO2 emission and 20% in life cycle cost with respect to the original system configuration.
Dynamic Modelling and Experimental Validation of Reaction Forces in Crane Structures
Authors: Rykkje Thorstein , Bakketun Ringheim Alexander , Willis Lundgaard Jonathan , Mezher Kenan , Øvsthus Knut , Impelluso Thomas 
Published: February 2024

Abstract
This paper presents a first-phase project toward designing a digital twin for a smart crane on a ship. Digital twin technologies create a virtual model of a physical system to simulate its behavior and aid in its operation. The long-term goal of this project is to integrate the finite element method, the multi-body dynamics method, artificial intelligence, and 3D visualization for the creation of digital twins. The short-term objective of this first phase, and the focus of this paper, is to use the moving frame method (MFM) in dynamics as a foundation for such an integration. The MFM relies on Lie group theory (distilled to the simplicity of matrix algebra) and Cartan’s notion of Moving Frames. A compact notation simplifies the kinematics. In addition to the underlying method, this paper presents a systematic and coherent way to create the frame connection matrices for multi-bodies. Then, with an appropriate restriction on the variation of the angular velocity, the MFM extracts the equations of motion using the Principle of Virtual Work. These are solved using an adaptive Runge-Kutta-4. Following this, the paper presents a systematic way to isolate each body in the linked system and solve for all contact forces (the latter in preparation for the deployment of the finite element method). The solution of the system drives a software simulation of the crane’s motion using WebGL and ThreeJS. Finally, the method and analysis is validated. A crane scale model was constructed using 3D-printed parts and electric motors for motion. Load cells were integrated into the base to measure the reaction forces. This paper reports on the first phase.
Evaluation of Fracture and Fatigue Properties of Graphene Oxide by Atomic Force Microscope and Molecular Dynamics Simulation
Authors: Sakuma Shunsuke , Nakao Yusuke , Tanaka Tomoyasu , Yonezu Akio 
Published: February 2024

Abstract
Graphene is a typical two-dimensional material and is expected to be a next-generation material for structural and functional applications, including weight reduction and miniaturization of high-tech structures and devices. However, graphene is difficult to be synthesized in large quantities, and its practical application has not been well advanced because graphene is very sensitive to defects, and defects significantly decreases its strength and fatigue life. Therefore, we focused on graphene oxide (GO), in which functional groups such as hydroxy and epoxy groups are bonded to graphene. Since GO can be synthesized in large quantities and is endowed with ductile behavior, it is expected to be used in various applications such as supercapacitors and conductive high-strength composite materials. Since these devices are subjected to repeated loading and deformation in the process of use, it is very important to know the fracture and fatigue properties of GO. However, there are very few studies on the fracture and fatigue properties of GO. Therefore, this study evaluated the fracture and fatigue properties of GO using Atomic Force Microscope (AFM) experiments and molecular dynamics, and investigated the mechanisms of fracture and fatigue damage.