bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quadcopter Control Using Single Network Adaptive Critics
Authors: Velazquez Alberto , Xu Lei , Sardarmehni Tohid 
Published: February 2023

Abstract
In this paper, optimal tracking control is found for an input-affine nonlinear quadcopter using Single Network Adaptive Critics (SNAC). The quadcopter dynamics consists of twelve states and four controls. The states are defined using two related reference frames: the earth frame, which describes the position and angles, and the body frame, which describes the linear and angular velocities. The quadcopter has six outputs and four controls, so it is an underactuated nonlinear system. The optimal control for the system is derived by solving a discrete-time recursive Hamilton-Jacobi-Bellman equation using a linear in-parameter neural network. The neural network is trained to find a mapping between a target costate vector and the current states. The network’s weights are iteratively trained using the least-squares approximation method until the maximum number of iterations or convergence is reached, and training begins at the final time and proceeds backward to the initial time. The trained neural controller applies online optimal feedback control that tracks a trajectory, minimizes control effort, and satisfies the optimality condition. The SNAC method provides a controller that can handle all initial conditions within the domain of training and all times less than the training’s final time.
Performance Advantage Evaluation of Air-Oil Heat Exchanger Based on Variable Cycle Engine in Flight Mission
Authors: Huang Congcong , Xu Guoqiang , Wen Jie , Li Mengchen , Zhuang Laihe 
Published: February 2023

Abstract
Adding an air-oil heat exchanger to the aero-engine is beneficial to improve the cooling quality of turbine cooling air, while its influence mechanism during the whole flight envelope is still ambiguous. This paper evaluates the performance advantages of the air-oil heat exchanger by building a comprehensive performance simulation model integrating variable cycle engine (VCE), air-oil heat exchanger, and blade temperature evaluation model. The results show, based on typical flight tasks: adding a heat exchanger without changing the cycle parameters reduces the engine’s overall performance, but the blade thermal environment improves, and the temperature drop of the cooling air can reach 45–214K under various operating conditions. Adding a heat exchanger and adjusting bleed air ratio or turbine inlet temperature can increase thrust obviously. For these two parameters, adjusting turbine inlet temperature can gain more enhancement in aeroengine performance. The increase in thrust is no less than 15% in take-off, climbing, and air combat conditions when high thrust is needed, effectively improving the climbing rate, service limit, and maneuverability of the assembled aircraft. Based on the flight envelope: the influence of flight environment on the two modes of VCE is consistent, the cooling air temperature and blade surface temperature are higher in the high-Ma region. Moreover, from the perspective of the engine’s internal thermal environment, double bypass mode is more suitable in low-altitude and low-speed regions, while single bypass mode is more fit in high-altitude and high-speed regions. Furthermore, the heat exchanger can effectively improve the thermal environment of hot-end components in the high-Ma region, ensuring the engine runs in safe conditions. In conclusion, this study points out the performance advantages of air-oil heat exchangers on VCE, which could help solve thermal problems in future advanced engines.
A Sequential Structural Optimization Framework to Design Compliant Constant Force Mechanisms
Authors: Ou Haihua , Johnson Shane 
Published: February 2023

Abstract
Compliant constant force mechanisms (CFMs) output a constant force over a large range of displacement input and offer tremendous energy storage compared to mechanisms/material with linear or hardening responses. In this study, we present a graph-based sequential structural optimization framework to design CFMs with high energy storage capacity. In the framework, the constant force behavior with a zero preload is defined to be ideal, as this behavior offers the maximum energy storage given a force and displacement limit. A graph-based topology selection, followed by shape optimization is conducted to select designs with energy storage most similar to the energy of the ideal constant force relation. During the graph-based topology selection, the possible topologies are exhaustively listed, and then ranked based on their performance in energy storage capacity. The better performing topologies are selected as the initial shape of the following shape optimization. We present two design cases obtained from this framework. The obtained CFM designs through this framework has a higher energy similarity index compared to typical designs from literature (0.95 vs. 0.90) and they are experimentally validated. The constant force mechanisms developed through this study can be further applied in different robot/human-environment interfaces that benefit from both mitigating impact force and increasing energy storage.
Experimental and Numerical Investigation of the Influence of Crack Front Orientation in Mode 1 Plane Strain Fracture Toughness of a Vero Material System via Poly Jet Additive Manufacturing
Authors: Khapper Vishwanath , Mohan Ram V. 
Published: February 2023

Abstract
Polyjet printing, a multi-jet Additive Manufacturing technique, has been used to fabricate 3-Dimensional structures for various polymeric material systems. This technique uses a layer-by-layer deposition method and allows for the fabrication of parts with different material compositions and varying thermomechanical properties. The current research investigates the influence of process-induced variation on Mode 1(K1C) fracture toughness of the Vero material system. Compact Tension (C-T) specimens with crack fronts parallel and perpendicular to the print direction were fabricated. The orientation of the crack front relative to the print and build directions influenced the Mode I fracture toughness values. When the crack front was parallel to the print plane, K1C decreased by 49.54%, G1C decreased by 41.56%, and peak load intensity decreased by 52.76% compared to the perpendicular crack front orientation. C-T samples were modeled in CAD to correlate with the experimental results and then analyzed in the Ansys workbench. The FEA yielded a Mode 1 fracture toughness value of 2.48 MPa m0.5 for a perpendicular configuration of the crack front and a fracture toughness value of 1.15 MPa m0.5 for a parallel configuration of the crack front. The Representative Volume Element method is used for a composite containing the Vero material system as a matrix and carbon nanofibers as reinforcement. Carbon nanofibers are integrated using a customized material configuration, and their influence on fracture is studied. A tailored network perpendicular to the crack front in a 3D printed C-T specimen stiffens the specimen. In contrast, a tailored network parallel to the crack front has a relaxing impact, indicating that an additively created part may be prone to softening under certain conditions.
Creasing Damage Analysis in Corrugated Packages Using Beam Lattice Models With Joints Stiffness Degradation
Authors: Tahir Saad , Qaiser Zeeshan , Ou Haihua , Ur Rehman Tanzeel , Johnson Shane 
Published: February 2023

Abstract
Corrugated packages are widely used for the distribution and storage of consumer goods. These containers experience high compressive forces in stacking, and the boxes fail due to buckling and creasing in the panels. Crease lines increase the consumer product rejections as the product is thought to be damaged with the package. With increased online shopping, these problems result in higher monetary losses for the companies and increased material waste. Lattice modeling, a method to represent continuums using beams or springs, provides new opportunities to describe post-buckling creases via beam joint stiffness reduction. This may be accomplished by inducing moment releases at the lattice joints upon failure. Lattice modeling has been used to model orthotropic material properties, but not to model nonlinear orthotropic behavior or creasing. The goal is to develop a modeling method to predict the creasing failure modes and the applied force magnitudes at the onset of creasing damage for corrugated paper packages with nonlinear orthotropic properties. This manuscript modifies the analytical beam-lattice models from literature to describe nonlinear (bi-linear) orthotropic paper, and analyze corrugated board lattices via classical lamination theory. The research employs an adjusted transformed cross-section method to represent the liners and homogenized fluting. To model failure, the computational framework replaces the original rotational constraints between beams with rigid connector elements, and reduces the lattice joint rotational stiffness to zero based on a pre-defined critical connector moment or critical stress criteria. The critical stress for failure is obtained by capturing crease line formation during non-standard edge compression tests (ECTs) in the container’s loading direction. The model is then validated via box compression tests (BCTs) of regular slotted containers (RSCs). The lattice model predicts the crease lines origin and progression as well as an accurate peak BCT load. The proposed framework may be used to alter corrugated box design to reduce failures and hence the consumer rejections. This will help lower the related financial losses and address sustainability concerns.
Prediction of Porosity and its Mechanisms in Metal Additive Manufacturing
Authors: Mohan Ram V. , Ingle Nikhil 
Published: February 2023

Abstract
Selective Laser Melting (SLM) is an up-and-coming additive manufacturing technique that uses a laser as the power source and is specially developed for 3D Printing metal alloys. SLM advancement is significant since it can create custom property parts, reduce material usage and design freedom, and quickly manufacture complex components.
The high energy density of laser generates various unwanted structural defects such as keyholes and porosity, which results in crack formation & distortion, and subsequent reduction in mechanical strength of the components.
The present work aims to simulate the relevant physical configurations of the SLM process and identify process parameters and the effect of metal powder variation. A representative model based on Molecular Dynamics (MD) is developed to explore the sintering mechanism of metal powders. Open-source code LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator) has been used to develop a working model to emulate a powder bed consisting of metal particles. The melting phenomenon is simulated by the heating layer of the metal particle bed. The results from this study will be able to predict the onset mechanism of porosity better and crack formation in Metal 3D printed parts.
Heat Transfer in Microchannel Heat Exchanger With Enhanced Surface Structure
Authors: Alnaimat Fadi , Mathew Bobby , Al Nuaimi Saeed 
Published: February 2023

Abstract
A simulation-based study is carried out on a counter-flow minichannel heat exchangers with smooth and staggered pinfins. The heat exchangers consist of two layers of hot and cold fluids. Each layer contained 10 minichannels with width of 2 mm and length of 100 mm; the height of the minichannel is 2 mm and the spacing between each minichannel is 0.5 mm. The heat exchanger is studied with water-water fluids. The investigation is carried out for different Reynolds numbers between 150 and 2000. The effectiveness is determined using the inlet and outlet temperatures of the fluids. Based on the investigation, it is observed that increasing Reynolds number decreases the effectiveness, and increases the overall heat transfer coefficient. It is also observed increasing Reynolds number decreases the friction factor. It was clearly observed that the heat transfer rate is higher for pin-fin minichannel compared to smooth channel. It is also noted that overall friction factor in pin-fin minichannel is higher than that in smooth channel.
Long Short-Term Memory Neural Networks for Predicting Dynamic Response of Structures of High Complexities
Authors: Liao Yabin , Poudel Biswas , Kumar Priyanshu , Sensemier Mark 
Published: February 2023

Abstract
This paper presents an initial investigation on the feasibility of modeling structural dynamics of complex structures using the Long Short-Time Memory (LSTM) deep learning neural networks, and predicting the structures’ vibration responses due to random excitation. LSTM networks are applied to the responses of various simulated systems subjected to random excitation loads, including mass-spring-damper systems with linear or nonlinear Duffing springs, a cantilever beam, and a tapered, cambered wing structure. Given a known force input, the dynamic response of the system is simulated in Matlab or ANSYS, which is used to train the LSTM model. In the case of mass-spring-damper and beam systems, the excellent agreement between the test and LSTM-predicted responses demonstrates the potential of the LSTM method for predicting vibration responses. In the case of cambered wing structure, the LSTM shows difficulties in dealing with responses consisting of multiple modes. Parametric studies are also performed to discover possible means for performance improvement. The studied learning parameters include the number of hidden units, the number of LSTM layers, and the size of train data. It is found that all these parameters have significant impact on the model accuracy. While it is always beneficial to have as much and there could be an optimal setting for the number of is not determined by the studies, they provide valuable directions to.
Relevant Aspects to Generate Reliable Simulations of Boiling Heat Transfer
Authors: Perez-Raya Isaac 
Published: February 2023

Abstract
Numerical simulations play a primary role in the understanding of multiphase flows with heat and mass transfer. The augment in computational studies comes from more accessible computer resources in terms of cost and performance. Another critical factor enabling computer simulations is the proposal of effective and easy-to-implement methods to capture the various multiphase physics, which leads to simulations resembling experimental trends. Despite relevant advances in computer modeling, an effort is still needed to get to the point where the simulations help explain the mechanisms that experimental researchers are observing. The present study discusses the development of multiphase modeling with an emphasis on boiling phenomena. The work provides a fundamental understanding on the working principles and highlights the relevance and weaknesses of its application in multiphase modeling. In addition, the study describes ways to validate simulations of multiphase flows with heat and mass transfer. Validating techniques compare simulation results against planar interface evaporation (Stefan type problems) and spherical bubble growth. Implications of numerical validation in the generated simulation results (heat transfer distribution, fluid dynamic behavior, and bubble growth rate) are discussed by analyzing simulation results of validated models. Moreover, the study outlines how validated simulations can accurately predict the performance of boiling systems.
Alignment of Nanomaterials in Hydrogels by Using Standing Surface Acoustic Wave-Enable
Authors: Li Jiali , Bo Luyu , Li Teng , Tian Zhenhua 
Published: February 2023

Abstract
Particle manipulation and patterning have gained tremendous attention in chemical, biomedical, and manufacturing studies. Hydrogels are usually used for applications in soft robots, biosensing, as well as tissue engineering. In this study, we investigated a nanoparticle manipulation method based on standing surface acoustic waves (SAWs). The SAW device consists of a piezoelectric lithium niobate (LiNbO3) substrate with a pair of interdigital transducers (IDTs). Finite element simulations were performed to understand the mechanisms of the SAW device as well as reveal the acoustic pressure field and electric potential field generated by the device. In addition to numerical studies, proof-of-concept experiments were performed by using a fabricated SAW device for patterning both silicon dioxide (SiO2) nanoparticles and multi-walled carbon nanotubes (MWCNTs) in a hydrogel solution.
Analysis of a Stationary Bicycle
Authors: Truhn Ryan , Saboori Parisa , Walker Graham 
Published: February 2023

Abstract
Cycling is one of the most popular forms of exercise with most gyms and even homes having a stationary bicycle. Cycling is a form of low impact activity which means it results in low resultant forces to the legs and knees when compared to other exercises (running, jumping, etc.). However, overusing and misusing a bicycle can cause a cyclist to have more severe joint stress and increased knee pain. Therefore, this study looks at the affect that changing the dimensions of a bicycle has on the forces at the knees and quadriceps during cycling. The scope of the stationary bicycle was chosen for this research due to its simplistic geometric adjustments and controlled environment. The goal of this study is to determine the most optimal dimensions of the bicycle to reduce knee forces while allowing the same amount of effectiveness of the exercise. To do this a parametric leg and bicycle system was modeled in Siemens NX with a driver at the pedal to create the cycling motion. Motion analysis was then run and the resultant forces were then analyzed at the knee joint and a linear slider representing the quadricep. Three total experiments were run with varying methodologies. The analysis of each method showed that any alteration to the dimensions of the bicycle changed the reaction forces at both the knee and quad. The seat height was determined to be the most influential dimension changed in the experiment as increasing the seat height increased the maximum forces at the knees for each method.
Deploying Machine Learning (ML) for Improving Reliability and Resiliency of Thermal Energy Storage (TES) Platforms by Leveraging Phase Change Materials (PCM) for Sustainability Applications and Mitigating Food-Energy-Water (FEW) Nexus
Authors: Sai Sudhir Pinjala , Ren Gangchen , Chuttar Aditya , Shettigar Nandan , Banerjee Debjyoti 
Published: February 2023

Abstract
In this paper, machine learning (ML) techniques, more specifically artificial neural networks (ANN), are utilized to enhance the efficacy of Cold Finger Technique (CFT). Experiments were conducted by melting the PCM at different values of power input to an electrical heater (mounted at the base of the container and immersed in PCM). Temperature transients were recorded by three thermocouples that were mounted at locations corresponding to liquid-meniscus heights for melt fraction values of 30%, 60% and 85%. The surface temperature transients were measured using thermocouples mounted on the exterior of the container surface that were mounted at locations corresponding to liquid-meniscus heights for melt fraction values of 30%, 60% and 90%. The surface temperature transients afford a cheap, reliable and cost-effective option for predicting the required values in real-time (i.e., the time remaining to attain a desired melt fraction, say 85%, at any particular instant during the melting cycle). These results validated the approach reported by (Chuttar et al. 2022). The average prediction error in the last half hour (before reaching a target melt fraction of 85%) was less than 10 minutes for all but one of the datasets. The Mean Absolute Percentage Error (MAPE) was as low as 11% for some of the predicted values of the datasets.
Ultrasonic Guided Waves Nondestructive Damage Detection for Square Steel Pipe Based on Semi-Analytical Finite Element Method
Authors: Yang Tingting , Zhou Wensong 
Published: February 2023

Abstract
Ultrasonic guided-wave (UGW) NDT technology is an efficient means for damage identification and has been applied widely in the field of detection for pipelines, railway tracks, ships and aircrafts. Besides, the dispersion curves of the guided waves in a square steel pipe are indispensable references for the integrity test of continuous structural components, which represent the frequency dependence of guided wave velocities. Unfortunately, the complete dispersion curve of ultrasonic waves in square steel pipes cannot be solved by the traditional finite element modal analysis method.
To address the problem, the semi-analytical finite element (SAFE) method was used to obtain the ultrasonic guided wave dispersion curves in a square steel pipe, on this basis, a UGW-based NDT strategy is proposed. Firstly, triangular elements are adopted to perform the finite element discretization on the cross-section of the square steel pipe, and the guided wave is assumed to be in a harmonic motion along the wave propagation direction. Then, the wave equation of the ultrasonic guided waves propagating in the square steel pipe is deduced theoretically, through solving the characteristic equation, the wave number and frequency can be obtained, and the relation between the frequency and phase velocity & group velocity is obtained; thus, the dispersion curves can be plotted, which can be used to analyze the vibration characteristics of the guided wave modes. Afterwards, the optimal excitation frequency, excitation direction and excitation location are selected based on dispersion property for the different damage modes of the square steel pipe. Lastly, the proposed damage identification method is validated through numerical simulation. The results show that the dispersion curves of square steel pipe solved with the semi-analytical finite element method are in good agreement with the simulated result, besides, for the damage on the square steel pipe surface, the reflected guided wave package can identify the damage location effectively under the selected excitation.
Finite Element Modeling of Football Helmet Foams to Maximize Energy Absorption Against Impacts
Authors: Honarmandi Peyman , Ceriati Andrea 
Published: February 2023

Abstract
About 3.8 million concussions occur every year in the U.S. from sports-related injuries. Studying and improving the protective gears of the head, particularly by focusing on the use of foams, would help to mitigate traumatic brain injuries. The use of closed-cell polyurethane foams is widespread in protective football helmets applications. The purpose of this research is to investigate the maximization of energy absorption under impact-loading conditions through the use of foams, maximizing their protective potential. Implementing the hyperfoam model together with the Prony series it was possible to accurately describe the nonlinear hyperelastic-viscoelastic behavior of these foams. By plotting stress-strain curves of the constitutive model it was possible to visualize and understand how constitutive model parameters influence foam behavior and to choose the optimal starting parameters to input in ABAQUS to perform impact simulations on a foam sample. Changing parameters and properties in the software it was possible to determine how the energy absorption capability of foam was influenced by them. It was concluded that this research offered a new approach to study and maximize foams energy absorption capability, acting on the constitutive model parameters and on foam properties such as thickness and density. A method to understand and visualize how these parameters influence foam behavior was also presented, as well as a strategy to perform accurate FEA of impact conditions.