bluuebunny/crossref_metadata_2025_split huggingface dataset:
Indentation Tests for Sintered Silver in Die-Attach Interconnection After Thermal Cycling
Authors: Qin Fei , Zhao Shuai , Dai Yanwei , Liu Lingyun , An Tong , Chen Pei , Gong Yanpeng 
Published: November 2021

Abstract
Thermomechanical reliability assessment for sintered silver is a crucial issue as sintered silver is a promising candidate of die-attachment materials adopted for power devices. In this paper, the nano-indentation tests are performed for sintered silver in typical die-attach interconnection under different thermal cycles. Based on thermal cycling test, the Young's modulus and hardness of sintered silver layer have been presented. It is found that the Young's modulus and hardness of sintered silver layer changes slightly although the microstructure of sintered silver also presents some variations. The stress and strain curves for different thermal cycling tests of sintered silver are also given based on reverse analysis of nano-indentation. The results show that the elastoplastic constitutive equations change significantly after thermal cycling tests, and the yielding stress decreases remarkably after 70 thermal cycles. The experimental investigation also shows that the cracking behaviors of sintered silver depend on its geometry characteristics, which implies that the possible optimization of sintered silver layer could enhance its thermomechanical performance.
A Comparative Analysis of Artificial Neural Networks for Photovoltaic Power Forecast Using Remotes and Local Measurements
Authors: Lopes Sofia M. A. , Cari Elmer P. T. , Hajimirza Shima 
Published: November 2021

Abstract
The inclusion of photovoltaic systems in distribution networks has raised the importance of the prediction of photovoltaic power for safe planning and operation. Artificial neural networks (ANNs) have been used in this task due to its capacity of representing nonlinearities. However, the profile of the data used may affect the forecast accuracy. This manuscript reports on a comparative analysis of the performance of four neural network models for photovoltaic power forecast regarding their input dataset. Four sets composed of photovoltaic power data (local measurements) and external weather data (remote measurements) were used, and the networks were validated through actual measurements from a photovoltaic micro plant. The ANN that dealt with only weather data showed a good level of accuracy, being a useful tool for the feasibility analysis of new photovoltaic projects. In addition, the approach that used only photovoltaic power data has excelled and can be used in electric sector companies.
Testing the Modified Subchannel tempa-sc Code in Comparison With Experiments and Other Computer Codes
Authors: Baisov A. M. , Churkin A. N. , Deev V. I. , Kharitonov V. S. 
Published: November 2021

Abstract
The paper describes a modified version of the tempa-sc computer program designed to calculate temperature fields in bundles of rods cooled by a supercritical pressure (SCP) fluid. This version of the program is based on the subchannel method that was used in the tempa-1f program, developed earlier in the OKB “GIDROPRESS” for calculating heat and mass transfer in the core of VVER-type reactors cooled by single-phase water at subcritical pressure. As the relations that close the system of equations of mass, momentum, and energy conservation, the new version of the program includes correlations for calculating heat transfer and friction resistance, taking into account the strong dependence of the properties of the coolant on temperature and pressure. In particular, the use of the universal calculation model of heat transfer, developed by the authors of this paper, allows us to perform calculations in a wide range of flow parameters of various fluids, including the modes of normal, improved and deteriorated heat transfer. The results of tests of the tempa-sc program are presented in comparison with the available experimental data for water and modeling fluids (carbon dioxide, freons R-12 and R-134a) at SCPs, as well as with the published data of calculations by using similar subchannel programs (cobra-sc, assert-pv) and CFD codes. A qualitative agreement between the calculated and experimental data is shown.
Subharmonic Resonance of Two Thirds Order of Electrostatically Actuated Bio-MEMS Circular Plates: Amplitude-Frequency Response
Authors: Caruntu Dumitru I. , Beatriz Julio , Alipi Marcos 
Published: November 2021

Abstract
This paper deals with subharmonic resonance of two thirds order or electrostatically activated BioMEMS circular plates. Specifically, this paper investigates the frequency amplitude response of this resonance. The system consists of a clamped flexible circular plate above a parallel electrode situated at a distance, and under an AC voltage of frequency near three fourths of the natural frequency of the plate. The method of multiple scales is used to model the hard excitations in the system, hard excitations that are necessary to produce this secondary resonance. This work predicts the response, as well as the effects of parameters such as voltage and damping on the response. This paper predicts that the subharmonic resonance of two thirds order consists of a near zero steady state amplitude, and higher values steady state amplitudes consisting of a stable branch and an unstable branch, and a saddle-node bifurcation point. The predictions regarding the effects of voltage and damping on the response of the BioMEMS plate shows that as the voltage increases, the bifurcation point is shifted to lower frequencies and lower amplitudes, while as the damping increases the bifurcation point is shifted to lower frequencies and high amplitudes. Therefore, the increase of damping leads to a case in which it is harder to reach higher amplitude steady-state solutions since it requires large initial amplitudes of the plate.
Using Physics-Informed Generative Adversarial Networks to Perform Super-Resolution for Multiphase Fluid Simulations
Authors: Li Matthew , McComb Christopher 
Published: November 2021

Abstract
Computational Fluid Dynamics (CFD) simulations are useful to the field of engineering design as they provide deep insights on product or system performance without the need to construct and test physical prototypes. However, they can be very computationally intensive to run. Machine learning methods have been shown to reconstruct high-resolution single-phase turbulent fluid flow simulations from low-resolution inputs. This offers a potential avenue towards alleviating computational cost in iterative engineering design applications. However, little work thus far has explored the application of machine learning image super-resolution methods to multiphase fluid flow (which is important for important for emerging fields such as marine hydrokinetic energy conversion). In this work, we apply a modified version of the Super-Resolution Generative Adversarial Network (SRGAN) model to a multiphase turbulent fluid flow problem, specifically to reconstruct fluid phase fraction at a higher resolution. Two models were created in this work, one with a simple physics-constrained loss function and one without, and the results are discussed and analyzed. We found that both models were able to significantly outperform non-machine learning upsampling methods and can preserve an impressive amount of detail and nuance, showing the versatility of the SRGAN model for upsampling fluid simulations. However, the difference in accuracy between the two models is quite minimal. This indicates that, for these contexts studied here, the additional complexity of a physics-informed approach may not be justified.
A Numerical and Experimental Study on the Energy Absorption Characteristics of Deployable Origami Tubes
Authors: Wo Zhongyuan , Raneses Julia M. , Filipov Evgueni T. 
Published: November 2021

Abstract
Energy absorption devices are widely used to mitigate damage from collisions and impact loads. Due to the inherent uncertainty of possible impact characteristics, passive energy absorbers with fixed mechanical properties are not capable of serving in versatile application scenarios. Here, we explore a deployable design concept where origami tubes can extend, lock, and are intended to absorb energy through crushing (buckling and plasticity). This system concept is unique because origami deployment can increase the crushing distance between two impacting bodies and can tune the energy absorption characteristics. We show that the stiffness, peak crushing force, and total energy absorption of the origami tubes all increase with the deployed state. We present numerical and experimental studies that investigate these tunable behaviors under both static and dynamic scenarios. The energy-absorbing performance of the deployed origami tubes is slightly better than conventional prismatic tubes in terms of total absorbed energy and peak force. When the origami tubes are only partially deployed, they exhibit a nearly-elastic collapse behavior, however, when they are locked in a more deployed configuration they can experience non-recoverable crushing with higher energy absorption. Parametric studies reveal that the geometric design of the tube can control the nonlinear relationship between energy absorption and deployment. This concept for deployable energy-absorbing origami tubes can enable future protective systems with on-demand properties for different impact scenarios.
A Hypergraph-Based Knowledge Representation Model for Smart Product-Service System Development
Authors: Zuoxu Wang , Xinyu Li , Chun-Hsien Chen , Pai Zheng 
Published: November 2021

Abstract
In the trend of digital servitization, manufacturing companies have been transforming their business paradigms to Smart product-service systems (Smart PSS) by integrating products and associated services as bundles. To support the knowledge-intensive process of Smart PSS development, massive domain knowledge should be well-organized and reused. However, due to the existence of non-binary relations caused by product-service bundles (PSB) and context-awareness concerns in the Smart PSS development activities, conventional graph-based approaches for knowledge representation may lose essential information in transforming non-binary relations into binary ones, and hence cause incorrect results in the subsequent knowledge queries. To mitigate this problem, a hypergraph-based knowledge representation model for Smart PSS was proposed, which represents the non-binary relations among multiple entities with hyperedges. Technically, the knowledge source and the typical hyperedge schema in Smart PSS development are identified in this paper. A detailed case study in the scenarios of 3D printing troubleshooting and PSB recommendation was conducted to showcase the proposed hypergraph-based knowledge representation model and demonstrate its validity. The results show that the hypergraph-based knowledge model significantly relieves the sparsity in the ordinary KG by adding multiple hyperedges. It is anticipated that the proposed hypergraph knowledge representation model can serve as a fundamental study for further knowledge reasoning activities.
Serial Chain of Rigid Origami That Extends, Bends and Turns
Authors: Kamijo Haruto , Tachi Tomohiro 
Published: November 2021

Abstract
This paper presents a family of serial chain mechanisms with three degrees of freedom (DOF) by concatenating rigid origami modules. This chained mechanism forms a circular arc shape and can continuously extend, bend, and turn. The mechanism keeps three-DOF regardless of the number of connected modules, and the whole motion can be controlled by determining the configuration of one module at the end. We first describe the geometric construction of the mechanism and its implementation as a rigid origami fabricated from a flat sheet. We then analyze the kinematics of the system to illustrate the configuration space and how the shapes change by manipulating the input parameters. We also synthesize the motions by numerically solving inverse kinematics of the system. We also propose novel torus mechanism with two DOF.
Enabling Artificial Intelligence Studies in Off-Road Mobility Through Physics-Based Simulation of Multi-Agent Scenarios
Authors: Young Aaron , Taves Jay , Elmquist Asher , Serban Radu , Negrut Dan , Benatti Simone , Tasora Alessandro 
Published: November 2021

Abstract
We describe a simulation environment that enables the development and testing of control policies for off-road mobility of autonomous agents. The environment is demonstrated in conjunction with the design and assessment of a reinforcement learning policy that uses sensor fusion and inter-agent communication to enable the movement of mixed convoys of human-driven and autonomous vehicles. Policies are learned on rigid terrain and are subsequently shown to transfer successfully to hard (silt-like) and soft (snow-like) deformable terrains. The enabling simulation environment is developed from the high fidelity, physics-based simulation engine Chrono. Five Chrono modules are employed herein: Chrono::Engine, Chrono::Vehicle, PyChrono, SynChrono and Chrono::Sensor. Vehicle’s are modeled using Chrono::Engine and Chrono::Vehicle and deployed on deformable terrain within the training/testing environment. Utilizing the Python interface to the C++ Chrono API called PyChrono and OpenAI Gym’s supporting infrastructure, training is conducted in a GymChrono learning environment. The GymChrono-generated policy is subsequently deployed for testing in SynChrono, a scalable, cluster-deployable multi-agent testing infrastructure built on MPI. SynChrono facilitates inter-agent communication and maintains time and space coherence between agents. A sensor modeling tool, Chrono::Sensor, supplies sensing data that is used to inform agents during the learning and inference processes. The software stack and the Chrono simulator are both open source. Relevant movies: [1].
Multi-Objective Robust Design Exploration of a Canine Ventricular Shunt for Managing Hydrocephalus
Authors: Sharma Gehendra , Nellippallil Anand Balu , Yingling Ryan , Lee Na Yeon , Shores Andy , Miralami Raheleh , Stone Tonya W. , Prabhu Raj K. 
Published: November 2021

Abstract
Hydrocephalus is characterized by the abnormal accumulation of cerebrospinal fluid (CSF) within the ventricles of the brain, resulting in an increase of intracranial pressure (ICP). Ventriculoperitoneal shunts (VPS) are designed to prevent buildup of pressure in the brain by allowing excess CSF flow from the intracranial ventricles to the peritoneal cavity through a shunting mechanism. The shunt design presented in this paper is an inexpensive alternative to VPS, that is, a non-valve ventricular shunt design that directly routes CSF into the subarachnoid space.
We recognize that consideration of multiple design criteria and uncertainty management are critical for designing biomedical devices to ensure robust performance. Hence, our objective in this paper is to present a multi-objective robust design exploration of canine shunts for managing hydrocephalus. Our approach in robust design focuses on managing uncertainties to deliver design solutions that are relatively insensitive to uncertainties. Hence, a multi-objective robust design problem is formulated using the compromise Decision Support Problem (cDSP) construct to explore shunt designs that best satisfy the conflicting goals dealing with the pressure difference and the stress, and a robust design goal dealing with the variations in pressure difference. We compare the results against optimal solutions to build confidence in the proposed method to identify design solutions that are relatively insensitive to uncertainties. The method presented is generic and can be applied to the multi-objective robust design of similar biomedical devices.
The Kinematic Analysis and Bistable Characteristics of the Winding Origami Structure
Authors: Liu Peng , Ma Jiayao , Chen Yan , Yuan Lin , Zhao Haifeng , Wang Ke 
Published: November 2021

Abstract
In the military and aerospace fields, bistable structures with adjustable or adaptive stiffness have been widely applied. Origami structures can be used to design bistable systems due to their unique geometrical characteristics. In this paper, we investigate a special design of winding origami, which consists of a square hub in the center and compactly folded panels around it. This delicate design provides the structure a bistable property. According to its motion characteristics, the folding process of the winding origami can be divided into two stages: the mechanism motion stage and the structural deformation stage. The D-H matrix method and truss transformation method were combined to analyze the kinematic relations, and the winding origami pattern was found to have one degree of freedom. At the structural deformation stage, the mechanical response and the local panel deformation were carefully studied via both experiments and finite element simulations, and a reasonable agreement was reached. It was observed that four creases exhibited a non-uniform folding pattern during the deformation process; that is, a portion of the crease was totally flattened while the rest remained folded. The origami structure’s unique kinematic and bistable features could possibly help provide some new ideas in designing a bistable system in the future.
The Development and Testing of Pour-Flush Toilet Sensors for Understanding User Interaction in Peri-Urban Households
Authors: Cotera Rivera Pablo , Bilton Amy M. 
Published: November 2021

Abstract
Rapid worldwide urbanization has created peri-urban environments that often lack services and infrastructure for water and sanitation. Globally, around 4.5 billion people do not have access to safely managed sanitation, as is often the case in such environments. Efforts to develop appropriate sanitation alternatives in these contexts recognize the value of understanding users’ preferences and interaction with their sanitation systems, however, the traditional tools for assessing technology usage and adoption are based on physical observation, which presents limitations. In this work, we developed a toilet sensor to identify usage patterns of pour-flush toilets by quantifying flushing and defecation events. The device has a methane gas sensor, IR distance sensor and a motion sensor connected to a microcontroller. Its small footprint allows for unobtrusive installation inside a toilet bowl and operates battery-powered for about 5 days depending on usage patterns. To evaluate the sensor performance, units were installed for a field trial in nine participants’ households in a Mexican peri-urban community and an algorithm for automated data analysis was developed. Surveys were also conducted to benchmark the sensor performance and determine the potential value of the approach. Results showed that on average people underreported their daily toilet usage by two events compared to the measurements and they flushed only 75% of the time after defecation. By monitoring the usage of the current pour-flush toilets lacking piped water and sewerage and complementing the data with users’ feedback, we can gain an understanding of the existing limitations so more suitable sanitation alternatives can be proposed.
Computational Design and 3D Weaving of 2D-Printable Conformal Flexible Electronics Using Harmonic Foliation Theory
Authors: Ye Qian , Guo Yang , Gu Xianfeng David , Chen Shikui 
Published: November 2021

Abstract
This paper proposes a new way of designing and fabricating conformal flexible electronics on free-form surfaces, which can generate woven flexible electronics designs conforming to free-form 3D shapes with 2D printed electronic circuits. Utilizing our recently proposed foliation-based 3D weaving techniques, we can reap unprecedented advantages in conventional 2D electronic printing. The method is based on the foliation theory in differential geometry, which divides a surface into parallel leaves. Given a surface with circuit design, we first calculate a graph-value harmonic map and then create two sets of harmonic foliations perpendicular to each other. As the circuits are processed as the texture on the surface, they are separated and attached to each leaf. The warp and weft threads are then created and manually woven to reconstruct the surface and reconnect the circuits. Notably, The circuits are printed in 2D, which uniquely differentiates the proposed method from others. Compared with costly conformal 3D electronic printing methods requiring 5-axis CNC machines, our method is more reliable, more efficient, and economical. Moreover, the Harmonic foliation theory assures smoothness and orthogonality between every pair of woven yarns, which guarantees the precision of the flexible electronics woven on the surface. The proposed method provides an alternative solution to the design and physical realization of surface electronic textiles for various applications, including wearable electronics, sheet metal craft, architectural designs, and smart woven-composite parts with conformal sensors in the automotive and aerospace industry. The performance of the proposed method is depicted using two examples.
Multi-Material Topology Optimization of Ferromagnetic Soft Robots Using Reconciled Level Set Method
Authors: Tian Jiawei , Gu Xianfeng David , Chen Shikui 
Published: November 2021

Abstract
Ferromagnetic soft materials can generate flexible mobility and changeable configurations under an external magnetic field. They are used in a wide variety of applications, such as soft robots, compliant actuators, flexible electronics, and bionic medical devices. The magnetic field enables fast and biologically safe remote control of the ferromagnetic soft material. The shape changes of ferromagnetic soft elastomers are driven by the ferromagnetic particles embedded in the matrix of a soft elastomer. The external magnetic field induces a magnetic torque on the magnetized soft material, causing it to deform. To achieve the desired motion, the soft active structure can be designed by tailoring the layouts of the ferromagnetic soft elastomers. This paper aims to optimize multi-material ferromagnetic actuators. Multi-material ferromagnetic flexible actuators are optimized for the desired kinematic performance using the reconciled level set method. This type of magnetically driven actuator can carry out more complex shape transformations by introducing ferromagnetic soft materials with more than one magnetization direction. Whereas many soft active actuators exist in the form of thin shells, the newly proposed extended level set method (X-LSM) is employed to perform conformal topology optimization of ferromagnetic soft actuators on the manifolds. The objective function comprises two sub-objective functions, one for the kinematic requirement and the other for minimal compliance. Shape sensitivity analysis is derived using the material time derivative and the adjoint variable method. Three examples are provided to demonstrate the effectiveness of the proposed framework.