bluuebunny/crossref_metadata_2025_split huggingface dataset:
Performance Analysis and Optimization of Supercritical CO2 Recompression Brayton Cycle Coupled With Organic Flash Cycle With a Two-Phase Expander
Authors: Yu Tingfang , Zhang Genli , Zhou Jiapeng , Tang Yicun 
Published: August 2024

Abstract
In this work, a combined supercritical CO2 recompression Brayton cycle (SCRBC)/organic flash cycle with a two-phase expander (OFCT) system is proposed to improve the thermal efficiency of the SCRBC, which utilizes a two-phase expander to replace the high-pressure throttling valve of a basic organic flash cycle (OFC). In addition, the OFCT is coupled at the waste heat end of the SCRBC as the bottom cycle for the use of waste heat at low temperatures. A comprehensive comparison is carried out for different organic working fluids, including the R123, R245fa, R142B, R236ea, and R600, regarding the thermal performance, environmental effect, and safety levels. Furthermore, influences of various factors on the thermal performance of the combined SCRBC/OFCT cycle are also examined, including the top cycle pressure ratio, top cycle turbine inlet temperature, mass flowrate ratio, evaporation temperature, and the condenser's pinch point temperature difference. A multi-objective optimization approach is employed on the combined SCRBC/OFCT system, which considers both the thermal efficiency and the specific investment cost as the objective function, and the optimization procedure is implemented through the nondominated sorting genetic algorithm II (NSGA-II) algorithm. The Pareto solution set and the compromise solution are finally obtained. The results indicate that the optimized combined SCRBC/OFCT system can improve the thermal efficiency by 11.75% and 9.70% when compared with the SCRBC and SCRBC/OFC, respectively.
State of Health Estimation for Lithium-Ion Batteries Based on Multi-Scale Frequency Feature and Time-Domain Feature Fusion Method
Authors: Zhao Yunji , Liu Yuchen 
Published: August 2024

Abstract
Accurately estimating the state of health (SOH) of lithium-ion batteries is important for improving battery safety performance. The single time-domain feature extraction is hard to efficiently extract discriminative features from strongly nonlinear coupled data, leading to difficulties in accurately estimating the battery SOH. To this end, this paper proposes a multi-scale frequency domain feature and time-domain feature fusion method for SOH estimation of lithium-ion batteries based on the transformer model. First, the voltage, current, temperature, and time information of the battery are extracted as time-domain features; second, the battery signal is processed by a multi-scale filter bank based on Mel-frequency cepstral coefficients (MFCCs) to obtain the multi-scale frequency-domain features; then, a parallel focusing network (PFN) is designed to fuze the time-domain features with the frequency-domain features, which yields low-coupling complementary discriminative features; finally, constructing the SOH estimation mechanism based on the transformer deep network model. The algorithm is validated by NASA and Oxford datasets, and the mean absolute error (MAE) and root-mean-square error (RMSE) are as low as 0.06% and 0.23%, respectively.
Optimization of Injection-Production Relationship of Offshore Unconsolidated Sandstone Reservoirs Based on Inter-Well Connectivity
Authors: Zhang Xinlong , Du Fengshuang , Zhao Hui , Ge Lizhen , Deng Jingfu 
Published: August 2024

Abstract
The dynamic heterogeneity of the water drive sandstone reservoir in high water cut stage is strong, which leads to the differential enrichment and distribution of the remaining oil. The adjustment of the injection-production relationship can effectively guide the work of stabilizing oil and controlling water. Based on the principle of inter-well connectivity, this paper comprehensively considers the geological characteristics and development dynamics, and constructs the multi-layer reservoir joint well network inter-well connectivity model. By integrating the automatic history matching and the real-time injection-production optimization algorithms, the accurate inversion of connectivity parameters and real-time optimization prediction of production dynamics are realized. An actual field application showed that using this method led to an annual increase in oil production by 16,000 cubic meters and a reduction in water cut by 0.87%, which significantly enhanced oil recovery and improved water control. This method can be applied to guide the adjustment of the planar injection-production structure in similar reservoirs.
Theoretical and Experimental Study of Heat Transfer in a Two-Channel Flat Plate Solar Air Collector
Authors: Álvarez Benjamin , Arce Jesús , Chávez Yvonne , Lira Leonel 
Published: August 2024

Abstract
In this article, a theoretical–experimental study was conducted on a two-channel solar air collector (SAC-2C). For the experimental study, a prototype of the SAC-2C was designed, built, and instrumented with dimensions of 1.860 m in length, 0.605 m in width, and featuring two air channels of 5.5 mm and 5 mm thick each, respectively. The collector operates via forced convection and was positioned at an inclination angle of 18.88 deg at the Tecnológico Nacional de México CENIDET campus (TecNM/CENIDET) located in Cuernavaca, Morelos, Mexico. For the theoretical analysis, the method of global energy balances in two dimensions (2D) and under transient conditions was applied. Temperature differences of up to 3.0∘C are observed with respect to mathematical models that do not consider heat conduction terms in solid elements. These differences are accentuated in the glass cover. Furthermore, altitude’s impact on air density calculations could influence theoretical temperature profiles up to 3.0∘C. The theoretical results of the numerical model were validated with the information obtained from the experimental tests, which showed good similarity. It was observed that the elements of SAC-2C are sensitive to sudden changes in meteorological conditions. The system’s response time is not only associated with the characteristics of the materials but also with the thermal bridges between the absorber plate and the casing. The calculation of the appropriate heat transfer coefficients allowed the evaluation of energy gains or losses in the SAC-2C collector.
A Novel Method for Bearing Fault Diagnosis Based on Novel Feature Sets With Machine Learning Technique
Authors: Mali Asmita R. , Shinde P. V. , Patil Amit Prakash , Salunkhe Vishal G. , Desavale R. G. , Jadhav Prashant S. 
Published: August 2024

Abstract
Bearings often experience small and medium raceway damage due to operating and loading conditions, which induces abnormal dynamic behavior. The rotor-bearing system is tested at various conditions, and the influence of each fault has been presented in this study. The fundamental bearing characteristics frequencies and statistical features withdrawn from a vibration response are utilized for fault identification using a machine learning algorithm. Extreme learning machine (ELM) and the supervised machine learning method K-nearest neighbor (KNN) network were utilized to classify vibration data collected experimentally under various operating conditions. Bearing characteristics frequencies and statistical features are applied to both proposed approaches and compared regarding their prediction quality. The result shows that the ELM has better performance over the KNN in precision of fault recognition up to 99% and thus feels promising for condition monitoring of industrial rotating machines. This work provides valuable insights for operation, maintenance, and early fault warning related to bearings.
Quenching Vibration on a Symmetric Laminated Composite Plate Excited by Multiple Harmonics Using Inerter-Based Dynamic Vibration Absorbers
Authors: Yu Jiang , Cha Philip D. , Chen Jiawang , Yu Zhefeng , Zhou Xiang 
Published: August 2024

Abstract
In this article, a simple and efficient method is developed to quench the steady-state vibration of a symmetric laminated composite rectangular plate subjected to multiple harmonics with distinct excitation frequencies. The introduction of the inerter into the traditional dynamic vibration absorber enlarges the solution space for both the feasible attachment locations and the absorber parameters. For a given set of attachment locations, when the traditional vibration absorbers yield physically unrealizable absorber parameters, i.e., negative absorber parameters, an inerter-based vibration absorber can be used such that the absorber parameters become strictly positive. Using the assumed modes method, the governing equations of the laminated composite plate carrying the inerter-based dynamic vibration absorbers are first formulated. A set of constraint equations is established by enforcing nodes at user-specified locations on the plate. Harmonic excitations consisting of a single or multiple distinct excitations are considered. In addition, two attachment scenarios are analyzed: when the attachment and node locations coincide, and when they are distinct. Numerical experiments show that the absorbers’ parameters can be readily determined for both cases, and the proposed method can effectively enforce the desired node locations when the plate is subjected to either a single or multiple harmonic excitations.
Positioning Accuracy in a Concurrent Robot-CNC Hybrid Manufacturing System
Authors: Goodwin Jesse , Kelly Kathryn , Foley Melissa , Saldana Christopher , Kurfess Thomas , Saleeby Kyle 
Published: August 2024

Abstract
Additive manufacturing (AM) has gained notoriety for offering advantages over traditional manufacturing methods, such as increased design complexity and flexibility. However, it has not found widespread use beyond rapid prototyping. One hindrance to the acceptance of AM processes in industry is the time and cost of fabrication per component. While metal AM by itself can be inexpensive, extra manufacturing steps in the form of subtractive manufacturing (SM) may need to be performed to reach final part tolerances, leading to hybrid additive-subtractive manufacturing (HASM) of a part, which increases time and cost. A potential area to reduce cost is through increasing the efficiency of the HASM process by conducting additive and subtractive manufacturing simultaneously. Usually, HASM is performed in a process where AM is completed in one machine or cell and transferred to another machine or cell for SM in a sequential assembly line process. This efficiency decreases part cost, but high aspect ratio parts or parts with internal geometry that require interleaved additive deposition and machining cannot be produced. One unexplored solution to simultaneous HASM that allows for interleaved operations is to operate the deposition head and machining spindle concurrently within the same machine envelope, known as concurrent HASM (CHASM). In this type of process, both AM and SM occur simultaneously on a batch of small parts or a single large part, maintaining a high efficiency without sacrificing the full range of complex geometries that AM allows for. A potential approach to the single-machine method could be to combine a robot and mill within the same envelope. A challenge to this approach, however, is control of both systems. Most machine controllers have limited external communication or, if a robot has been integrated, only offer movement of either the robot or mill at any given time. As a result, systems must pause either the AM or SM process to switch between them rather than working simultaneously. The present work investigates the positional accuracy of such a CHASM system comprised of a robotic arm and a 3-axis mill. Open-loop tests with limited communication between machines are performed on the system to verify positional error during concurrent robot-mill movements. Under certain conditions, it is demonstrated that position error can stay within 2 mm for the duration of a single layer; however, these tests show that, generally, the open-loop positioning performance of the system is inadequate for CHASM without part-specific hand-tuning of parameters. Based on these results, a set of requirements for successful robot-CNC CHASM is proposed for future integrations.
Investigating Nozzle Design for Cutting Fluid Supply During Inconel 718 Turning With CBN-Tools
Authors: Liu Hui , Kelliger Tobias , Meurer Markus , Bergs Thomas 
Published: August 2024

Abstract
The machining of difficult-to-cut materials, such as nickel-based alloys and high-alloy steels, is usually assisted by cutting fluid. In addition to the commonly used flood cooling, high-pressure cutting fluid supply offers great potential for further increasing tool life and process reliability. Although the positive effect of high-pressure cooling has been confirmed in a large number of studies, the relevant cutting fluid setting parameters such as nozzle cross-section area and supply pressure, and their influence on the process results have so far been insufficiently investigated. Against this background, a prototype tool holder was designed and additively manufactured in this work. The tool holder allows to vary the nozzle cross-section area without changing the cooling channels and the inclination of the nozzles. Experimental results revealed the optimal cross-section area of the rake face nozzle for the investigated process. It was also shown that although flank face cooling is necessary for the turning process, improper setting of the flank face nozzles can lead to a reduction in tool life.
Inspection on the Scratch Performance of a PVD-Coated Cemented Carbide Previously Micromachined by a Nanosecond Laser
Authors: Fang Shiqi , Salan Nuria , Guo Yuebin , Colominas Carles , Llanes Luis 
Published: August 2024

Abstract
Recently, nanosecond laser has been increasingly applied to process functional surfaces of cemented carbides in the tool industry, that have high finishing requirements for geometric precision. Coating is a common surface treatment for cemented carbides to improve their mechanical and thermal properties. In this work, micro-scratch tests were conducted on a PVD-coated cemented carbide grade, which was previously processed by a nanosecond laser. Scratch performance was evaluated and compared to the non-laser processed one in terms of their acoustic emission, penetration, and friction. Scratch tracks were inspected using SEM. The first results demonstrate that laser processing was beneficial to the scratch performance of the coated cemented carbide grade as less penetration and surface damage were induced.
Brief Paper: Quantifying Spatial Heterogeneity of Laminated Perovskite Semiconductors Using Photoluminescence Mapping
Authors: Okia Oluka , Lanaghan Clare , Palmer Jack , Yadavalli Srinivas , Fenning David , Dasgupta Neil 
Published: August 2024

Abstract
Halide perovskite solar cells (PSCs) are a state-of-the-art photovoltaic technology that exhibit high efficiencies and can be manufactured using roll-to-roll systems. However, PSCs are currently fabricated using sequential layer-by-layer deposition, which constrains the selection of suitable functional layers in the solar cell and limits the processing conditions and techniques that can be used.
Lamination via diffusion bonding is a scalable parallel-processing technique that has the capability to overcome some of the challenges of sequential deposition by widening the thermal processing window and reducing the chemical compatibility requirements for PSC manufacturing. However, there remains a lack of detailed understanding of the process-structure-property relationships needed to accelerate the development of high-volume lamination-based manufacturing processes.
In this work, we introduce a method to study the process-structure-property relationships of laminated perovskite semiconductors by using a custom photoluminescence (PL) spectroscopy system to quantify spatial heterogeneity in laminated halide perovskite (HP) materials. PL is an important figure-of-merit used to quantify the optoelectronic properties of semiconductor materials used in PV manufacturing. The spatial variation in PL of a laminated HP film is compared to that of an unlaminated HP film.
The PL system uses servomotors and an Arduino microcontroller to automate a PL mapping procedure. The PL equipment is tunable to achieve a minimum possible spot size of ∼50 μm, enabling high-resolution measurements. The system is used to measure the PL of 19 separate locations on both a laminated and unlaminated HP material.
The results of this study reveal that lamination at optimal conditions will improve the average PL peak intensity of the HP by 55%, indicating that lamination has the potential to improve the optoelectronic characteristics of PSCs. However, lamination also increases the standard deviation of PL peak intensity. Therefore, although lamination improves the PL of HPs, it also induces unwanted spatial heterogeneity. This warrants future studies on the governing physical mechanisms that determine quality control metrics in lamination-based PSC manufacturing.
Variable Friction Model Development and Implementation to the Pulling Force Prediction of the Split-Sleeve Cold Expansion Process for Aluminum 2024-T3
Authors: Hossen Md. Saddam , Westrum Jeremiah J. , Shultz Matthew , Tan Hua , Kim Dave 
Published: August 2024

Abstract
The split-sleeve cold expansion process enhances the durability of metallic structures by imparting deep compressive residual stresses around fastener holes to extend the fatigue lives of the fastened structures. This study aims to improve the accuracy of the pulling force estimation by establishing the variable friction model of the dry-lubricated split sleeve when cold working an aluminum 2024-T3 hole. The variable friction model was empirically obtained from the friction experimental setup simplified from the split-sleeve cold expansion process. The contact-pressure-dependent variable friction model was derived through a systematic design of experiments approach with three different normal stress conditions, namely low normal stress (220 MPa), medium normal stress (440 MPa), and high normal stress (660 MPa) to cover the range of normal stresses occurred in the cold expansion process. A full quadratic response surface model was drawn for the friction coefficient’s nonlinear relationship between the mandrel and the lubricated sleeve depending on the normal stresses. The variable friction model was verified with 3-dimensional friction test finite-element (FE) simulations. This FE modeling validates the variable friction model to predict the pulling forces accurately to show a sound agreement between the estimated values and the experimentally obtained values. We conducted split-sleeve cold expansion experiments with 12.7 mm thick Al 2024-T351 alloy coupons to obtain the pulling force profile. The hole size was an average of 5.746 mm and the sleeve thickness of 0.152 mm to achieve approximately 4% radial expansion. Two 3-dimensional (3D) FE numerical analyses of the same split-sleeve cold expansion process were conducted using the variable friction model and a constant frictional coefficient of 0.05. The pulling force profiles from the FE modeling with the variable friction model closely align with those from the experiments to show the four distinct regions.
Spatial Atomic Layer Deposition: Reduced Order Model Towards In-Line Process Control
Authors: Penley Daniel , Dasgupta Neil P. 
Published: August 2024

Abstract
Spatial atomic layer deposition (SALD) is a thin film deposition technique that could provide precise atomic-scale control at a large enough scale for many applications, such as clean energy technologies, catalytic conversion, batteries, and anti-fouling coatings. The spatially separated precursor zones are sequentially exposed to the substrate surface to deposit a film with precise control. If the precursor zones were to intermix during a deposition process, the precise control over film thickness would be lost. Therefore, it is essential to control the location of the precursors within the process region during a manufacturing process. This is typically achieved by controlling the gas flow rates and/or pressures, however it is challenging to actively monitor the location of the precursors during a deposition process as the process region has a small characteristic length and the vapor/gas precursors are difficult to observe/monitor. Therefore, there is a need to validate the precursor location and consequential process quality during a deposition. This can be of particular importance for substrate surfaces that are highly irregular or for manufacturing conditions where external factors such as temperature and ambient air speeds could change dynamically. In this study, a reduced order COMSOL Multiphysics® model is introduced that can predict the location of precursors in the process region. The model itself is discussed; the mesh size is selected considering accuracy and computation time; the model outputs are shown; and an initial experimental validation of the model is demonstrated.
Support-Structure Decision in 3D Printing With Unsupervised Computer Vision
Authors: Guo Shenghan , Ouidadi Hasnaa , Xu Boyang 
Published: August 2024

Abstract
In 3D printing, support-structure decisions for CAD models heavily rely on expert knowledge. Automatically evaluating CAD geometry and deciding the need for support structures remains challenging. This study adopts the Oriented Fast and Rotated BRIEF feature detector and descriptor to match geometric features among CAD models and predict support-structure decisions for printing a new CAD model. This work demonstrates the potential of automating 3D printing process planning with AI tools.
Unsupervised Anomaly Detection Using 3D Point Cloud Data for Model-Free Products
Authors: Liu Jiayu , Bird Tommy , Nagori Aadit , Samuel Johnson , Wang Yinan 
Published: August 2024

Abstract
Anomaly detection is pivotal in various industrial areas, including automotive, aircraft, and manufacturing. The primary goal of anomaly detection is to minimize human intervention while enhancing detection accuracy. Recently, researchers have achieved considerable progress in pinpointing defects using image-based techniques. However, these methods present two main challenges: (i) the detection accuracy is often influenced by various image factors such as perspective, lighting, and color variations, and (ii) some defects are subtle and challenging to discern in images. Recognizing these constraints shows a growing interest in exploiting three-dimensional (3D) point cloud data. These data offer a detailed and accurate representation of an object’s surface, promising better localization of surface defects. However, the 3D point cloud processing has its challenges. Two key issues include: (i) point cloud-based methods need to be both transformation and permutation invariant, as different transformations or permutations of the 3D point cloud can describe the same object structures, and (ii) at times, anomalies might share similar geometric features (e.g., local surface variations, etc.) with a non-defective surface, especially for objects with a complex shape, which makes it hard to distinguish the normal and abnormal surfaces in the space of geometric features. This paper introduces a novel, lightweight, unsupervised approach to detect and localize surface defects from 3D point cloud data, emulating human recognition capabilities and excelling in localization accuracy. We compare the performance of the proposed method and two classical unsupervised methods, K-means clustering based on cosine similarity between normal vectors and threshold method based on local surface variations on the real scanned dataset. The results show that our proposed method receives the best defect localization accuracy compared with baseline methods.