bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimisation of a Hydrogen-Fuelled Parametric Strut Injector Using an Automated Workflow CFD Method
Authors: Treleaven Nicholas C. W. , Fournier Guillaume J. J. , Leparoux Julien , Mercier Renaud
Published: August 2024

A strut injector for burning hydrogen has been optimised using an automated workflow system. The design process began with a parametric CAD model that allowed for various design features to be altered and various different designs to be generated from a given list of parameters. In order to choose the optimal set of injectors to cover the design space, an optimised design of experiments (DOE) method was used to automatically choose the parameters that best spanned the design space. One hundred candidate designs were chosen and a script used to generate a series of stereolithography (STL) files for each design. The STL files were then uploaded to a supercomputer for CFD analysis. For each of the 100 designs, a 4 step process was followed to generate the required data, this included a automated mesh generation step, field initialisation step, mesh adaptation step and finally an LES all within the YALES2 numerical framework. These 400 simulations were automated using an automatic workflow management process which limited the quantity of human intervention required and massively boosted productivity. In order to reduce the time required for post-processing and the amount of data required, the simulations relied heavily on a on-the-fly post-processing methodology which reduced the complex time-unsteady flow fields to a small number of quantified outputs of interest that measured the suitability of each design such as the pressure drop across the injector and the efficiency of the mixing process. At the conclusion of these simulations, automated scripts translated these outputs into a smaller set of parameters that could be used to compare each design and allow subsequent optimisation and surrogate modelling. Several surrogate modelling methods were attempted with mixed results however a simple classification methodology quickly identified the parameters of interest.
Experimental Study of Fuel Gas Leak in a Real Scale GT Enclosure
Authors: Ricco Alessandro , Lucherini Gabriele , Minotti Stefano , Azzini Francesco , Presotto Valentina , Vanghi Stefano
Published: August 2024

As part of NovaLT16 100% H2 product release, a new ventilation system was designed to achieve hydrogen dilution within the gas turbine (GT) package according to safety criteria. In this context, an experimental study of fuel gas leak in a real GT enclosure was performed to have valuable reference, due to a lack of literature experience with this kind of application.

This paper describes test bench setup and requirements to validate the ventilation design as part of NovaLT16 100% H2 test campaign. The test is representative of a typical gas leak from the fuel gas line inside the GT package leading to a target %LFL (Lower Flammability Limit) at the ventilation outlet defined according to gas detection control.

During the test, the ventilation is kept in operation while the GT is turned off to avoid any potential source of ignition. The gas leak is generated releasing natural gas into the GT package via a set of orifices with sonic flow. For safety reasons, natural gas is chosen instead of pure hydrogen, being equally indicative of a gas release phenomenon. The simulated flow rates are representative of real possible leakages that may occur due to damage to connections or flanges along the fuel supply line. Multiple gas detectors both within the package and in the ventilation outlet duct provide a visualization of the dynamic evolution of the gas cloud both in terms of concentration and location.

The test confirms the gas detection system capability to identify presence of local gas leaks preventing the occurrence of hazardous scenarios. Moreover, acquired data are employed to tune numerical models that are used to design ventilation and gas detection systems with a higher level of confidence.
Investigating the Performance of a Small Horizontal Axis Wind Turbines (HAWT) Using Toroidal Blades
Authors: Ezz Ahmed , El Baz Ahmed M. R.
Published: August 2024

Optimizing the aerodynamic design of small-scale horizontal-axis wind turbine (HAWT) blades is essential for enhancing annual energy production, performance, and efficiency. This study employs Computational Fluid Dynamics (CFD) with the ANSYS FLUENT solver to investigate the aerodynamic behavior of a newly designed multi-bladed HAWT, specifically introducing toroidal blades. The primary objectives include understanding the aerodynamics of two and three-bladed toroidal rotors, improving HAWT performance by increasing the power coefficient (Cp) and identifying the optimal looping ratio (C) for elliptic toroidal blade shape. The research involves a detailed comparison between toroidal and conventional turbine blades, utilizing Blade Element Momentum (BEM) theory and a NACA 4412 airfoil for blade sections. The geometry characteristics, such as chord length and twist, are carefully calculated along the blade. A 3D geometric domain is created and appropriately meshed for the rotor. Analysis is conducted on a model representing the rotor at a constant wind speed of 7 m/s and various Tip Speed Ratios (TSR). A parametric study for the toroidal blade focuses on the shape ratio (C), determining the optimum ratio as 0.25. The results reveal a notable 14% increase in the power coefficient (Cp) for the three-bladed toroidal blade, calculated based on the optimum TSR for both basic and toroidal blades. The findings suggest that toroidal blades can effectively enhance small HAWT performance, especially at lower TSR. Overall, this research highlights the potential of toroidal blades to improve the power coefficients of small-scale HAWTs.
Topology Optimization of Fuel Cells: an Innovative Approach for Sustainable Aviation
Authors: Casari Nicola , Di Caterino Antonio , Pietropaoli Marco
Published: August 2024

The imperative to meet COP 21 targets underscores the pressing need to reduce our dependence on fossil fuel-based technologies. Among the array of viable alternatives, hydrogen stands out as a compelling candidate, with applications spanning from ground vehicles to energy production and even the most challenging sectors to decarbonize, like aviation.

Hydrogen’s versatility and scalability render it a subject of growing interest across various industries, but the rapid market penetration of hydrogen-related solutions is hampered by some shortcomings in the performances of the applications. For instance, the current maximum efficiency of fuel cells hovers around 60%, leaving significant room for improvement.

This paper shows how topology optimization can help designers and manufacturers of fuel cells understand and improve some of the crucial features of these devices. For example, the application of topology optimization can increase the uniformity in reactant delivery, improve the cooling system and reduce the pressure losses in the manifolds. These aspects are crucial for improving the energy density of these products, increasing also their efficiency and reliability. The resulting geometries show how, with the support of topology optimization, fuel cells will be soon ready for real-world aviation applications.
Application of Machine Learning Techniques in Calibration and Data Reduction of Multi-Hole Probes
Authors: Mirhashemi Arman , Juangphanich Paht , Miki Kenji
Published: August 2024

This work presents procedures for implementing machine learning methods into existing algorithms for multi-hole probe calibration and data reduction. It demonstrates that using artificial neural networks (ANNs) can decrease the amount of calibration data needed to achieve a specific calibration uncertainty by over 50%, while also significantly reducing data reduction times. Instead of surface fitting methods, ANNs are employed. Initially, directional calibration coefficients related to flow angles are computed based on pressure measurements, and then these flow angles serve as input parameters for subsequent ANNs to iteratively define Mach number, static pressure, and total pressure. In an alternative approach, new calibration coefficients directly relate pressure measurements from the five-hole probe to the quantities of interest, thereby eliminating the need for iterative algorithms used in conventional surface fitting methods. This method offers several advantages: an average increase of less than 1% in calibration uncertainty for flow angles and a significant reduction in data reduction times to a few seconds on average. Additionally, the methodology is confirmed to avoid both over- and under-fitting.
Operation Planning for Hydrogen Co-Combustion in Combined-Cycle Power Plants
Authors: Hübel Moritz , Rohde Daniel , Gottelt Friedrich , Harper James , Pezzini Paolo , Noble David R.
Published: August 2024

Hydrogen Co-Combustion is seen as an important measure to reduce carbon dioxide emissions of gas combined-cycle power plants. Besides technical challenges, the addition of a new fuel introduces a need for more advanced economic planning, considering new and existing technical constraints as well as different types of legal incentives or constraints to reduce carbon emissions or increase hydrogen blending in gas-turbine combined cycle plants. The paper will demonstrate a gradient-based dynamic optimization routine that is applied to a natural gas-fired combined cycle power plant model with hydrogen co-combustion and real-world boundary conditions. It is used to investigate different legal boundary conditions such as reducing CO2 emission rights or prescribing minimum hydrogen-blend rates and study the effects produced energy, CO2 emissions and the operating result (EBITDA). Therefore, it provides guidance for plant operators, defining the right technological development for a given plant site, e.g. investing in increasing technical feasible hydrogen blending capabilities beyond the minimum legal requirements, planning hydrogen storage capacity for onsite production with electrolyzer or securing continuous hydrogen delivery with other methods, e.g. pipelines, tube-trailers, or ship delivery. In addition, the paper reveals how market participants will operate with variant legal boundary conditions. The findings can be used to validate suggested rules, e.g. EPA suggestion to introduce minimum hydrogen blend rates, the European emission trading systems penalizing CO2 emissions or cooperate sustainability targets enforcing CO2 reduction paths and how these will affect a plant site and resulting consequences for the electricity system.
Gas Path Fault Diagnosis Method Under Small Samples With Inter-Class Imbalance
Authors: Wang Kun , He Ai , Liu Yuan , Xiao Tingyu , Chen Zhixiong , Hu Zhongzhi
Published: August 2024

Current data-driven methods for gas path fault diagnosis in aero-engines often require extensive fault sample sets, which are challenging and expensive to obtain in practice. Additionally, even with limited samples, these methods face issues of inter-class imbalance, including imbalances in normal and fault data quantities, imbalances in the quantities of different fault classes, and imbalances in fault severity. Additionally, current methods for simulating gas path faults solely focus on the degradation of gas path component efficiency, neglecting the non-linear alterations in component characteristics caused by faults and the interconnected effects between components. Therefore, we propose to use a transfer learning-based variational autoencoder (TL-VAE) approach to generate fault samples and optimize the accuracy of gas path fault diagnosis. First, we train the VAE using normal engine operation samples. Then, by incorporating transfer learning, we retrain the VAE using a small number of fault samples by fine-tuning certain weights of VAE. This allows us to combine the operational state features from the source domain with the fault features from the target domain, fitting the distribution of the measured parameters of the faulty engine. This enables the TL-VAE to function as a generator of fault samples. Subsequent fault diagnosis strategies rely on mature classification methods and the generated samples, including Softmax and SVM classifiers. We validate the effectiveness and superiority of the proposed method through simulation. The experimental results demonstrate that the proposed method significantly improves fault diagnosis results with limited samples. Especially within the coverage of the generated samples, fault diagnosis accuracy (FDA) of the Softmax and SVM classifiers significantly improved from 73.3% and 66.5%, respectively, to a perfect 100% after employing the proposed approach. The FDA of Softmax and SVM classifiers with the proposed method is improved from 77.9% and 80.9% to 100% compared to other typical data generation methods.
A Keyphasor-Free Traveling Waves Analysis Method Based on Blade Tip Timing and Experimental Validation
Authors: Meng Yiming , Xiao Zhicheng , Chai Pengfei , Wang Shang , Zhu Xiaocheng , Ouyang Hua
Published: August 2024

Vibration-induced high-cycle fatigue of blades is a prevalent issue in turbomachinery. Blade Tip Timing (BTT) emerges as a non-intrusive, promising method for assessing blade vibration. Despite its potential, BTT’s inherent measurement limitations often result in the under-sampling of individual blade data. Assuming that the bladed-disk assembly vibrates in nodal diameter modes, traveling wave analysis (TWA) can overcome the limitations of under-sampling and identify the nodal diameter modes associated with the frequency components. Traditional TWA methods rely on a keyphasor or once-per-revolution (OPR) sensor to provide accurate reference signals. However, such a sensor could be damaged during operation or challenging to install due to limited space in field tests. In this paper, a new keyphasor-free TWA (KF-TWA) method is introduced, which is capable of measuring the order and nodal diameter of nodal diameter vibrations with as few as two sensors. Theoretical derivations reveal the method’s resilience to the steady-state displacement of blades. The feasibility and effectiveness of the KF-TWA method are validated through numerical experiments and compressor tests. In the numerical experiments, blade detuning and nodal diameter vibration responses are simulated, leading to the development of a criterion for identifying nodal diameter vibrations. A compressor test rig, equipped with a 64-keyphasor disk and a sufficient number of circumferentially distributed sensors, is designed to provide blade vibration benchmark. In the experiments, the KF-TWA method successfully identified nodal diameter vibrations with amplitudes as low as 0.014 mm, consistently yielding identical results across multiple sensor pairs, which demonstrates a higher robustness compared to the traditional TWA method. The results presented offer valuable insights into the engineering application of this technology.
High Temperature Industrial-Scale CO2 Heat Pumps: Thermodynamic Analysis and Pilot-Scale Testing
Authors: Held Timothy J. , Miller Jason D. , Mallinak Jason A. , Magyar Luke
Published: August 2024

Electrification of heat-generating processes is a key means to decarbonize industrial emissions, and heat pumps significantly improve the efficiency of electrified heat. Carbon dioxide is one of the oldest known heat pump working fluids, but its use is presently limited to low temperature (< 120 °C) applications and, when operating in a transcritical mode, for heating liquid water and similar single-phase materials. Conventional subcritical HFC or HFO refrigerants also have temperature limitations due to thermal degradation and are subject to eventual phase-out. Finally, most smaller heat pump systems use oil-lubricated positive displacement compressors, which also impose temperature limitations due to the thermal stability of the entrained oil in the refrigerant.

By taking advantage of oil-free, turbomachinery-based equipment and using CO2 as the refrigerant, the temperature limitations of existing heat pump solutions can be eliminated. Novel cycle architectures, partially derived from sCO2 power cycle concepts, have been developed that significantly improve the performance of CO2 heat pumps relative to conventional vapor compression architectures, both for single-phase material heating and for medium pressure steam generation. Cycle simulations of these new heat pump cycles that cover a wide range of conditions and applications have been completed. Pilot-scale (< 50 kWth) demonstration systems have been built and tested, and their measured performance provides validating data for the simulated results.
Numerical Investigation of Lean Hydrogen-Air Flame Stabilization Regimes Using Large-Eddy Simulations
Authors: Verma Ishan , Yadav Rakesh , Orsino Stefano , Shrivastava Sourabh , Zhang Yuxin , K. Vasudevarao , Sukumar Vijayaraj
Published: August 2024

High-fidelity large-eddy simulations (LES) of turbulent combustion in a typical H2-air flame have been conducted in this work. The simulations are based on a laboratory-scale coaxial dual-swirl injector in which fuel and air are injected separately. Based on the thermal power, at a given equivalence ratio, two flame archetypes are observed in the experiments: a flame anchored to the injector (at ∼4 kW) and an aerodynamically stabilized flame (at ∼10 kW). LES allows the scrutiny of the flame structure and stabilization mechanisms seen with each archetype. The LES is first validated on a non-reacting configuration using Particle Image Velocimetry (PIV), followed by extending the modeling formulation to account for combustion. The modeling formulations successfully retrieve the two regimes, and the stabilization mechanism is investigated further by comparing the LES results with PIV and OH* chemiluminescence images. The mean velocity field for both operating conditions suggests the existence of a strong central recirculation zone (CRZ), which penetrates along the central axis in the injector nozzles, leading to a radial deviation of the central hydrogen jet. As a result, CRZ favors the stabilization of one mode over the other. In one mode, the flame anchors over the lip of the injector and exists along the mixing layer between hydrogen and swirling air jets. In the latter mode, the flame is aerodynamically lifted and stabilizes in the inner shear layer between CRZ and exiting swirling air jets.

Further, LES analysis suggests that the flame is diffusion-dominated in the anchored regime, while the lifted regime has partial premixing and diffusion fronts. Another aspect of numerical investigations is to predict the NOx generated for each operating point. The combustion model formulation is further extended to account for NOx by using the extended Zeldovich mechanism. Finally, various approaches are compared for computational efficiency to predict different NOx levels for each operating condition. In general, LES results successfully predict the flame stabilization regimes along with NOx.
Development of SGT-A35 GT61 (39 MW) for Oil and Gas Applications
Authors: Thirumurthy Deepak , Perez Vincent , Wong Mew Wah Didier , Scudamore Mark
Published: August 2024

The SGT-A35 (previously known as Industrial RB211) aeroderivative gas turbine is derived from the Rolls-Royce RB211 aviation gas turbine and it has a fleet size of more than 800 units. It is a known reference in the oil and gas market for both offshore and onshore application with more than 46 million hours of operating experience. Since its entry into service in 1974, this gas turbine has gone through continuous improvement with advanced technologies for increased power output, cycle efficiency, reliability, and availability. The SGT-A35 GT61 is the current fourth-generation gas turbine which was introduced in 2001 and provides 34 MW.

The new fifth generation SGT-A35 GT61 (39 MW) is the latest and most significant development in the Siemens Energy aeroderivative gas turbine product portfolio. The design changes were limited to cold section of the gas turbine. This includes addition of stage zero to the intermediate pressure compressor, newly designed variable inlet guide vane, variable stator vanes, and minor redesign to other compressor stages. These changes increased the flow capacity and greater than 10% increase in shaft power is achieved. No changes to the hot section has been implemented to maintain the industry class reliability and to keep the fleet experience relevant.

This paper provides the details on how the new fifth generation SGT-A35 variant was developed and verified. An extensive engine test program was completed at Siemens Energy facilities to verify all critical-to-quality attributes and to mitigate technical risks before the entry to service. In addition to the design details, results from the development test campaign are presented. The test exceeded the expectations and provided valuable data for further optimization of the product performance.
Effect of Geometry Modification of a Double Entrance Y-Duct Inlet on Aerodynamic Performance With High Speed Flow
Authors: Gilbart Ben , Rider Courtney , Asghar Asad , Allan William D. E. , Stowe Robert A. , Pimentel Rogerio
Published: August 2024

Certain aircraft configurations use embedded gas turbine engines that require offset inlets to direct oncoming air to the engine face. Y-duct inlets are commonly used, especially in military aviation, due to their versatility and aerodynamic performance. Work completed at the Royal Military College of Canada has investigated the performance of two Y-duct designs to study the effect of certain geometric parameters on duct performance. A baseline duct was created and its performance was evaluated at an entrance Mach number of Ma = 0.63. The baseline duct was originally designed for Ma = 0.80 entrance flow; however, the flow choked in the Y-duct at Ma = 0.63. A modified Y-duct was then created by reducing offset and bends in the baseline geometry to overcome the problem. Static and total pressure recovery were evaluated at Ma = 0.8 to determine the presence of secondary flows in the modified duct. This work aims to develop the understanding of relationships between geometric parameters and performance of Y-duct inlets.
Comparative Life Cycle Assessment of Waste Coal and Biomass/Torrefied Biomass Co-Fired Power Plant With Carbon Capture and Storage Technologies
Authors: Sarkar Surja , Bhoi Prakash
Published: August 2024

Climate change is currently one of the prominent worldwide issues that has garnered significant attention. The primary sources of fuel for generating utility-scale electricity in the US include coal, natural gas, petroleum, and other gases. Global warming arises from the extensive release of greenhouse gases, specifically CO2, from the burning of fossil fuels. Nonetheless, the rapid expansion of biomass-based heat and electricity generation is contributing significantly to the attainment of the goal of zero carbon emissions, mostly because of their reduced carbon footprint. In this study, the life cycle impact assessment (LCA) of the 100 MW subcritical pulverized coal-fired power plants that utilize anthracite waste coal and loblolly pine biomass/torrefied biomass as the power plant feedstocks have been assessed with and without the implementation of carbon capture and storage (CCS) technology considering the corresponding material, energy, and transportation inputs and outputs. The findings demonstrate that as the biomass fraction in the power plant feed increases, the global warming potential (GWP) decreases, and an addition of CCS further reduces GWP. Moreover, it is observed that the acidification potential, particulate matter formation potential, and ozone depletion potential typically exhibit a diminishing trend with the increment of the biomass/torrefied biomass ratio in co-fired power plants. However, the eutrophication potential and photochemical smog formation potential show an escalated value in waste coal and torrefied biomass co-firing cases. Nonetheless, the water consumption of waste coal and biomass/torrefied biomass co-fired power plants escalates as the ratio of biomass/torrefied biomass increases, and the integration of CCS further increases the water consumption potential.
Insight Into the Rotor Dynamics Consortium’s History, Vision, and Ongoing Technical Projects
Authors: Powell Don , Patel Hemant
Published: August 2024

The Engine-Aero industry has used MSC Nastran for propulsion loads and dynamics for more than 40 years. Over that timeframe, many collaborative efforts have taken place to position MSC Nastran to satisfy the structural dynamics analysis requirements when designing a new engine and installing it on an airplane. In the late 1990s, a NASA/Boeing/MSC Software (now part of Hexagon AB) rotor dynamic consortium was formed. This effort lasted for a decade (∼1998 to 2008) and resulted in numerous significant rotor dynamics simulation capability improvements driven by Boeing, the jet engine manufacturers and turbo-machinery companies. Now it’s 2023, fifteen years later, and the Engine-Aero industry again is expressing the need to push additional development into MSC Nastran’s rotor dynamic capabilities. This is supported by Boeing, jet engine OEMs, including General Electric, Safran Aircraft Engines, Pratt and Whitney, Rolls-Royce, and Honeywell. The Rotor Dynamics Consortium aims to define, drive, and standardize requirements to build models to address demanding rotor dynamics modeling and simulation needs. In this paper we will discuss what constitutes the consortium, the participating companies, subject matter, and the timeline to complete some of the ongoing initiatives. It will also include technical details about some of the ongoing activities (but is not excluded to): Advanced non-linear harmonic response; Support for 1D, axisymmetric and 3D Rotors; Synchronous analysis with multiple rotors; Consistent super elements and model reduction techniques; Internal rotor damping; and the solution procedure to best capture the effects of internal rotor damping for complex eigenvalue analysis (Campbell diagram) and frequency response analysis.
A Large Language Model Interface for Cycle Modeling
Authors: Roddy Reese , Replogle Cole , Connolly Brian
Published: August 2024

Large Language Models (LLMs) have demonstrated intelligent capabilities, but there has been limited research into their applicability to engineering applications. This work assesses the potential of LLMs, specifically OpenAI’s GPT-4, as an interface for the Numerical Propulsion System Simulation (NPSS). Training data and code were provided to the LLM in context, and it was able to process and understand basic engineering concepts related to NPSS. In most cases it was able to satisfactorily answer user queries and provide suggestions. Despite the evident capability of the model, it also exhibited several deficiencies including errors, oversights, and high operational costs. The most insidious problems occurred when the LLM answered confidently and incorrectly. As such, LLMs cannot yet be relied on for complex engineering work. Potential areas for further development and testing to mitigate these issues were explored. An analysis of LLM temperature variation for simple recall and reasoning tasks was conducted, showing good repeatability and reliability, albeit on a limited test set. Future work could explore the development of a standardized NPSS test suite for LLM performance evaluation. With improvements, LLMs could have transformative implications for future users of complex engineering software.
Hybrid RANS-LES Simulation of Rotor-Stator Interaction in a Compressor Stage Using Grid-Adaptive Simulation Method
Authors: Tang Yumeng , Wei Xindi , Liu Yangwei
Published: August 2024

Flows in compressors are extremely complex with various scales. Small-scale turbulence, middle-scale rotor-stator interaction, large-scale corner separation and tip leakage flow, should all be considered in the simulation of compressors. Recently, a new hybrid RANS-LES strategy that modifies the turbulent viscosity equation based on the Kolmogorov energy spectrum termed the grid-adaptive simulation (GAS) method, is proposed by our group to achieve high accuracy simulation using different grid resolutions. In this study, the GAS method with the SST turbulence model is employed to simulate the rotorstator interaction just with RANS-like grid resolution in a singlestage transonic compressor TUDa-GLR open test case. Compared with experiments and other simulation methods (including RANS and DDES methods), results show that the GAS method can significantly improve the prediction accuracy for stall margin and radial distribution of flow parameters. Then, the effect of rotor-stator interaction on the secondary flow structures is analyzed based on the unsteady flow field simulated by the GAS method. Results show that the incorrect prediction of rotor tip leakage vortex breakdown and the underestimation of mixing losses in the tip region of the rotor are blamed for the high prediction deviation of RANS. An intuitive total pressure fluctuation caused by wakes is observed in the stator inlet. The particle tracking shows that the wake from the suction surface of the rotor has a strong trend to transport into the tip region of the stator. Spectral proper orthogonal decomposition (SPOD) is also utilized. Unsteady temporal-spatial structures induced by local unsteadiness and rotor-stator interaction (RSI) are distinguished by SPOD, which includes the reverse flow in the tip region of the rotor and the pressure wave generated from RSI. SPOD also found the separation of the stator on the suction side exhibits an unsteady fluctuation with a frequency of 1.6 BPF.
Effect of sputtering power and thickness ratios on the materials properties of Cu–W and Cu–Cr bilayer thin films using high power impulse magnetron and DC magnetron sputtering
Authors: Nguyen Tra Anh Khoa , Huang Yu , Dang Nhat Minh , Lin Chi-Han , Chen Wei-Chieh , Wang Zhao-Ying , Lin Ming-Tzer
Published: August 2024

This study investigates the influence of Cu thickness ratios on the structural, morphological, and mechanical properties of sputtered Cu–W and Cu–Cr bilayer thin films. Employing high power impulse magnetron sputtering (HiPIMS), five distinct thickness ratios of 1:3, 3:5, 1:1, 5:3, and 3:1 were analyzed and compared to bilayer films developed using direct current magnetron sputtering (DCMS). The microstructural and surface characteristics of these films were evaluated using x-ray diffraction (XRD), atomic force microscopy, and scanning electron microscopy. Electrical properties were measured using a four-point probe, while mechanical properties were assessed through nanoindentation. Results reveal that increasing Cu thickness in Cu–W and Cu–Cr bilayers inversely affects hardness, grain size, and roughness, highlighting the influence of thickness ratios on film properties. Films with a higher Cu thickness ratio in both Cu–W and Cu–Cr bilayer systems deposited by HiPIMS exhibited lower hardness, smaller grain size, and reduced average roughness. Cross-sectional analysis and XRD confirmed the impact of thickness ratio on crystal phase and microstructure, indicating smoother columnar structures. Specifically, the HiPIMS-deposited Cu–Cr 3-1 film exhibited the lowest resistivity, at 4.77 μΩ cm, and hardness, measuring 8.26 GPa. Moreover, the 1:1 ratio films of Cu–W and Cu–Cr demonstrated hardness values of 13.81 and 11.37 GPa, respectively, which were 1.39 times higher than the films grown by DCMS. Additionally, variations in the bilayer thickness ratio significantly affected the electrical properties of the films. The enhanced properties of HiPIMS films are attributed to the higher peak power density of the target, leading to increased ion energy and deposition of dense grain structures.
The Effect of Ischemic Preconditioning on Tennis Exercise Performance and the Recovery Subsequent to a Simulated Tennis Match: A Randomized Controlled Trial
Authors: Xin Zekun , Shi Yuxuan , Wu Ying
Published: August 2024

Purpose: The purpose of this study was to investigate the effects of acute ischemic preconditioning (IPC) on tennis skill and physical exercise performance, as well as to explore whether 7-day repeated IPC (RIPC) accelerated fatigue recovery after a simulated tennis match. Methods: Twenty-nine male tennis-specific current students were randomly allocated into 1 of 2 groups: SHAM (n = 14, 3 × 5 min at 20 mm Hg) and IPC (n = 15, 3 × 5 min at 220 mm Hg). Participants in both groups engaged in acute IPC and RIPC interventions. After the first acute IPC intervention, assessments were conducted to evaluate tennis-specific skills and overall physical exercise capacity. Following completion of chronic RIPC interventions, all participants competed in a simulated tennis match specifically designed to induce fatigue. To evaluate recovery from this induced fatigue, physical exercise capacity tests were conducted at 24 and 48 hours postmatch, allowing for an assessment of the participants’ recovery capabilities over time. Results: After the first acute intervention, notable differences were observed between the IPC and SHAM groups in their performance on the repeated-sprint ability test. Specifically, the total times recorded were significantly shorter in the IPC group compared with the SHAM group (IPC: 109.05 [2.70] vs SHAM: 114.57 [7.45] s, P = .012), and this trend was also reflected in their best times (IPC: 4.20 [0.18] s vs SHAM: 4.39 [0.30] s, P = .042), indicating an immediate benefit of the IPC intervention on sprint performance. After a 7-day RIPC intervention, significant changes were noted in the SHAM group’s performance metrics postmatch. There was an increase (P < .001) in fatigue index from 22% (8%) to 30% (9%) during repeated-sprint ability test and a decrease in serve speed from 120.2 (17.5) to 106.7 (13.0) km/h (P = .002) and knee peek torque from 196.0 (49.0) to 162.7 (39) N (extension, 60°/s, P < .001) in the SHAM group 24 hours postmatch, relative to the IPC group. Moreover, compared with the SHAM group, the IPC group showed a lower rate of perceived exertion during the match (P < .001) and a decrease in visual analog scale score (P = .026) 24 hours postmatch, suggesting enhanced recovery and reduced perception of pain relative to the SHAM group. Conclusion: IPC could serve as a strategy to generate an ergogenic effect and recovery during training and competition.
Exploring the Factors Influencing Motivation and Satisfaction of Video Game Players
Authors: Kępka Patrycja , Strzelecki Artur
Published: August 2024

The focus of the article is the user motivation and satisfaction from playing video games. It covers the basic information on the video game player types and the video game market. The aim of this work is to assess the factors influencing the motivation and satisfaction from playing video games. The purpose of this study is to examine what elements influence motivation and satisfaction in the video game players and what aspects of playing video games are influenced by the gamers’ motivation. The study tested and applied a theoretical model in the context of video game players. To test the suggested research model, a structural equation modeling’s partial least squares approach was used. Data from the 1,400 video game players were gathered through an online survey. SmartPLS 4 was used to analyze the data set. The results indicated that the most accurate predictor of the players’ motivation is satisfaction, followed by openness of the world. Motivation predicted the users’ achievements, competitiveness, and long-term goals. The video game producers are especially interested in this research because the findings help better understand the motivation and satisfaction of video game players.
Design of intrinsically disordered protein variants with diverse structural properties
Authors: Pesce Francesco , Bremer Anne , Tesei Giulio , Hopkins Jesse B. , Grace Christy R. , Mittag Tanja , Lindorff-Larsen Kresten
Published: August 2024

Intrinsically disordered proteins (IDPs) perform a broad range of functions in biology, suggesting that the ability to design IDPs could help expand the repertoire of proteins with novel functions. Computational design of IDPs with specific conformational properties has, however, been difficult because of their substantial dynamics and structural complexity. We describe a general algorithm for designing IDPs with specific structural properties. We demonstrate the power of the algorithm by generating variants of naturally occurring IDPs that differ in compaction, long-range contacts, and propensity to phase separate. We experimentally tested and validated our designs and analyzed the sequence features that determine conformations. We show how our results are captured by a machine learning model, enabling us to speed up the algorithm. Our work expands the toolbox for computational protein design and will facilitate the design of proteins whose functions exploit the many properties afforded by protein disorder.
Inertial range of magnetorotational turbulence
Authors: Kawazura Yohei , Kimura Shigeo S.
Published: August 2024

Accretion disks around compact stars are formed due to turbulence driven by magnetorotational instability. Despite over 30 years of numerous computational studies on magnetorotational turbulence, the properties of fluctuations in the inertial range—where cross-scale energy transfer dominates over energy injection—have remained elusive, primarily due to insufficient numerical resolution. Here, we report the highest-resolution simulation of magnetorotational turbulence ever conducted. Our simulations reveal a constant cross-scale energy flux, a hallmark of the inertial range. We found that as the cascade proceeds to smaller scales in the inertial range, the kinetic and magnetic energies tend toward equipartitioning with the same spectral slope, and slow magnetosonic fluctuations dominate over Alfvénic fluctuations, having twice the energy. These findings align remarkably with the theoretical expectations from the reduced magnetohydrodynamic model, which assumes a near-azimuthal mean magnetic field. Our results provide important implications for interpreting the radio observations by the Event Horizon Telescope.
OsCYP706C2 diverts rice strigolactone biosynthesis to a noncanonical pathway branch
Authors: Li Changsheng , Haider Imran , Wang Jian You , Quinodoz Pierre , Suarez Duran Hernando G. , Méndez Lucía Reyes , Horber Robin , Fiorilli Valentina , Votta Cristina , Lanfranco Luisa , Correia de Lemos Samara M. , Jouffroy Lucile , Moegle Baptiste , Miesch Laurence , De Mesmaeker Alain , Medema Marnix H. , Al-Babili Salim , Dong Lemeng , Bouwmeester Harro J.
Published: August 2024

Strigolactones exhibit dual functionality as regulators of plant architecture and signaling molecules in the rhizosphere. The important model crop rice exudes a blend of different strigolactones from its roots. Here, we identify the inaugural noncanonical strigolactone, 4-oxo-methyl carlactonoate (4-oxo-MeCLA), in rice root exudate. Comprehensive, cross-species coexpression analysis allowed us to identify a cytochrome P450, OsCYP706C2, and two methyl transferases as candidate enzymes for this noncanonical rice strigolactone biosynthetic pathway. Heterologous expression in yeast and
Nicotiana benthamiana
indeed demonstrated the role of these enzymes in the biosynthesis of 4-oxo-MeCLA, which, expectedly, is derived from carlactone as substrate. The
oscyp706c2
mutants do not exhibit a tillering phenotype but do have delayed mycorrhizal colonization and altered root phenotype. This work sheds light onto the intricate complexity of strigolactone biosynthesis in rice and delineates its role in symbiosis and development.
Identification of novel and potent inhibitors of SARS-CoV-2 main protease from DNA-encoded chemical libraries
Authors: Akaberi Dario , Pourghasemi Lati Monireh , Krambrich Janina , Berger Julia , Neilsen Grace , Strandback Emilia , Turunen S. Pauliina , Wannberg Johan , Gullberg Hjalmar , Moche Martin , Chinthakindi Praveen Kumar , Nyman Tomas , Sarafianos Stefan G. , Sandström Anja , Järhult Josef D. , Sandberg Kristian , Lundkvist Åke , Verho Oscar , Lennerstrand Johan
Published: August 2024

In vitro
screening of large compound libraries with automated high-throughput screening is expensive and time-consuming and requires dedicated infrastructures. Conversely, the selection of DNA-encoded chemical libraries (DECLs) can be rapidly performed with routine equipment available in most laboratories. In this study, we identified novel inhibitors of SARS-CoV-2 main protease (M
pro
) through the affinity-based selection of the DELopen library (open access for academics), containing 4.2 billion compounds. The identified inhibitors were peptide-like compounds containing an N-terminal electrophilic group able to form a covalent bond with the nucleophilic Cys145 of M
pro
, as confirmed by x-ray crystallography. This DECL selection campaign enabled the discovery of the unoptimized compound SLL11 (IC
50
= 30 nM), proving that the rapid exploration of large chemical spaces enabled by DECL technology allows for the direct identification of potent inhibitors avoiding several rounds of iterative medicinal chemistry. As demonstrated further by x-ray crystallography, SLL11 was found to adopt a highly unique U-shaped binding conformation, which allows the N-terminal electrophilic group to loop back to the S1′ subsite while the C-terminal amino acid sits in the S1 subsite. MP1, a close analog of SLL11, showed antiviral activity against SARS-CoV-2 in the low micromolar range when tested in Caco-2 and Calu-3 (EC
50
= 2.3 µM) cell lines. As peptide-like compounds can suffer from low cell permeability and metabolic stability, the cyclization of the compounds will be explored in the future to improve their antiviral activity.
N
-linked protein glycosylation in
Nanobdellati
(formerly DPANN) archaea and their hosts
Authors: Nakagawa Satoshi , Sakai Hiroyuki D. , Shimamura Shigeru , Takamatsu Yoshiki , Kato Shingo , Yagi Hirokazu , Yanaka Saeko , Yagi-Utsumi Maho , Kurosawa Norio , Ohkuma Moriya , Kato Koichi , Takai Ken
Published: August 2024

Members of the kingdom
Nanobdellati
, previously known as DPANN archaea, are characterized by ultrasmall cell sizes and reduced genomes. They primarily thrive through ectosymbiotic interactions with specific hosts in diverse environments. Recent successful cultivations have emphasized the importance of adhesion to host cells for understanding the ecophysiology of
Nanobdellati
. Cell adhesion is often mediated by cell surface carbohydrates, and in archaea, this may be facilitated by the glycosylated S-layer protein that typically coats their cell surface. In this study, we conducted glycoproteomic analyses on two co-cultures of
Nanobdellati
with their host archaea, as well as on pure cultures of both host and non-host archaea.
Nanobdellati
exhibited various glycoproteins, including archaellins and hypothetical proteins, with glycans that were structurally distinct from those of their hosts. This indicated that
Nanobdellati
autonomously synthesize their glycans for protein modifications probably using host-derived substrates, despite the high energy cost. Glycan modifications on
Nanobdellati
proteins consistently occurred on asparagine residues within the N-X-S/T sequon, consistent with patterns observed across archaea, bacteria, and eukaryotes. In both host and non-host archaea, S-layer proteins were commonly modified with hexose,
N
-acetylhexosamine, and sulfonated deoxyhexose. However, the
N
-glycan structures of host archaea, characterized by distinct sugars such as deoxyhexose, nonulosonate sugar, and pentose at the nonreducing ends, were implicated in enabling
Nanobdellati
to differentiate between host and non-host cells. Interestingly, the specific sugar, xylose, was eliminated from the
N
-glycan in a host archaeon when co-cultured with
Nanobdella
. These findings enhance our understanding of the role of protein glycosylation in archaeal interactions.

IMPORTANCE

Nanobdellati
archaea, formerly known as DPANN, are phylogenetically diverse, widely distributed, and obligately ectosymbiotic. The molecular mechanisms by which
Nanobdellati
recognize and adhere to their specific hosts remain largely unexplored. Protein glycosylation, a fundamental biological mechanism observed across all domains of life, is often crucial for various cell–cell interactions. This study provides the first insights into the glycoproteome of
Nanobdellati
and their host and non-host archaea. We discovered that
Nanobdellati
autonomously synthesize glycans for protein modifications, probably utilizing substrates derived from their hosts. Additionally, we identified distinctive glycosylation patterns that suggest mechanisms through which
Nanobdellati
differentiate between host and non-host cells. This research significantly advances our understanding of the molecular basis of microbial interactions in extreme environments.
Ipsilateral or contralateral boosting of mice with mRNA vaccines confers equivalent immunity and protection against a SARS-CoV-2 Omicron strain
Authors: Ying Baoling , Liang Chieh-Yu , Desai Pritesh , Scheaffer Suzanne M. , Elbashir Sayda M. , Edwards Darin K. , Thackray Larissa B. , Diamond Michael S.
Published: August 2024

Boosting with mRNA vaccines encoding variant-matched spike proteins has been implemented to mitigate their reduced efficacy against emerging SARS-CoV-2 variants. Nonetheless, in humans, it remains unclear whether boosting in the ipsilateral or contralateral arm with respect to the priming doses impacts immunity and protection. Here, we boosted K18-hACE2 mice with either monovalent mRNA-1273 (Wuhan-1 spike) or bivalent mRNA-1273.214 (Wuhan-1 + BA.1 spike) vaccine in the ipsilateral or contralateral leg after a two-dose priming series with mRNA-1273. Boosting in the ipsilateral or contralateral leg elicited equivalent levels of serum IgG and neutralizing antibody responses against Wuhan-1 and BA.1. While contralateral boosting with mRNA vaccines resulted in the expansion of spike-specific B and T cells beyond the ipsilateral draining lymph node (DLN) to the contralateral DLN, administration of a third mRNA vaccine dose at either site resulted in similar levels of antigen-specific germinal center B cells, plasmablasts/plasma cells, T follicular helper cells, and CD8
+
T cells in the DLNs and the spleen. Furthermore, ipsilateral and contralateral boosting with mRNA-1273 or mRNA-1273.214 vaccines conferred similar homologous or heterologous immune protection against SARS-CoV-2 BA.1 virus challenge with equivalent reductions in viral RNA and infectious virus in the nasal turbinates and lungs. Collectively, our data show limited differences in B and T cell immune responses after ipsilateral and contralateral site boosting by mRNA vaccines that do not substantively impact protection against an Omicron strain.

IMPORTANCE

Sequential boosting with mRNA vaccines has been an effective strategy to overcome waning immunity and neutralization escape by emerging SARS-CoV-2 variants. However, it remains unclear how the site of boosting relative to the primary vaccination series shapes optimal immune responses or breadth of protection against variants. In K18-hACE2 transgenic mice, we observed that intramuscular boosting with historical monovalent or variant-matched bivalent vaccines in the ipsilateral or contralateral limb elicited comparable levels of serum spike-specific antibody and antigen-specific B and T cell responses. Moreover, boosting on either side conferred equivalent protection against a SARS-CoV-2 Omicron challenge strain. Our data in mice suggest that the site of intramuscular boosting with an mRNA vaccine does not substantially impact immunity or protection against SARS-CoV-2 infection.