Mechanical Components Research Articles

Residual Stress in Friction Stir Welding of Dissimilar Aluminum Alloys: A Parametric Study

Welding-induced residual stress has the capacity to significantly compromise the integrity of mechanical components. Its minimization therefore plays a critical role in the selection of process parameters during the welding process. Friction stir welding is a useful joining technique to weld many materials that are not amenable to the traditional welding techniques. Using a sequentially coupled thermomechanical three-dimensional finite element simulation, this work aimed to quantitatively evaluate the influence of the tool rotational and traverse speeds on the generation of residual stress in the friction stir welding of dissimilar aluminum alloys AA2024−T3 and AA5086−O. The model was validated using established experimental and numerical results. The procedure entailed an initial thermal analysis, the results of which were superposed on a mechanical model to determine the distribution of the residual stress across the welded alloy. The results showed that longitudinal residual stress was dominant as compared to lateral stress. It was also demonstrated that, although the tool rotational speed and the tool traverse speed both affected the post-weld temperature distribution and consequently the longitudinal residual stress, the influence of the former was more substantial. Furthermore, the peak values of the residual stress were found on the retreating side (AA5086−O), making it more critical for the selection of welding process parameters.

MDM2 functions as a timer reporting the length of mitosis.

Delays in mitosis trigger p53-dependent arrest in G1 of the next cell cycle, thus preventing repeated cycles of chromosome instability and aneuploidy. Here we show that MDM2, the p53 ubiquitin ligase, is a key component of the timer mechanism triggering G1 arrest in response to prolonged mitosis. This timer function arises due to the attenuation of protein synthesis in mitosis. Because MDM2 has a short half-life and ongoing protein synthesis is therefore necessary to maintain its steady-state concentration, the amount of MDM2 gradually falls during mitosis but normally remains above a critical threshold for p53 regulation at the onset of G1. When mitosis is extended by prolonged spindle assembly checkpoint activation, the amount of MDM2 drops below this threshold, stabilizing p53. Subsequent p53-dependent p21 accumulation then channels G1 cells into a sustained cell-cycle arrest, whereas abrogation of the response in p53-deficient cells allows them to bypass this crucial defence mechanism.

Fluorination to Enhance the Tribological Properties of Carbonaceous Materials

This review compiles data from 77 articles on the tribological properties of fluorinated carbons CFx. Covalent grafting of fluorine atoms improves the tribological properties. The C-F bonding plays a key role in reducing friction. The tribological stability of CFx, along with their ability to form protective films from the very first cycles, provides a significant advantage in reducing wear and extending the lifespan of mechanical components. The role of the presence of fluorine atoms, their content, their distribution in the carbon lattice, and the C-F bonding, as well as the dimensionality and the size of the materials, are discussed. Some ways of improving lubrication performance and investigating friction-reducing properties and mechanisms are proposed.

Nucleus softens during herpesvirus infection.

Mechanical properties of the nucleus are remodeled not only by extracellular forces transmitted to the nucleus but also by internal modifications, such as those induced by viral infections. During herpes simplex virus type 1 infection, the viral regulation of essential nuclear functions and growth of the nuclear viral replication compartments are known to reorganize nuclear structures. However, little is known about how this infection-induced nuclear deformation changes nuclear mechanobiology. Our analyses showed that the nucleus softens during the infection. To understand why this happens, we used microscopy and computational methods to study how the mechanical components of the nucleus are modified during the infection. We discovered that the viral replication compartment occupying the nuclear center has a low biomolecular density compared to the centrally located euchromatin in noninfected cells. The nuclear lamina was also modified such that in the infection the amount of lamin proteins increased and the nuclear envelope had more outward curved regions and moved less in infection compared to noninfected cells. The computational modeling of virus-induced changes in cellular forces showed that the most probable cause for the decreasing nuclear stiffness is the removal of lamina-associated domains or the decrease in outward forces, such as reduced intranuclear osmotic pressure and cytoskeletal pull. The simulations showed that an increase in the nuclear envelope tension can occur with a decrease in nuclear stiffness. Based on these findings, we propose a mechanical model that explains mechanistic coordination between the nuclear deformation in infection and decreased nuclear stiffness.

Design and Development of a Four-Wheeled Mobile Robot (WMR) for Any Terrain

This paper presents the design, development, and analysis of an all-terrain Wheeled Mobile Robot (WMR). A Wheeled Mobile Robot (WMR) is an autonomous robot that uses wheels for locomotion, allowing it to move efficiently on flat surfaces. These robots are commonly used in various applications, from industrial automation to service robots and research platforms. The robot aims to achieve high mobility on diverse terrains, remote teleoperation, and an effective payload handling capability. The research includes the design and implementation of the mechanical structure, electronic components, control systems, and robot performance analysis. Special focus is given to the kinematic behavior, vibration analysis, and simulation of various components. The robot can carry loads up to 5 kg and navigate complex terrains, including stair climbing. The methodology followed includes structure design, integration of electronic components, assembly, and subsequent trials and simulations. The results demonstrate the robot's potential for practical applications in diverse fields such as exploration, rescue operations, and industrial automation. In summary, wheeled mobile robots are versatile, efficient, and widely used in various industries. Their design carefully balances mechanical, electronic, and software components to achieve reliable and autonomous operation. As technology advances, WMRs become more capable and adaptable, expanding their range of applications.

Basic Research on Multi-Directional Forging of AZ80Mg Alloy for Fabrication of Bulky Mechanical Components

Basic Research on Multi-Directional Forging of AZ80Mg Alloy for Fabrication of Bulky Mechanical Components

Influence of the shape of abrasive soil particles on the regularities of destruction of structural steels during wear

The article presents the results of studying the patterns of destruction and their influence on the wear resistance of structural steels: steel 45, steel 65G and steel 28MnB5 when moving in soils with different abrasive particle shape factors. The phenomenon of the presence of a critical abrasive particle shape factor (CPSF) was established, up to which the wear resistance of steels decreases. In the supercritical region, wear resistance is stabilized, and the differences between its values of the studied steels are significantly reduced. When forming wear resistance, the role of the particle shape factor is to regulate active deformation and fatigue phenomena by means of the level of external force action on the working surface and is realized through the rheological-fatigue parameter, which is controlled by the cyclic viscosity of steel deformation. In this regard, the choice of structural steel grade for the manufacture of machine parts intended for use in soils with different abrasive particle shape factors must be made based on its ranking by the rheological-fatigue parameter. It is shown that in the strength basis of the steel wear mechanism under sliding friction in soils with different particle shape factors, in addition to the resistance to the propagation of axial and radial fatigue cracks in the destructive deformation layer, an important role is played by the resistance to the initiation and propagation of lateral fatigue cracks at its boundary with the plastic-destructive deformation layer, and the mechanical component of the contact interaction is decisive. It is established that under wear in soils with different particle shape factors, the action of the softening process is more effective than the hardening process. In the supercritical region, the intensity of steel softening is significantly reduced due to the increase in the effectiveness of the hardening action due to the dispersion hardening of steel. However, no qualitative changes in the metal wear process are observed

Effects of the Geometric Uncertainties of Bladed Disks Through the Analytical Derivatives of the Finite Element Matrices

Abstract Manufacturing processes and wear are known to create imperfections in mechanical components that may result in a significant deviation of the modal properties from their predicted values. This is especially true for periodic structures such as bladed disks, where even small variations in the blade geometry can cause mistuning. The effect of parameter variations on the model is commonly assessed through sensitivity analysis within the framework of uncertainty propagation or structural optimization. Different formulations are available when dealing with the variation of a single scalar parameter. The problem becomes more complicated when the source of the variation is the whole component geometry. To deal with this case, it is necessary to define a representation able to describe the shift from the nominal geometry through a finite set of parameters and compute the derivatives of the system matrices with respect to those parameters. This paper proposes to compute analytically the derivatives of the system matrices with respect to the geometric variations. The derivatives are calculated at the finite element (FE) level and are then assembled into global derivative matrices. Using directional derivatives, the sensitivities of the system matrices are computed with standard FE numerical schemes based on the nominal geometry.

Research on fault component extraction and fault type identification of rotating machinery based on MDSM and a novel convolutional neural network

Abstract Given the complexity and difficulty in extracting and recognizing multi-axis mechanical fault components, a method for fault extraction and identification based on the Multi-Axis Displacement Superposition Method (MDSM) and a Novel Convolutional Neural Network (NCNN) is proposed. In the proposed MDSM method, first, correlation analysis is used to determine the operational status of the mechanical system and to identify the location of faults in the multi-axis rotating mechanical system. Secondly, a simplified initial point selection process is introduced to segment the collected fault component. Subsequently, a signal superposition method with position offset correction is employed to perform position correction and superposition operations on the segmented signals, enhancing the accuracy of the fault signal. Finally, the front end of the superimposed signals is extracted as the fault component, completing the separation and extraction of the fault components. For the extracted fault signals, an NCNN is designed for fault-type identification. NCNN improves computational efficiency and effectively completes fault feature identification through a lightweight network architecture and a nonlinear learning rate scheduling strategy. The results of the experiment show that the proposed method can accurately determine the fault occurrence location, extract the fault components, and achieve high-accuracy fault type identification.

Fuel consumption analysis and cost overview of mechanical vehicles in petroleum drilling rig

During the drilling activities carried out before the use of Petroleum and Geothermal Energy resources, daily fuel consumption occurs depending on the operational diversity of the mechanical components of different types of rigs in our country. In this study, a time-dependent financial analysis of the preferred operating procedure and fuel consumption during drilling operations was performed, both in engineering studies and in order to reach a predictable level in terms of cost, oil drilling operations were mentioned by drilling rig type today, and comparisons of mechanical evenings were made to provide an economically predictable earning environment for daily fuel consumption. As a result of the research and findings, Group Motors/Drawworks, Pump Motor and Generators were actively used during the idling of mechanical evenings, and the average daily diesel consumption of 23.61 lt/h, 45.8 lt/h and 33.3 lt/h was reached, respectively. Maneuver Opr. the average daily diesel consumption of 37.5 lt/h, 0 lt/h and 39.58 lt/h was reached based on the active use of Group Motors/Drawworks, Pump Motors and Generators during the operation. Drilling Opr. the average diesel consumption of 26.24 lt/h, 129 lt/h, 33.3 lt/h and 83 lt/h respectively was reached based on the active use of Group Motors/Drawworks, Pump Motor, Generators and Top Drive.

Pneumatic coding blocks enable programmability of electronics-free fluidic soft robots.

Decision-making based on environmental cues is a crucial feature of autonomous systems. Embodying this feature in soft robots poses nontrivial challenges on both hardware and software that can undermine the simplicity and autonomy of such devices. Existing pneumatic electronics-free soft robots have so far mostly been approached by using system fluidic circuit architectures analogous to digital electronics. Instead, here we design dedicated pneumatic coding blocks equivalent to If, If...break, and For software control statements, which are based on the analog nature of nonlinear mechanical components. We demonstrate that we can combine these coding blocks into programs to implement sequences and to control an electronics-free autonomous soft gripper that switches between behaviors based on interactions with the environment. As such, our strategy provides an alternative approach to designing complex behavior in soft robotics that is more reminiscent of how functionalities are also encoded in the body of living systems.

Implementation of Principal Component Analysis (PCA)/Singular Value Decomposition (SVD) and Neural Networks in Constructing a Reduced-Order Model for Virtual Sensing of Mechanical Stress.

This study presents the design and validation of a numerical method based on an AI-driven ROM framework for implementing stress virtual sensing. By leveraging Reduced-Order Models (ROMs), the research aims to develop a virtual stress transducer capable of the real-time monitoring of mechanical stresses in mechanical components previously analyzed with high-resolution FEM simulations under a wide range of multiple load scenarios. The ROM is constructed through neural networks trained on Finite Element Method (FEM) outputs from multiple scenarios, resulting in a simplified yet highly accurate model that can be easily implemented digitally. The ANN model achieves a prediction error of MAEtest=(0.04±0.06) MPa for the instantaneous mechanical stress predictions, evaluated over the entire range of stress values (0 to 5.32 MPa) across the component structure. The virtual sensor is capable of producing a quasi-instantaneous, detailed full stress map of the component in just 0.13 s using the ROM, for any combination of 4-load inputs, compared to the 6 min and 31 s required by the FEM. Thus, the approach significantly reduces computational complexity while maintaining a high degree of precision, enabling efficient real-time monitoring. The proposed method's effectiveness is demonstrated through rigorous ROM validation, underscoring its potential for stress control. This precise AI-driven procedure opens new horizons for predictive maintenance strategies centered on stress cycle monitoring.

A Novel Polarity Correction Method for Waveform Stacking Location of Microseismic Events

Microseismic events play a crucial role in mapping fault and fracture distributions in natural and induced earthquakes. Detecting and localizing microseismic events is challenging due to low signal-to-noise ratios (SNR). Waveform stacking (WS) imaging location is a practical approach for automatically detecting and localizing microseismic events, assuming that the traveltime-corrected seismic waveforms will stack and enhance coherently. However, coherent stack enhancement is susceptible to polarity reversal caused by the non-explosive components of the source mechanism, which can lead to an unfocused source image, making it difficult to retrieve the optimal location accurately. In this study, we propose a new polarity correction method to address this issue, based on the characteristic that the instantaneous phase difference between two seismic signals with opposite polarity is ±p. First, the Hilbert transform is applied to the original seismic record to obtain instantaneous amplitude A(t) and phase f(t). Then, a new signal is constructed by multiplying A(t) with cos[2f(t)]. The constructed signals for different receivers have the same polarity, thereby being used to refocus the source image. Furthermore, they preserve both positive and negative amplitudes, which contributes to noise suppression. Synthetic tests show that the proposed method can effectively achieve polarity correction and noise suppression, enabling a high-resolution source image. Application to real hydraulic fracturing data demonstrates that the proposed method can detect and locate more microseismic events at the fracturing depths, suggesting its effectiveness and potential advantage in microseismic data processing. Since the polarity correction is performed in the data domain without relying on specific receiver layouts, the method is computationally efficient and could be applied to real-time microseismic monitoring across various sites, including hydraulic fracturing and volcano monitoring.

Improved Friction Reduction and Wear Resistance of Steel Using a Subnanometer Nanowires-Poly-α-Olefin Gel Lubricant.

Lubricating oil is commonly utilized due to its excellent lubricating properties in mechanical motion systems. However, high fluidity in lubricating oil often leads to leakage during machine operation, causing mechanical components to fail. Herein, a gel lubricant of SNWs-PAO6 was devised by combining subnanometer nanowires (SNWs) with poly α-olefin 6 (PAO6) at room temperature, effectively confining PAO6 and preventing PAO6's creeping and leakage while enhancing its load-bearing capacity. SNWs-PAO6 outperforms PAO6 in reducing friction and wear for steel-on-steel interfaces. The friction coefficient is markedly diminished by 57.53%, from 0.223 to 0.095, while the wear rate is significantly curtailed by 84.98%. Furthermore, SNWs-PAO6 remains stable even after 180 000 cycles at 200 N and 25 Hz, withstanding high-speed centrifugation without releasing PAO6. It remained stable over 6 months of resting and can well withstand low temperatures. Surface analysis of the wear scar and the formed tribochemical film after friction has demonstrated that PW12O403- is more likely to adsorb onto the steel surface, forming a lubricating medium film through tribochemical reactions and thus reducing interfacial friction and wear. This method facilitates the development of domain-limited nanomaterials-based gels for mass production and their applications in engineering moving parts.

The problem of institutional positioning of the prosecutor’s office in the context of the constitutional principle of separation of powers

It is indicated that in the conditions of the formation of Ukraine as a state based on the principles of democracy and the rule of law, it is extremely important to ensure the effective work of all links of the state mechanism, in particular the prosecutor’s office as its integral component. The correct positioning of the prosecutor’s office in the structure of state institutions is of decisive importance for the organization of power as a whole, because it directly affects both the quality of the prosecutor’s office’s performance of the tasks assigned to it and the balanced functioning of the system of checks and balances. The article examines the problem of determining the place of the prosecutor’s office in the system of state authorities of Ukraine. Scientific approaches to understanding the legal nature of law enforcement agencies and their positioning in the state mechanism are analyzed. The discussion on the allocation of law enforcement agencies as an independent component of the state mechanism and the possibility of expanding the constitutional model of the separation of powers is highlighted. Particular attention is paid to the trend of rethinking the traditional concept of the separation of powers and the separation of the control authority as the fourth branch. The need for the formation of an independent control and supervisory branch of power is substantiated and proposals for including a special section on state control in the structure of the Fundamental Law of Ukraine are analyzed. The main approaches to determining the place of the prosecutor’s office in the system of state power are considered in detail: as part of the legislative, executive, judicial branches of power or the presidential vertical. Foreign experience in organizing the prosecutor’s office is analyzed and five main models of its functioning in different countries are identified. International standards on the role of the prosecutor’s office are studied, in particular the Recommendations of the Committee of Ministers of the Council of Europe. Based on the analysis, a conclusion is drawn about the need to reform the status of the prosecutor’s office in Ukraine, taking into account both international standards and national characteristics - historical traditions, legal culture, socio-economic and political realities. The importance of a comprehensive approach to resolving the issue of integrating the prosecutor’s office into the system of separation of state power is emphasized.

Gyroid Lattice Heat Exchangers: Comparative Analysis on Thermo-Fluid Dynamic Performances

In recent years, additive manufacturing has reached the required reliability to effectively compete with standard production techniques of mechanical components. In particular, the geometrical freedom enabled by innovative manufacturing techniques has revolutionized the design trends for compact heat exchangers. Bioinspired structures, such as the gyroid lattice, have relevant mechanical and heat exchange properties for their light weight and increased heat exchange area, which also promotes the turbulent regime of the coolant. This work focuses its attention on the effect of the relevant design parameters of the gyroid lattice on heat exchange performances. A numerical comparative analysis is carried out from the thermal and fluid dynamic points of view to give design guidelines. The results of numerical analyses, performed on cylindrical samples, are compared to the experimental results on the pressure drop. Lattices samples were successfully printed with material extrusion, which is a low-cost and easy-to-use metal AM technology. For each lattice sample, counter pressure, heat exchange, and turbulence intensity ratio are calculated from the numerical point of view and discussed. At the end, the gyroid lattice is proven to be very effective at enhancing the heat exchange in cylindrical pipes. Guidelines are given about the choice of the best lattice, depending on the considered applications.

On the Feasibility of Detecting Faults and Irregularities in On-Load Tap Changers (OLTCs) by Vibroacoustic Signal Analysis.

Unlike traditional tap changers, which require transformers to be de-energized before making changes, On-Load Tap Changers (OLTCs) can adjust taps while the transformer is in service, ensuring continuous power supply during voltage regulation. OLTCs enhance grid reliability and support load balancing, reducing strain on the network and optimizing power quality. Their importance has grown as the demand for stable voltage and the integration of renewables has increased, making them vital for modern and resilient power systems. While enhanced OLTCs often incorporate stronger materials and improved designs, mechanical components like contacts and diverter switches can still experience wear over time. This can result in longer maintenance intervals. In the era of digitalization, advanced diagnostic techniques capable of detecting early signs of wear or malfunction are essential to enable preventive maintenance for these important components. This contribution introduces a novel method for detecting faults and irregularities in OLTCs, leveraging vibroacoustic signals to enhance OLTC diagnostics. This paper proposes a tolerance-based approach using the envelope of vibroacoustic signals to identify faults. A significant challenge in this field is the limited availability of faulty signal data, which hinders the performance of machine learning algorithms. To address this, this study introduces a nonlinear model utilizing amplitude modulation with a Gaussian carrier to simulate faults by introducing controlled distortions. The dataset used in this study, with data recorded under real operating conditions from 2016 to 2023, is free of anomalies, providing a robust foundation for the analysis. The results demonstrate a marked improvement in the robustness of detecting simulated faults, offering a promising solution for enhancing OLTC diagnostics and preventive maintenance in modern power systems.

Nzf2 promotes oligodendrocyte differentiation and regeneration via repressing HDAC1-mediated histone deacetylation.

Proper axonal myelination and function of the vertebrate central nervous system rely largely on the timely differentiation of oligodendrocytes (OLs), yet key regulatory factors remain enigmatic. Our study reveals neural zinc finger (Nzf2) as a crucial orchestrator that controls the timing of OL differentiation both during development and myelin repair, contrasting with its previously suggested role in direct myelin gene regulation. Nzf2 ablation delays the onset of OL differentiation, while hyperactivation stimulates OL differentiation both during development and remyelination. Using RNA-seq and ChIP-seq, we pinpoint Nkx2.2 as a critical downstream target of Nzf2. Specific binding of Nzf2 in the Nkx2.2 gene locus inhibits histone deacetylation by disrupting the HDAC1 repressor complex and reducing deacetylase activity. Furthermore, Nzf2 overrides the inhibitory Notch signaling to initiate OL differentiation. Thus, we propose that the Notch-Nzf2-Nkx2.2 axis is a vital component of OL differentiation timing mechanism, suggesting Nzf2 as a potential therapeutic target for stimulating OL differentiation and boosting myelin repair in demyelinating diseases.

LLM4CAD: Multimodal Large Language Models for Three-Dimensional Computer-Aided Design Generation

Abstract The evolution of multimodal large language models (LLMs) capable of processing diverse input modalities (e.g., text and images) holds new prospects for their application in engineering design, such as the generation of 3D computer-aided design (CAD) models. However, little is known about the ability of multimodal LLMs to generate 3D design objects, and there is a lack of quantitative assessment. In this study, we develop an approach to enable LLMs to generate 3D CAD models (i.e., LLM4CAD) and perform experiments to evaluate their efficacy where GPT-4 and GPT-4V were employed as examples. To address the challenge of data scarcity for multimodal LLM studies, we created a data synthesis pipeline to generate CAD models, sketches, and image data of typical mechanical components (e.g., gears and springs) and collect their natural language descriptions with dimensional information using Amazon Mechanical Turk. We positioned the CAD program (programming script for CAD design) as a bridge, facilitating the conversion of LLMs’ textual output into tangible CAD design objects. We focus on two critical capabilities: the generation of syntactically correct CAD programs (Cap1) and the accuracy of the parsed 3D shapes (Cap2) quantified by intersection over union. The results show that both GPT-4 and GPT-4V demonstrate great potential in 3D CAD generation by just leveraging their zero-shot learning ability. Specifically, on average, GPT-4V outperforms when processing only text-based input, exceeding the results obtained using multimodal inputs, such as text with image, for Cap 1 and Cap 2. However, when examining category-specific results of mechanical components, the prominence of multimodal inputs is increasingly evident for more complex geometries (e.g., springs and gears) in both Cap 1 and Cap 2. The potential of multimodal LLMs to improve 3D CAD generation is clear, but their application must be carefully calibrated to the complexity of the target CAD models to be generated.

Phycobiliprotein content and growth profile of Spirulina platensis in airlift photobioreactor

<p>Microalgae are versatile organisms capable of adapting to diverse environmental conditions, allowing for enhanced biomass production and metabolite synthesis. Due to their rich biochemical composition and rapid growth rate, they are widely utilized across various industries. Microalgae cultivation can be conducted at different scales and methods, including photobioreactors and open ponds. Among various microalgae species, <em>Spirulina platensis</em> is particularly favored in industrial applications and recognized as one of the most significant commercial sources of phycobiliproteins, bioactive compounds unique to blue-green algae. Phycocyanin, a phycobiliprotein derived from <em>S. platensis</em>, is especially valued for its high-added economic potential. This study investigates the production of phycocyanin from <em>S. platensis</em> using an airlift photobioreactor, which offers advantages such as the elimination of mechanical mixing components and the efficient replacement of O<sub>2</sub> and CO<sub>2</sub> through aeration. The specific growth rate of <em>S. platensis</em> was determined to be 0.28 ± 0.01 day<sup>−1</sup>, with a doubling time of 2.47 ± 0.09 days. The phycobiliprotein concentrations were measured as follows: 1.03 ± 0.001 mg/L for phycoerythrin, 10.37 ± 0.08 mg/L for phycocyanin, 6.29 ± 0.24 mg/L for allophycocyanin, and 17.71 ± 1.76 mg/L for total phycobiliprotein. This study successfully cultivated <em>S. platensis</em> in an airlift photobioreactor, demonstrating its potential for efficient production of biomass and bioactive materials.<strong></strong></p>