Hasil untuk "Mechanical industries"

S. Prasad, R. Asthana

Bandar AlMangour, Jenn-Ming Yang

Eman M. Zayed, Abdulrahman I. Alateyah, Waleed H. El‐Garaihy et al.

ABSTRACT Severe Plastic Deformation (SPD) is a widely recognized method for producing ultrafine‐grained (UFG) and nano‐structured materials with superior mechanical properties by imposing high strains without the need for alloying elements or secondary reinforcements. Although SPD techniques for bulk and sheet materials have been extensively developed, recent advancements have focused on creating effective SPD methods specifically designed for tubular samples. These techniques are critical for industries where lightweight, high‐strength tubular components are essential, such as aerospace, automotive, and biomedical sectors. Machine learning (ML) approaches have emerged as powerful tools for optimizing SPD parameters and predicting material behavior. ML involves constructing systems capable of analyzing and identifying patterns in data to make informed decisions, such as supervised and unsupervised learning, which analyze training data to reveal relationships and trends. When dealing with small datasets, cross‐validation (CV), particularly k‐fold CV, is a reliable technique to prevent overfitting and enhance model robustness. ML and statistical analysis were employed to predict and optimize the input parameters in terms of the plastic strain (PS) and the impact on the improvement of the mechanical properties. This review provides a comprehensive analysis of SPD processes tailored for tubular materials, including methods such as High‐Pressure Tube Twisting (HPTT), Accumulative Spin Bonding (ASB), and Parallel Tubular Channel Angular Pressing (PTCAP). Each method is examined in terms of deformation behavior, die design, and microstructural evolution. Additionally, the review addresses critical research gaps, explores potential industrial applications, and highlights how advancements in ML can enhance the understanding and application of SPD techniques, offering insights into scaling up these processes for large‐scale production.

Edgar Carrejo, Rhonald Ortega, Kai Lan et al.

Abstract The pulp and paper industry is a promising yet underexplored platform for large-scale carbon dioxide removal (CDR) due to its use of biogenic feedstocks and production of concentrated CO2 emissions from point sources. This study presents the first comprehensive life cycle assessment (LCA) of retrofitting an amine-based carbon capture and storage (CCS) system into a representative virgin kraft pulp and paper mill in the Southeastern U.S. We evaluate carbon removal across five system configurations, applying both static and dynamic LCA methods under multiple functional units: CO2 captured, biomass input, and paper output. Results show that CCS retrofits can convert a conventional mill from a net emitter into a net carbon sink, with total removal efficiencies from 17% to 92% (metric tonnes of CO2 removed per metric tonne of CO2 available for removal under selected boundary conditions). When carbon removal is normalized to the quantity of biogenic CO2 captured—a narrow, gate-to-gate system boundary that considers only CCS facility emissions—removal efficiencies reached as high as 92%. The use of such narrow boundaries aligns with precedents in traditional LCA methodology, where gate-to-gate assessments are commonly applied to isolate process-level performance and allocate emissions accordingly, providing a consistent basis for comparison across technologies. Under broader cradle-to-grave boundaries—which begin tracking carbon at the point of its physical removal from the atmosphere via photosynthesis in the forest, and extend to include upstream forest operations, mill-wide emissions, and downstream product decomposition—efficiencies declined, ranging from 17% to 46% under static assumptions and dropping to 12% when accounting for dynamic biogenic carbon fluxes over time. These results underscore how system boundary definitions influence reported outcomes, while also illustrating the complementary roles of narrow and broad perspectives for different decision-making contexts.

Jake Morris-Campbell, James Annesley

Shoukat Ali Noonari, Muiz Asghar, Sagheer Ahmed et al.

The main aim of this paper is to design dual-axis auto tracking system for the utilization of solar energy to maximize power efficiency and optimizing solar radiation capture. By constantly adjusting the direction of solar panels, the system significantly improves energy harvesting and boosts overall efficiency, marking a significant advancement in renewable energy technology. The evolution of dual-axis tracking systems describes a transformative approach to solar energy optimization by dynamically aligning photovoltaic panels with the sun’s movement. The main aim of this paper is also to maximize energy capture and improving efficiency by design, implementation and performance evaluation of a dual-axis solar tracking system. The system tracks the sun's azimuthal and altitudinal shifts throughout the day using precision sensors and adaptive control algorithms to guarantee ideal panel alignment. A sturdy mechanical framework, efficient actuation mechanisms, and real-time monitoring interfaces form the foundation of the system, enabling reliable operation under varying environmental conditions. Experimental results indicated an increase in solar energy collection, with efficiency gains of up to 30% compared to fixed solar panel setups.  These results findings emphasize the massive potential of dual-axis tracking systems in advancing renewable energy solutions, paving the way for more efficient and sustainable solar energy utilization.

Komal Chhikara, Sinduja Suresh, Scott Morrison et al.

A variety of 3D volumetric scanners and smart-device applications are currently being used in podiatry for recording virtual foot data. The accuracy and reliability of these devices vary, resulting in a large variation in the quality of foot scans used for orthotic design. While it is widely believed that a higher quality scanner yields a better scan and thus is expected to produce a more accurate orthotic design, the direct impact of scanning quality on orthotic design has not yet been tested. Therefore, in this study, three commonly used industrial 3D scanners with varying output qualities were used to obtain foot scans of three participants in two weight-bearing conditions. A total of 54 foot scans were obtained, out of which 18 were used to design orthotic insoles using commercial software (FitFoot360). We found variation in the quality of foot scans produced by the different scanners (61.75 ± 2.23% similarity of the foot scans showing a deviation of less than ±1 mm). However, there were no significant differences in the designed foot orthoses within the same weight-bearing condition (83.59 ± 1.97% similarity of the orthotic designs showing a deviation of less than ±1 mm). The medial arch height and heel width differed significantly only when the weight-bearing condition was changed. The findings from this study suggest that the industrial design and production of an orthotic insole using current methods does not depend on the scanning quality of the scanner used but is dependent on the extent of weight bearing.

Vasileios Papageorgiou, Gabriel Mansour, Ilias Chouridis

Additive Manufacturing is a rapidly developing technology that enables the fabrication of objects with complex geometries and high levels of customization while keeping the prototyping costs relatively low. In recent years, its application has grown to include the fabrication of end-use parts, creating new opportunities in industries such as the automotive, aerospace, mechanical, and hydraulic engineering industries. The present research paper focuses on the fabrication and evaluation of 3D-printed operational end-use parts of a water pump, which were originally made from cast iron. This approach aims to determine whether AM can be an alternative for metal parts in operational systems such as water pumps. In particular, the impeller of a centrifugal pump is remanufactured using material extrusion AM technology with PPS-CF composite polymer as a fabrication material. Subsequently, the surface roughness of the two parts is measured, and the performance of each part is predicted by creating a CFD model. Additionally, the printed part is compared to the original part by conducting a centrifugal pump performance test for each impeller. The results show that the 3D-printed impeller achieves an approximate 15% increase in overall efficiency compared to the original impeller.

A. Alawar, A. M. Hamed, K. Al-Kaabi

Xiaozhen Li, Weixu Zhang, Xiaobing Cai

Thermal barrier coatings (TBCs) play an important role in the thermal protection of alloy components in high temperature industries. Accurately characterizing and extracting mechanical properties of TBCs are crucial for structural design, performance optimization, failure prediction and lifespan assessment. Indentation test is an effective method for experimentally obtaining the mechanical properties and provides valuable insights into the elastic, plastic and fracture behaviors of TBCs at elevated temperatures. This paper aims to provide an overview of indentation mechanical evaluation of TBCs, including the mechanical properties at different temperatures, the mechanical property anisotropy, the microstructural and mechanical behavior under thermal exposure and/or thermal cycling, as well as the comparison of functional performance between conventional and nanostructured TBCs. Furthermore, this paper points out the main challenges and future directions from indentation investigations of TBCs. Finally, this paper is summarized and prospected.

Hom N. Dhakal, Sakib Hossain Khan, Ibrahim A. Alnaser et al.

Abstract This article presents a comprehensive review of the advancements in the use of Date Palm Fiber (DPF) reinforced composites, highlighting their mechanical, thermal, and morphological properties and the enhancements achieved through various modification techniques. Date palm fibers, a sustainable and biodegradable resource, have garnered significant interest due to their potential in reducing environmental impact across several key industries, including building and construction, automotive, and packaging. The review discusses the effects of hybrid approaches and physical and chemical treatments on the mechanical properties of DPF composites, demonstrating improvements in tensile strength, elasticity, and flexural strength through optimized fiber‐matrix bonding and reduced moisture absorption. Thermal behavior analyses through Thermogravimetric Analysis (TGA), Dynamic Mechanical Analysis (DMA), and thermal conductivity underscore the composites’ suitability for applications requiring high thermal stability and conductivity for insulation applications. Morphological studies reveal that surface‐treated fibers integrate more effectively with various polymeric matrices, leading to enhanced composite performance. The practical applications of DPF composites are explored, emphasizing their role in promoting sustainable manufacturing practices. Challenges such as scalability, cost‐efficiency, and performance consistency are addressed, alongside future perspectives that suggest a promising direction for further research and technological development in the field of natural fiber composites. This review aims to solidify the foundation for ongoing advancements and increase the adoption of DPF composites in commercial applications.

Shriya Shrivastava, Dipen Kumar Rajak, Tilak Joshi et al.

Ceramic matrix composites (CMCs) are a significant advancement in materials science and engineering because they combine the remarkable characteristics of ceramics with the strength and toughness of fibers. With their unique properties, which offer better performance and endurance in severe settings, these advanced composites have attracted significant attention in various industries. At the same time, lightweight ceramic matrix composites (LCMCs) provide an appealing alternative for a wide range of industries that require materials with excellent qualities such as high-temperature stability, low density, corrosion resistance, and excellent mechanical performance. CMC uses will expand as production techniques and material research improve, revolutionizing aerospace, automotive, and other industries. The effectiveness of CMCs primarily relies on the composition of their constituent elements and the methods employed in their manufacturing. Therefore, it is crucial to explore the functional properties of various global ceramic matrix reinforcements, their classifications, and the manufacturing techniques used in CMC fabrication. This study aims to overview a diverse range of CMCs reinforced with primary fibers, including their classifications, manufacturing techniques, functional properties, significant applications, and global market size.

Luis Prieto-Miranda, Jordan D Kern

Although damages to local distribution systems from wind and fallen trees are typically responsible for the largest fraction of electricity outages during hurricanes, outages caused by flooding of electrical substations pose a unique risk. Electrical substations are a key component of electric power systems, and in some areas, the loss of a single substation can cause widespread power outages. Before repairing damaged substations, utilities must first allow floodwaters to recede, potentially leaving some customers without power for weeks following storms. As economic losses from flooding continue to increase in the U.S., there has been increasing attention paid to the potential impacts of flooding on power systems. Yet, this attention has mostly been limited to geospatial risk assessments that identify what assets are in the path of flooding. Here, we present the first major attempt to understand how flooding from hurricanes and other extreme precipitation events affects the dynamic behavior of power networks, including losses of demand and generation, and altered power flows through transmission lines. We use North Carolina, hit by major hurricanes in three of the past seven years, as a test case. Using open-source data of grid infrastructure, we develop a high-resolution direct current optimal power flow model that simulates electricity production and generators and power flows through a network consisting of 662 nodes and 790 lines. We then simulate grid operations during the historical (2018) storm Hurricane Florence. Time series of flooding depth at a discrete set of ‘high water’ mark points from the storm are used to spatially interpolate flooding depth across the footprint area of the storms on an hourly basis. Outages of substations and solar farms due to flooding are translated to location-specific losses of demand and solar power production throughout the network. We perform sensitivity analysis to explore grid impacts as a function of the height of sensitive equipment at substations. Results shed light on the potential for localized impacts from flooding to have wider impacts throughout the grid (including in areas not affected by flooding), with performance tracked in terms of transmission line flows/congestion, generation outputs, and customer outages.

Jun Liu, Jie Xiao, Jihui Yang et al.

Energy storage is important for electrification of transportation and for high renewable energy utilization, but there is still considerable debate about how much storage capacity should be developed and on the roles and impact of a large amount of battery storage and a large number of electric vehicles. This paper aims to answer some critical questions for energy storage and electric vehicles, including how much capacity and what kind of technologies should be developed, what are the roles of short-term storage and long-duration storage, what is the relationship between energy storage and electrification of transportation, and what impact will energy storage have on materials manufacturing and supply chain. Accelerating the deployment of electric vehicles and battery production has the potential to provide terawatt-hour scale storage capability for renewable energy to meet the majority of the electricity need in the United States. However, it is critical to greatly increase the cycle life and reduce the cost of the materials and technologies. Long-lasting lithium-ion batteries, next generation high-energy and low-cost lithium batteries are discussed. Many other battery chemistries are also briefly compared, but 100 % renewable utilization requires breakthroughs in both grid operation and technologies for long-duration storage. New concepts like dual use technologies should be developed.

Zhixin Jia, Qing Wang, Jiang Liu

Fused filament fabrication (FFF) technology is highly favored by various industries as the simplest and most commonly used technology in additive manufacturing. The embedding of continuous fiber-reinforced thermoplastic composites (CFRTC) is a great help to compensate for the mechanical properties of FFF-printed specimens. In this paper, the optimal printing parameters of printed specimens containing continuous carbon fiber-reinforced PLA were investigated by the Taguchi method, full factorial analysis, and the tensile test. Fiber printing layer thickness and fiber printing speed are significant factors. After excluding the influence of fiber overlap, the optimal printing parameters were obtained. When the thickness of the fiber printing layer is 0.05 mm, the speed of the fiber printing nozzle is 250 mm/min, and the temperature of the fiber printing nozzle is 210 °C, the maximum tensile stress of the sample is 189.52 MPa. In this paper, the maximum tensile stress of the specimen printed by different printing parameters can be doubled, which shows the influence of printing parameters on the mechanical properties of the specimen. Compared with the specimen using pure PLA printing, the increase was 703.5%. Then the failure mechanism of 3D-printed CFRTC specimens with different layer thicknesses was investigated by using microstructural morphology and tensile fracture interfacial property analysis. The influence of layer thickness parameters on the interfacial bonding force was revealed. Through analysis, it is found that the lower the thickness of the specimen printing layer, the better the interface bonding force of the specimen, and the minimum layer thickness suitable for FFF independent extrusion printer is found.

Jing Rao, Subin Lee, Gerhard Dehm et al.

Hydrogen embrittlement is common in metallic materials and a critical issue in industries involving hydrogen-related processes. Here we investigate the mechanical response upon hydrogen loading of ferritic Fe-16Cr, Fe-21Cr and Fe-4Al alloys. We use a novel in situ setup for electrochemical backside hydrogen charging during nanoindentation. Single-phase ferritic Fe-Cr binary alloys with high hydrogen diffusivity and low solubility, are ideal for in situ studies during hydrogen charging, particularly the effect of diffusible and lightly trapped hydrogen is targeted. The hardness increases linearly with increasing hydrogen content until a quasi-equilibrium state between hydrogen absorption and desorption is reached while Young's modulus remains unaffected. Above this transient region, the slope of the absolute hardness experiences a drastic decrease. The hardness variation in Fe-21Cr is anisotropic as determined for (100), (110) and (111) oriented grains. Increasing the Cr content enhances the hardening effect in (100) orientation: a 16.7 % hardness increase is observed in Fe-21Cr, while Fe-16Cr, shows an increment of 10.8 %. A Fe-4Al alloy increases slightly in hardness by only 4.3 % at the applied current density of 3 mA/cm2. The hardening effect is caused by enhancing dislocation density, as revealed by studying the cross-section underneath the nanoindentation imprints.

Patricia Kara De Maeijer, Bart Craeye, J. Blom et al.

This state-of-the-art review was aimed to conduct a comprehensive literature survey to summarize experiences of crumb rubber (CR) application in concrete within the last 30 years. It shows that certain gaps prevent obtaining a coherent overview of both mechanical behaviour and environmental impact of crumb rubber concrete (CRC) to object to the stereotypes which prevent to use of CR in concrete in the construction industry. Currently, four major barriers can be distinguished for a successful CR application in the concrete industry: (1) the cost of CR recycling, (2) mechanical properties reduction, (3) insufficient research about leaching criteria and ecotoxicological risks and (4) recyclability of CRC. The application of CR in concrete has certainly its advantages and in general cannot be ignored by the construction industry. CR can be applied, for example, as an alternative material to replace natural aggregates and CRC can be used as recycled concrete aggregates (RCA) in the future. A certain diversity for the CR application can be introduced in a more efficient way when surface treatment and concrete mix design optimization are properly developed for each type of CR application in concrete for possible field applications. The role of CRC should not be limited to structures that are less dependent on strength.

Yúmina Alexandre Zêdo, Ana Luísa Ferreira Andrade Ramos

With globalization and the high competitiveness faced in a business environment, adopting technological solutions to satisfactory respond to an increasingly demanding customer is the watchword for organizations. With technological advances and an increasingly volatile society, it is mandatory for industries to ensure agile production processes capable of responding quickly and assertively to consumer expectations. Industry 4.0 with its technological pillars comes up to boost company to have more flexible and agile processes. This work results of a project developed in an automotive factory that will be producing a new mechanical part. The definition of the best layout of the production line was carried in an instable environment characterized by budget limitations, security and space restrictions that forced the company to study and discuss four possible layouts to define the future line. The goal was to ensure that the line was able to produce 3625 parts/week with an Operational Income of 87%. Moreover, it was also important to consider the cost of implementing a new line in the company. With this study it is proven that in an automotive industry where flexibility is required in an unpredictable environment during a decision-making process, analyzing the impact and possible consequences of every change in a layout definition phase is a great asset, where alteration like adding a conveyor, Automated Guided Vehicle or Robots can be made easy and quickly, and important conclusions can be taken from this analyze with less effort. Finally, 2 criteria were created to examine every variant and a decision was made.

Rytis Maskeliūnas, Raimondas Pomarnacki, Van Khang Huynh et al.

To monitor and handle big data obtained from electrical, electronic, electro-mechanical, and other equipment linked to the power grid effectively and efficiently, it is important to monitor them continually to gather information on power line integrity. We propose that data transmission analysis and data collection from tools like digital power meters may be used to undertake predictive maintenance on power lines without the need for specialized hardware like power line modems and synthetic data streams. Neural network models such as deep learning may be used for power line integrity analysis systems effectively, safely, and reliably. We adopt Q-learning based data analysis network for analyzing and monitoring power line integrity. The results of experiments performed over 32 km long power line under different scenarios are presented. The proposed framework may be useful for monitoring traditional power lines as well as alternative energy source parks and large users like industries. We discovered that the quantity of data transferred changes based on the problem and the size of the planned data packet. When all phases were absent from all meters, we noted a significant decrease in the amount of data collected from the power line of interest. This implies that there is a power outage during the monitoring. When even one phase is reconnected, we only obtain a portion of the information and a solution to interpret this was necessary. Our Q-network was able to identify and classify simulated 190 entire power outages and 700 single phase outages. The mean square error (MSE) did not exceed 0.10% of the total number of instances, and the MSE of the smart meters for a complete disturbance was only 0.20%, resulting in an average number of conceivable cases of errors and disturbances of 0.12% for the whole operation.

Md Ashequl Islam, Nur Saifullah Kamarrudin, Ruslizam Daud et al.

This study aims to summarize the current state of scientific knowledge on factors that contribute to heat generation during the bone drilling process and how these aspects can be better understood and avoided in the future through new research methodologies. Frictional pressures, mechanical trauma, and surgical methods can cause thermal damage and significant micro-fracturing, which can impede bone recovery. According to current trends in the technical growth of the dental and orthopedic industries’ 4.0 revaluation, enhancing drill bit design is one of the most feasible and cost-effective alternatives. In recent years, research on drilling bones has become important to reduce bone tissue damage, such as osteonecrosis (ON), and other problems that can happen during surgery. Reviewing the influence of feed rate, drill design, drill fatigue, drill speed, and force applied during osteotomies, all of which contribute to heat generation, was a major focus of this article. This comprehensive review can aid medical surgeons and drill bit makers in comprehending the recent improvements through optimization strategies for reducing or limiting thermal damage in bone drilling procedures used in the dental and orthopedic industries.