Hasil untuk "Mechanical industries"

A. Moghadam, E. Omrani, P. Menezes et al.

K.J. Rajimon, Rajiv Gandhi Gopalsamy

Perovskite, oxide, organic, and dye-sensitised solar cells are studied from 2015 to 2025, and their current standing and future Mott-Schottky (MS) analysis in photovoltaic (PV) research are highlighted in this review. The incorporation of MS characterisation methodology with solar cell capacitance simulator one dimension (SCAPS-1D) simulations, ab-initio calculations, impedance spectroscopy, and nascent data-driven models is addressed. The MS approach will always be at the forefront in the extraction of the flat band potential, doping concentration, depletion region width, and built-in potential. This is the link between the energetics of the semiconductors and the charge transport of the solar cells and other PV. With MS-validated doping profile optimisation, interface engineering achieves (37.66%) power conversion efficiencies, 1.52 V (open-circuit voltages) and fill factors above (87%). Unfortunately, there are limitations of the frequency-dependent capacitance, parasitic elements, trap states, and non-ideal depletion layer of some architectures, like organic and hybrid ones. The MS and simulations to be used together, and machine learning adoption and analytical models to improve the electronic characterisation, have the potential to resolve the problems. This study offers a critical evaluation of current methods and inherent constraints in MS analysis, offering a strategic framework for the systematic design of efficient, durable, and sustainable solar technologies.

Yichao Li, Xianrong Huang, Lijian Zeng et al.

Yongjian Sun, Jian Wang, Xiaohong Wang

Kiran Golwalkar

Nathan Lane

I study the impact of industrial policies on industrial development by considering an important episode during the East Asian miracle: South Korea's heavy and chemical industry (HCI) drive, 1973--1979. Based on newly assembled data, I use the introduction and termination of industrial policies to study their impacts during and after the intervention period. (1) I reveal that heavy-chemical industrial policies promoted the expansion and dynamic comparative advantage of directly targeted industries. (2) Using variation in exposure to policies through the input-output network, I demonstrate that the policy indirectly benefited downstream users of targeted intermediates. (3) The benefits of HCI persisted even after the policy ended, as some results were slower to appear. The findings suggest that the temporary drive shifted Korean manufacturing into more advanced markets and supported durable change. This study helps clarify the lessons drawn from the East Asian growth miracle. JEL Codes: L5, O14, O25, N6. Keywords: industrial policy, East Asian miracle, economic history, industrial development, Heavy-Chemical Industry Drive, Heavy and Chemical Industry Drive.

Sathish Krishna Anumula, Sivaramkumar Ponnarangan, Faizal Nujumudeen et al.

A mix of intelligent systems and robotics is making engineering industries much more efficient, precise and able to adapt. How artificial intelligence (AI), machine learning (ML) and autonomous robotic technologies are changing manufacturing, civil, electrical and mechanical engineering is discussed in this paper. Based on recent findings and a suggested way to evaluate intelligent robotic systems in industry, we give an overview of how their use impacts productivity, safety and operational costs. Experience and case studies confirm the benefits this area brings and the problems that have yet to be solved. The findings indicate that intelligent robotics involves more than a technology change; it introduces important new methods in engineering.

Arthur Bouffandeau, Sabine Bensamoun, Robert Schleip et al.

Background: Palpation is the most widely used approach to empirically assess the mechanical properties of superficial tissues. While elastography is used for volume measurements, it remains difficult to assess skin properties with non-invasive methods. This study aimed to compare the performances of an impact-based analysis method (IBAM) consisting in studying the dynamic response of a punch in contact with the tissue with other approaches available on the market. Materials and Methods: IBAM consists in analyzing the time dependent force signal induced when a hammer instrumented with a force sensor impacts a cylindrical punch placed in contact with soft tissue. Sensitivities to stiffness changes and to spatial variations were compared between IBAM and four other mechanical surface characterization techniques: IndentoPro (macroindentation), Cutometer (suction), MyotonPro (damped oscillation) and Shore Durometer (durometry) using soft tissue phantoms based on polyurethane gel. Results: For stiffness discrimination in homogeneous phantoms, IBAM was slightly better than IndentoPro and MyotonPro (by 20 % and 35 % respectively), and outperformed the Shore Durometer and Cutometer by a factor of 2 to 4. Furthermore, for stiffness and thickness variations in bilayer phantoms, the axial sensitivity of IBAM was between 2.5 and 4.5 times better than that of MyotonPro and IndentoPro. In addition, the Cutometer appeared to be severely limited by its measurement depth. Conclusion: IBAM seems to be a promising technique for characterizing the mechanical properties of soft tissue phantoms at relatively low depth after future ex vivo and in vivo validation studies with biological tissues (with both animal and in human experiments). This work could pave the way to the development of a decision support system in the field of dermatology and cosmetics.

E. Tianlong, Kai Qin, Zhao Liu et al.

Abstract Ultra-high-voltage (UHV) autotransformers are widely employed in long-distance power transmission systems. Their operation involves complex energy conversion and coupling mechanisms, including high-intensity magnetic induction energy and strong induced currents. From the perspective of power systems and automation control, it is essential to construct a comprehensive equivalent control circuit for UHV autotransformers, integrating the analysis of induced current and magnetic flux density into the domain of analog electronics. Numerical analysis has become a core approach for investigating the external thermal physical characteristics of transformer power and various thermal management strategies. In this paper, the Message Passing Interface (MPI) and Portable, Extensible Toolkit for Scientific Computation (PETSc) parallel computing framework is adopted to compute and analyze the electro-thermal coupling in a UHV autotransformer. The dielectric loss of transformer components is thoroughly examined. A linear numerical simulation method for evaluating dielectric loss is assessed through parallel computation and validated via the design of a three-dimensional coupling model for leakage flux and core temperature rise. The dielectric loss calculation is applied to the transformer. Magnetostriction measurements under rated output power and various current and voltage conditions reveal the correlation between the coupled data and the thermal topology. The MPI-PETSc framework significantly enhances the computational efficiency of three-dimensional electro-thermal coupling problems in UHV autotransformers through distributed computing and efficient numerical solving, making it suitable for large-scale, high-precision engineering simulations.

Kishor B. Shingare, Suhas Alkunte, Baosong Li et al.

Owing to their superior electro-thermo-mechanical properties, the significance of interpenetrating phase composites (IPCs) in various industries is in high demand. IPCs, characterized by infiltrating metal, ceramic, and polymer phases, provide various advantages, including a balanced mixture of strength, stiffness, and toughness, excellent thermal characteristics, wear resistance, and flexibility in microstructure and processing routes. This comprehensive review explores the realm of multifunctional reinforcing phases, specifically focusing on their integration into 3D printed composites. Within this context, the IPCs with a special spotlight on captivating world of Triply Periodic Minimal Surface (TPMS) and other cellular/lattice architectures wherein two core themes are presented and dissected: TPMS-based IPCs, which collaboratively amplify properties of another phase and interpenetrating piezoelectric phase composites (IP2Cs), which offer special advantages over conventional ones. We compiled comprehensive data on IPCs, emphasizing their effective properties, mechanical performance, fatigue and fracture behavior, energy absorption capacity, and coupled electromechanical characteristics. Furthermore, the commercial applications of architectured IPCs across industries are highlighted, along with a critical analysis of current research, identifying gaps and challenges. It highlights their pivotal role in advancing technology and addressing contemporary challenges while illuminating the uncharted possibilities presented by TPMS cellular structures in the dynamic landscape of 3D printing.

Heth Sethia, Abhishek Priyam

The use of hydrogen fuel cells has greatly increased in recent years. Advanced fuel cells are efficiently addressing the needs of portable power, backup power, and even modular power fuel cells. It has also been used to power cars and other vehicles. Hydrogen fuel cells are now specialized under the name portable power modules to highlight their newly discovered vehicle-mountable outboard engines. This review also targets the other issues of handling and encasing hydrogen fuel in specialized containers. All these gaps that revolve around the modern world are intertwined with one advancing vehicle engine to fix the ever-increasing global warming levels. Challenges faced by cost, storage, and infrastructure barriers are addressed, in addition to technological advancements in catalyst effectiveness, membrane technology, and hydrogen supply logistics. The report ends with a visionary outlook, outlining research avenues to drive the shift to a hydrogen economy.

M. A. Kashfipour, N. Mehra, Jiahua Zhu

David Wichner, Jeffrey Wishart, Jason Sergent et al.

Safety Management Systems (SMSs) have been used in many safety-critical industries and are now being developed and deployed in the automated driving system (ADS)-equipped vehicle (AV) sector. Industries with decades of SMS deployment have established frameworks tailored to their specific context. Several frameworks for an AV industry SMS have been proposed or are currently under development. These frameworks borrow heavily from the aviation industry although the AV and aviation industries differ in many significant ways. In this context, there is a need to review the approach to develop an SMS that is tailored to the AV industry, building on generalized lessons learned from other safety-sensitive industries. A harmonized AV-industry SMS framework would establish a single set of SMS practices to address management of broad safety risks in an integrated manner and advance the establishment of a more mature regulatory framework. This paper outlines a proposed SMS framework for the AV industry based on robust taxonomy development and validation criteria and provides rationale for such an approach. Keywords: Safety Management System (SMS), Automated Driving System (ADS), ADS-Equipped Vehicle, Autonomous Vehicles (AV)

Jinbo Wen, Jiawen Kang, Dusit Niyato et al.

Industrial Cyber-Physical Systems (ICPSs) are an integral component of modern manufacturing and industries. By digitizing data throughout product life cycles, Digital Twins (DTs) in ICPSs enable a shift from current industrial infrastructures to intelligent and adaptive infrastructures. Thanks to data process capability, Generative Artificial Intelligence (GenAI) can drive the construction and update of DTs to improve predictive accuracy and prepare for diverse smart manufacturing. However, mechanisms that leverage Industrial Internet of Things (IIoT) devices to share sensing data for DT construction are susceptible to adverse selection problems. In this paper, we first develop a GenAI-driven DT architecture in ICPSs. To address the adverse selection problem caused by information asymmetry, we propose a contract theory model and develop a sustainable diffusion-based soft actor-critic algorithm to identify the optimal feasible contract. Specifically, we leverage dynamic structured pruning techniques to reduce parameter numbers of actor networks, allowing sustainability and efficient implementation of the proposed algorithm. Numerical results demonstrate the effectiveness of the proposed scheme and the algorithm, enabling efficient DT construction and updates to monitor and manage ICPSs.

Md Bokhtiar Al Zami, Shaba Shaon, Vu Khanh Quy et al.

Industrial networks are undergoing rapid transformation driven by the convergence of emerging technologies that are revolutionizing conventional workflows, enhancing operational efficiency, and fundamentally redefining the industrial landscape across diverse sectors. Amidst this revolution, Digital Twin (DT) emerges as a transformative innovation that seamlessly integrates real-world systems with their virtual counterparts, bridging the physical and digital realms. In this article, we present a comprehensive survey of the emerging DT-enabled services and applications across industries, beginning with an overview of DT fundamentals and its components to a discussion of key enabling technologies for DT. Different from literature works, we investigate and analyze the capabilities of DT across a wide range of industrial services, including data sharing, data offloading, integrated sensing and communication, content caching, resource allocation, wireless networking, and metaverse. In particular, we present an in-depth technical discussion of the roles of DT in industrial applications across various domains, including manufacturing, healthcare, transportation, energy, agriculture, space, oil and gas, as well as robotics. Throughout the technical analysis, we delve into real-time data communications between physical and virtual platforms to enable industrial DT networking. Subsequently, we extensively explore and analyze a wide range of major privacy and security issues in DT-based industry. Taxonomy tables and the key research findings from the survey are also given, emphasizing important insights into the significance of DT in industries. Finally, we point out future research directions to spur further research in this promising area.

Neave O'Clery, Juan Chaparro, Andres Gomez-Lievano et al.

What drives formal employment creation in developing cities? We find that larger cities, home to an abundant set of complex industries, employ a larger share of their working age population in formal jobs. We propose a hypothesis to explain this pattern, arguing that it is the organised nature of formal firms, whereby workers with complementary skills are coordinated in teams, that enables larger cities to create more formal employment. From this perspective, the growth of formal employment is dependent on the ability of a city to build on existing skills to enter new complex industries. To test our hypothesis, we construct a variable which captures the skill-proximity of cities' current industrial base to new complex industries, termed 'complexity potential'. Our main result is that complexity potential is robustly associated with subsequent growth of the formal employment rate in Colombian cities.

Vincenzo Lunetto, Dario Basile, Valentino Razza et al.

This study investigates active filling friction stir repair (AF-FSR) and passive filling friction stir repair (PF-FSR) for repairing AISI 304 stainless steel sheets, focusing on addressing the challenges posed by high melting point metals. The research involved repairing overlapping 2 mm thick sheets with pre-drilled holes of 2, 4, and 6 mm diameters, simulating broken components. Various process parameters, including rotational speed, dwell time, and the use of metal fillers, were tested to evaluate their impact on repair quality. The results demonstrated that PF-FSR provided superior mechanical strength to AF-FSR, particularly for larger pre-hole diameters. PF-FSR achieved higher shear tension strength due to better defect filling and reduced void formation, with shear tension strengths exceeding 25 kN for larger pre-holes and lower variability in strength measurements. AF-FSR was less effective for larger pre-holes, resulting in significant voids and reduced strength. Microstructural analysis revealed that PF-FSR facilitated more efficient material mixing and filling, minimizing unrepaired regions. However, excessive rotational speeds and dwell times in PF-FSR led to deformation and flash formation, highlighting the need for optimal parameter selection. Although further studies are needed, this study confirms the feasibility of FSR techniques for repairing small defects in AISI 304 steels, offering valuable insights for sustainable manufacturing practices in industries such as automotive and aerospace, where efficient and reliable repair methods are critical.

Huiping Wu, Zhaohan Shen, Wei Yu et al.

Lithium–oxygen (Li–O2) batteries with ultra-high theoretical specific energy (3500 Wh kg−1) have attracted significant attention, but the sluggish electrochemical processes of discharge product Li2O2 lead to poor cycling stability. Redox mediators (RMs) as soluble catalysts are widely used to assist with the electrochemical formation/decomposition of Li2O2. However, the shuttle effect of RMs causes severe deterioration of both RMs and Li metal anodes. Herein, for the first time we synthesize a lithiated zeolite-based protective layer on Li anodes to mitigate the shuttle effect of 2,2,6,6-tetramethylpiperidinyloxy (TEMPO) in Li–O2 batteries. The protective layer successfully blocks the migration of TEMPO toward the Li anode owing to the angstrom-level aperture size of lithiated zeolite. Due to the excellent redox-mediator-sieving capability of the protective layer, the cycle life of the Li−O2 batteries is significantly prolonged more than ten times at a current density of 250 mA g−1 and a limited capacity of 500 mA h g−1. This work demonstrates that the lithiated zeolite-based protective layer capable of molecular sieving is a facile and scalable way to mitigate the shuttle effect of RMs in Li–O2 batteries.

Hiba Ismaeel, Talib Albayati, Hayder Dhahad et al.

In this study, mesoporous silica nanoparticles (MSNs) with a hexagonal structure and large surface area were synthesized via a sol-gel method. The properties of the synthesized MCM-41 catalyst were characterized using BET, EDX, XRD, and FTIR analyses. The results showed that the MCM-41 had a high surface area of 966 m2/g and large pore volume of about 0.91 cm3/g. Sunflower oil was converted to biodiesel in a batch reactor at different temperatures (40, 50, 60 °C), methanol-to-oil molar ratios (6:1, 9:1, 12:1), catalyst loadings (0.7, 0.9, 1.25 wt%), and reaction times (up to 80 min) using the prepared catalyst under atmospheric pressure. The biodiesel yield was found to reduce when the reaction time exceeded 1 hour despite maintaining the catalyst. The maximum biodiesel yield of 45% was obtained under optimal conditions of a 9:1 methanol-to-oil ratio, 1.25 wt% catalyst loading, 60 °C temperature, and 60 min reaction time. GC-MS analysis characterized the biodiesel composition and properties. The synthesized biodiesel showed improved properties compared to conventional fuels, with linoleic acid methyl ester (C17H34O2, 25.93%) as the main component. The MCM-41 catalyst exhibited remarkable catalytic activity and could be recovered, regenerated, and reused, reducing reaction costs. This makes it a potential alternative to homogeneous catalysts that complicate product separation.

X. L. Xu, M. Karakus