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Transient temperature analysis is involved in the thermal simulation of the heat treatment process, in which the hot metal temperature changes with respect to time from an initial state to the final state. The critical part of the simulation is to determine the heat transfer coefficient (HTC) between the hot part and the quenching medium or quenchant. In liquid quenching, the heat transfer between the hot metal part and water becomes complicated and it is difficult to determine HTC. In the current experimentation a medium carbon steel EN 9 rod with a diameter of 50 mm and length 100 mm was quenched in water and ethylene glycol mixture with different concentrations. A part model was created; meshed and actual boundary conditions were applied to conduct computational fluid dynamics (CFD) analysis. In order to validate CFD analysis the experimental trials were conducted. Experimental results showed a reduced cooling rate for the specimen, and also a reduction in heat-carrying capacity ofMutalikdesai, SachinShinde, TarangNanwatkar, Ravikant
Sustainability is both an ethical responsibility and business concern for the aerospace industry. Military and commercial avionics developers have pushed toward a common standard for interfaces, computing platforms, and software in hopes of having “reusability” and reducing weight with backplane computing architectures which, in theory, would support commonality across aircraft systems. The integrated modular avionics (IMA) and military Future Airborne Capability Environment (FACE) standards are two such examples. They emerged to support common computing architectures for reuse and sustainability concepts, from the beginning of aircraft development to the sundown or mortality phase. Pitfalls of Designing, Developing, and Maintaining Modular Avionics Systems in the Name of Sustainability looks at technological, organizational, and cultural challenges making reuse and IMA platform models difficult to fully realize their sustainability goals. Additionally, it considers the certificationReeve, Tammy
With population aging and life expectancy increasing, elderly drivers have been increasing quickly in the United States and the heterogeneity among them with age is also increasingly non-ignorable. Based on traffic crash data of Pennsylvania from 2011 to 2019, this study was designed to identify this heterogeneity by quantifying the relationship between age and crash characteristics using linear regression. It is found that for elderly driver-involved crashes, the proportion leading to casualties significantly increases with age. Meanwhile, the proportions at night, on rainy days, on snowy days, and involving driving under the influence (DUI) decrease linearly with age, implying that elderly drivers tend to avoid traveling in risky scenarios. Regarding collision types, elderly driver-involved crashes are mainly composed of angle, rear-end, and hit-fixed-object collisions, proportions of which increase linearly, decrease linearly, and keep consistent with age, respectively. The increaseZhang, ZihaoLiu, Chenhui
The development of electric commercial vehicles brought up novel challenges in the design of efficient and reliable air brake systems. The compressor is one of the critical components of the air brake system and is responsible for supplying pressurized air to the brake system. In this study, we aimed to gather essential information regarding the pressure and flow rate requirements for the compressor in the air brake system of electric commercial vehicles. We extensively analyzed the existing air brake systems utilized in conventional commercial vehicles. We examined the performance characteristics of reciprocating compressors traditionally employed in these systems. Recognizing the need for novel compressor designs tailored to electric commercial vehicles, we focused on identifying the specifics such as efficiency, performance characteristics, reliability, and cost of the compressor. Our study utilized theoretical calculations to ascertain the optimal pressure and flow rate parametersDhere, SiddhantGupta, SuryakantKumar, G. C. MohanReddy, Vamsikrishna
In this article, we investigated the effects of material parameters on the clinching joint geometry using finite element model (FEM) simulation and machine learning-based metamodels. The FEM described in this study was first developed to reproduce the shape of clinching joints between two AA5052 aluminum alloy sheets. Neural network metamodels were then used to investigate the relation between material parameters and joint geometry as predicted by FEM. By interpreting the data-driven metamodels using explainable machine learning techniques, the effects of the hard-to-measure material parameters during the clinching are studied. It is demonstrated that the friction between the two metal sheets and the flow stress of the material at high (up to 100%) plastic strain are the most influential factors on the interlock and the neck thickness of the clinching joints. However, their dependence on the material parameters is found to be opposite. First, while the friction between the two metalNguyen, Duc VinhTran, Van-XuanLin, Pai-ChenNguyen, Minh ChienWu, Yan-Jiu
Thermal runaway is a critical safety concern in lithium-ion battery systems, emphasising the necessity to comprehend its behaviour in various modular setups. This research compares thermal runaway propagation in different modular configurations of lithium-ion batteries by analysing parameters such as cell spacing and applying phase change materials (PCMs) and Silica Aerogel. The study at the module level includes experimental validation and employs a comprehensive model considering heat transfer due to thermal runaway phenomena. It aims to identify the most effective modular configuration for mitigating thermal runaway risks and enhancing battery safety. The findings provide valuable insights into the design and operation of modular lithium-ion battery systems, guiding engineers and researchers in implementing best practices to improve safety and performance across various applicationsGarcia, AntonioMonsalve-Serrano, JavierDreif, AminGuaraco-Figueira, Carlos
In the dynamic landscape of battery development, the quest for improved energy storage and efficiency has become paramount. The contemporary energy transition, coupled with growing demands for electric vehicles, renewable energy sources, and portable electronic devices, has underscored the critical role that batteries play in our modern world. To navigate this challenging terrain and harness the full potential of battery technology, a well-defined and comprehensive data strategy resp. knowledge management strategy are indispensable. Conversely, the imminent and rapid progression of artificial intelligence (AI) is poised to have a substantial impact on the forthcoming landscape of work and the methodologies organizations employ for the management of their knowledge management (KM) procedures. Conventional KM endeavors encompass a spectrum of activities such as the creation, transmission, retention, and evaluation of an enterprise’s knowledge over the entire knowledge lifecycle. HoweverBadi, IbtihalBraun, AndreasKallis, Lena
Aluminum and its alloys entered a main role in the engineering sectors because of their applicable characteristics for indispensable applications. To enhance requisite belongings for the components, the composition of variant metal/nonmetal with light metal alloys is essential in the manufacturing industries. To enhance the wear resistance with significant strength property of the aluminum alloy 2024, the reinforcement SiC and fly ash (FA) were added with the designation Al2024 + 10% SiC; Al2024 + 5% SiC + 5% FA; and Al2024 + 10% FA via stir-casting technique. The wear resistance property of the composites was tested in pin-on-disc with a dry-sliding wear test procedure. The experiment trials were designed in Box–Behnken design (BBD) by differing the wear test parameters like % of reinforcement, sliding distance (m), and load (N). The wear tests on casted samples were carried out at the constant velocity of 2 m/sec, such that the corresponding wear rate for the experiment trials wasSivakumar, N.Sireesha, S. C.Raja, S.Ravichandran, P.Sivanesh, A. R.Aravind Kumar, R.
Increasing awareness of the harmful effects on the environment of traditional Internal Combustion Engines (ICE) drives the industry toward cleaner powertrain technologies such as battery-driven Electric Vehicles (EV). Nonetheless, the high energy density of Li-Ion batteries can cause strong exothermic reactions under certain conditions that can lead to catastrophic results, called Thermal Runaway (TR). Hence, a strong effort is being made to understand this phenomenon and increase battery safety. Specifically, the vented gases and their ignition can cause the propagation of this phenomenon to adjacent batteries in a pack. In this work, Computational Fluid Dynamics (CFD) is employed to predict this venting process in an LG18650 cylindrical battery. The shape of the venting cap deformation obtained from experimental results was introduced in the computational model. The ejection of the generated gases was considered to analyze its dispersion in the surrounding volume through a ReynoldsGil, AntonioMicó, CarlosMarco-Gimeno, JavierCastro Espín, Mar
The extension of traction batteries from electric vehicles with supercapacitors is regularly discussed as a possibility to increase the lifetime of lithium-ion batteries as well as the performance of the vehicle drive. The objective of this work was to validate these assumptions by developing a simulation model. In addition, an economic analysis is performed to qualitatively classify the simulation results. Initially, a hybrid energy storage system consisting of battery and supercapacitor was developed. A semi-active hybrid energy storage topology was selected. Subsequently, the selection of use cases as well as the application-specific definition of load cycles took place. In addition, the control strategy was further developed so that a simulation on lifetime was made possible. The end-of-life of the battery cells was defined, according to the USABC guideline values. Based on the data of the respective use case, the control strategy parameter optimization was carried out according toMödl, RomanBraun, AndreasKallis, Lena
Beiker, SvenBock, ThomasTaiber, Joachim
Beiker, SvenRazdan, RahulFavaro, FrancescaTaiber, JoachimSell, Raivo
Beiker, SvenPorcel Magnusson, CristinaWaraniak, John
Lehmann, JohannesMoorehead, StewartMuelaner, Jody E.
Beiker, SvenMuelaner, Jody E.Razdan, Rahul
Coyner, KelleyBittner, JasonLambermont, SergeDe Boer, Niels
Abdul Hamid, Umar ZakirRoth, ChristianNickerson, JeffreyLyytinen, KalleKing, John Leslie
Fang, ChenRazdan, rahulBeiker, SvenTaleb-Bendiab, Amine