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Among the advantages of redundantly actuated mechanisms, one can mention the higher operational robustness, the feasibility of reduced power actuators and the load capacity increase in the mechanism. Focusing on such category of mechanism, the current work proposes a process for modeling and selecting the available actuation modes in accordance with adequate dynamic criteria. Here the modular modeling methodology is employed to formulate the dynamic equations for closed-loop redundantly actuated mechanisms of any topology that can operate even in the 2D- or 3D-spaces. Additionally, this general development is applied to generate dynamic models of the parallel mechanism 2 R R R + R R in the task space. Additionally, some simulations are conducted in order to compare the performance of the parallel mechanism when operating under distinct actuation modes, either keeping or switching between actuation modes during the motion cycle. The chosen metrics are the actuator torques and energy consumption. Moreover, other simulations aim to evaluate the capability of the actuated mechanism to overcome type-II singularities. Finally, this investigation also assesses the suitability of actuation mode indices for the motion planning of the parallel mechanism, which can be useful for control purposes.

DeepSeek-R1 performs reasoning tasks at the same level as OpenAI’s o1 — and is open for researchers to examine. DeepSeek-R1 performs reasoning tasks at the same level as OpenAI’s o1 — and is open for researchers to examine. DeepSeek website seen on an iPhone screen. Credit: Koshiro K/Alamy

In this research, thermal buckling and forced vibration characteristics of the imperfect composite cylindrical nanoshell reinforced with graphene nanoplatelets (GNP) in thermal environments are presented. Halpin–Tsai nanomechanical model is used to determine the material properties of each layer. The size-dependent effects of GNPRC nanoshell is analyzed using modified couple stress theory. For the first time, in the present study, porous functionally graded multilayer couple stress (FMCS) parameter which changes along the thickness is considered. The novelty of the current study is to consider the effects of porosity, GNPRC, FMCS and thermal environment on the resonance frequencies, thermal buckling and dynamic deflections of a nanoshell using FMCS parameter. The governing equations and boundary conditions are developed using Hamilton’s principle and solved by an analytical method. The results show that, porosity, GNP distribution pattern, modified couple stress parameter, length to radius ratio, mode number and the effect of thermal environment have an important role on the resonance frequencies, relative frequency change, thermal buckling, and dynamic deflections of the porous GNPRC cylindrical nanoshell using FMCS parameter. The results of current study can be useful in the field of materials science, micro-electro-mechanical systems and nano electromechanical systems such as microactuators and microsensors.

Additive manufacturing or 3D printing is a rapidly developing technology that has revolutionized the manufacturing sector. In this paper, a review of various manufacturing methods is presented and selected features are compared. Some examples requiring features on the micron-scale are presented.

This research work presents another design of a multi-input multi-output (MIMO) antenna with dual wide operating bands at the millimeter-wave (MMW) region proposed for 5G applications. The design consists of two monopole elements with full size of 26 × 11 mm 2 . The two monopoles are designed to provide dual-band operation at the frequencies 27 GHz and 39 GHz. The mutual coupling between the two elements is studied and optimized to maximally reduce the effect of one element on the other. The S-parameters of the proposed MMW MIMO configuration are simulated using two software and measured using VNA. The results are well agreed with considerable shifting between the measured and the simulated, which can be due to the fabrication tolerance and cable losses. The radiation characteristics are investigated in terms of gain and efficiency. The proposed MIMO manifests acceptable gain that reaches 5 dBi and 5.7 dBi in the first and second bands, respectively, while the radiation efficiency reaches 99.5% and 98.6% over the first and the second bands, respectively. The MIMO performance is also studied where a very low envelope correlation of about 10 –4 is obtained and a diversity gain of about 10 dB over the two operating bands is also achieved. The comparison between simulation and measurement shows the possible potential of the proposed MIMO antenna that makes it feasible for MMW 5G applications.

For the accessory gearbox of aero-engines, the gear transmission system is increasingly pursuing a lightweight design, which leads to flexible vibration of gears. However, the most popular lumped-mass modeling approach cannot capture the flexible vibration of gears, whereas solid element models result in extremely low computational efficiency. Therefore, this paper aims to develop a reduced dynamic model of a gear system to balance the computational accuracy and efficiency. First, the meshing stiffness of the gear pair is calculated based on the loaded tooth contact analysis method, and the meshing element between the driving and driven gears is established. Then, a dynamic model of the gear transmission system is proposed based on the solid elements, and the degrees of freedom of the dynamic model are reduced using the Guyan method. Finally, the reduced dynamic model proposed in this paper is verified through comparison of modal characteristics and dynamic responses on the basis of ANSYS and ADAMS. The results demonstrate that compared with other existing modeling approaches, the proposed dynamic modeling method achieves a favorable balance between computational accuracy and efficiency. Additionally, the tooth flexibility has negligible influence on the low-order modes of the system and the amplitude of the meshing frequencies. This study can provide an effective methodology for establishing dynamic models, offering valuable guidance for subsequent investigations into vibration mechanisms.

With the rapid increase of urbanization and industrialization, particulate matter (PM2.5) concentration has increased significantly. PM2.5 profile forecasting has become one of the critical research areas in environmental control and protection. The early detection of PM2.5 as a pollutant is vital because PM2.5 has a significant impact on human health than other pollutants. This paper proposes a deep neuro-fuzzy prediction system (DNFPS) by amalgamating the deep learning and the fuzzy time series algorithm to forecast the PM2.5 concentration. The proposed predictive model consists of three phases; a data preprocessing algorithm to generate a high-quality dataset, a denoising autoencoder using fully convolutional neural networks (FCNNs) to extract the features from the pollutant time series profile as well as reduce the dimension of the time series dataset, and the type-2 fuzzy time series forecasting (FTSF) method to forecast PM2.5 concentration. The butterfly optimization algorithm (BOA) is integrated with the type-2 FTSF method to improve the prediction accuracy of the proposed method. FTSF-BOA is implemented to fine-tune the length of type-2 fuzzy intervals. Experiments employing Sydney data sets to analyze the performance of DNFPS. DNFPS shows that the proposed model achieves an excellent performance than other standard baseline models. It has lower computational time (training time) than the other traditional baseline deep learning models.

Energy efficient routing protocol selection for Cluster based Underwater Wireless Sensor Network (CUWSN) is aimed to support monitoring and controlling underwater scenarios in the field of Internet of Underwater Things. The crucial requirement of Underwater Wireless Sensor Network (UWSN) is to prolong network lifespan. The aim of this article is to build energy-efficient UWSN that will trim energy expenditure as well as improve performance in the underwater scenario. In the proposed CUWSN, a UWSN architecture is designed, which uses the benefits of cluster head and multi-hop transmission. The proposed CUWSN extends the network lifetime by using multi-hop transmission. The proposed CUWSN model is simulated using QualNet 7.1 simulation tool. In this article, energy consumption, throughput, packet delivery ratio, transmission delay, error signals, and packet loss parameter indicators are considered to investigate the performance of proposed CUWSN. The outcomes of proposed CUWSN exhibit that the AODV routing protocol surpasses the DYMO routing protocol by 80%, the IERP routing protocol by 75%, STAR routing protocol by 47% and ZRP routing protocol by 81% in perspective of energy efficiency. In references to other performance indicators like average path loss and average interference the IERP routing protocol and in case of throughput the ZRP routing protocol performs well among the five routing protocols. Finally, the AODV routing protocol is energy conservative in the proposed CUWSN.

The intention of the present work is to study the stability analysis of heat transfer enhancement occurring due to the influence of significant properties variation of fluids in the presence of thermal radiation with an aid of suspended hybrid nanofluids. The mathematical equations are converted into a pair of self-similarity equations by applying appropriate transformation. Runge Kutta Fehlberg 45th order method is applied to solve the reduced similarity equivalences numerically. The flow and energy transfer characteristics are studied for distinct values of important factors to obtain better perception of the problem. According to graphical results, heat transfer enhancement is higher for larger values of radiation parameter ( R ) and higher values of Prandtl number resulted in heat transfer reduction.