Effect of loading paths on hydroforming ability of stepped hollow shaft components from double layer pipes

The step hollow shaft components are composed of two layers of different materials, they are formed using tube hydroforming process due to its high strength and rigidity, low weight and flexible profiles, compared to traditional casting, welding, and forming methods. These products are effectively used in industries such as the automotive, shipbuilding, aerospace and defense, and oil and gas sectors. The success of various double layer pipe hydroforming process depends on several factors, with the most important being the internal pressure path and axial loading path. This paper presents research on the effect of input loading paths on the hydroforming ability of a different two-layer metal structure - an outer layer of SUS304 stainless steel and an inner layer of CDA110 copper - using 3D numerical simulations on Abaqus/CAE software. Output criteria were used to evaluate the forming ability of the formed components, including Von Mises stress, Plastic strain component (PEmax), wall thinning, and pipe profile, based on which the input loading paths were combined during the forming process. These output criteria allow for more accurate predictions of material behavior during the hydroforming process, as well as deformation and stress distribution. This can support the design process, improve product quality, reduce errors, and increase production efficiency. The research results can be applied as a basis for optimizing load paths for the next experimental step in the near future, for undergraduate and graduate training, as well as allowing designers and engineers to optimize the process of hydroforming of different 2-layer tubes, reducing costs, improving accuracy, flexible design, minimizing risks, and increasing efficienc

Theoretical predictions of melting behaviors of hcp iron up to 4000 GPa

The high-pressure melting diagram of iron is a vital ingredient for the geodynamic modeling of planetary interiors. Nonetheless, available data for molten iron show an alarming discrepancy. Herein, we propose an efficient one-phase approach to capture the solid-liquid transition of iron under extreme conditions. Our basic idea is to extend the statistical moment method to determine the density of iron in the TPa region. On that basis, we adapt the work-heat equivalence principle to appropriately link equation-of-state parameters with melting properties. This strategy allows explaining cutting-edge experimental and ab initio results without massive computational workloads. Our theoretical calculations would be helpful to constrain the chemical composition, internal dynamics, and thermal evolution of the Earth and super-Earths

Vietnamese Word Segmentation with CRFs and SVMs: An Investigation

PACLIC 20 / Wuhan, China / 1-3 November, 200

A THEORETICAL STUDY ON CHEMICAL BONDING AND INFRARED SPECTRA OF SinM (M = Sc, Y; n = 1-10) CLUSTERS

In this paper, we applied the B3P86 method and DGDZVP basis set to investigate electronic properties and infrared (IR) spectra for SinM (M = Sc, Y; n = 1-10) clusters. The NBO analyses show that electron transfers from the dopant atoms to silicon frame of the SinM clusters. It is remarkable that the Si-M bond is mainly formed by the overlaps of the 3s-AOs and 3p-AOs of Si atoms, and 3d-AOs and 4s-AOs of Sc (or 4d-AOs and AO-5s of Y). The chemical bonds in the SiM and Si2M clusters are dominated by the covalent character including sigma and pi bonds. In addition, the analysis of the IR spectra suggests that the vibrational modes of SinM clusters are delocalized over the whole cluster. Moreover, the high-frequency and strong-intensity modes usually involve the vibrations of the dopant atoms. The results of this work provide fundamental information for experimental studies on transition-metal doped silicon clusters

The role of green finance, eco-innovation, and creativity in the sustainable development goals of ASEAN countries

Recently, sustainable development has become a global requirement. Every country strives to achieve this essential goal, and this attracts the attention of researchers and policymakers. This study investigates the impact of green finance, eco-innovation, and creativity on the sustainable development goals in ASEAN countries. Using CUP-FM and CUP-BC techniques, the study examines the association between variables, and finds that green finance (such as green credit), renewable energy production, eco-innovation, and creativity, have positive associations with sustainable development goals. The control variable, economic growth, has a negative association with sustainable development goals. Based on the evidence, the ASEAN region must increase the quantity of green bonds as a part of green finance. This financial measure would guarantee adequate returns for private investors

Factors affecting the adoption of climate-smart aquaculture (CSAq) in the North Central Coast of Vietnam

Climate-smart aquaculture (CSAq) is considered an appropriate and effective adaptation approach for the coastal aquaculture sector under the climate change phenomenon. This study, applying probit model, aims to assess the influence of several factors on the farmers’ decision to apply CSAq practices in extensive coastal shrimp farming. Data were collected from interviews with 200 households who have both already applied and have yet to apply CSAq practices in five coastal districts of Thanh Hoa Province. The results showed six key factors that influenced the decision of the farmers to apply CSAq practices: availability of household labor; access to information on CSAq practices; market price of products applying CSAq practices; economic efficiency; ability to ensure food security; and improved pond environment when applying CSAq practices. These factors explained 69.41% of their decision to apply CSAq, among which economic efficiency had the greatest impact (30.2%). Market prices and access to information about CSAq are also important factors with respective levels of influence at 16.0% and 14.9%. The result implies that strengthening access to CSAq information and improving technical understanding of CSAq practices are important solutions to upscale CSAq in the North Central Coast of Vietnam

Dynamic association between energy transition technologies, renewable energy production, trade openness, green investment, carbon tax, and carbon neutrality: empirical evidences from China

The existing millennium documents the most adverse consequences of global warming which in contrast to pre-industrial era are more devastating. Thus, these prevailing consequences raise numerous concerns regarding the well-being of future and current generation. Scholars, in this regard, are putting efforts punctiliously towards methods that could halt the surging emissions. This paper also attempts to contributes to existing literature by reporting the empirical evidences regarding the role of energy transition technologies, renewable energy production (REP), trade openness, green investment, and carbon taxes in carbon neutrality in Chinse economy covering the time span of 1980–2020. By employing Dynamic Auto-regressive Distributed Lags (DARDL) model to check the association, findings exposed that electricity production from water sources, electricity production from solar sources, REP, trade openness, green investment, and carbon taxes are negatively correlated with CO2 emissions. Study offers policymakers a help in formulating policies related to achieve carbon neutrality using renewable sources of energy production, carbon taxes, and green investmen

Effect of Silver Nanowire Dimension to Ammonia Adsorption of Graphene-silver Nanowires Hybrid

In this report, we study the effect of silver nanowires (AgNws) dimension to electrical properties of rGO/AgNws hybrid. The alteration of these electrical properties leads the difference of ammonia sensibility of the rGO/AgNws hybrid based sensing devices. When the rGO is accompanied by AgNws of different sizes from \sim 500$~\text{nm to } 10\;\mum, the ammonia sensitivity of these hybrids change from 60% to 340% alteration compared with the bare rGO material

Seasonal Prediction of Surface Air Temperature across Vietnam Using the Regional Climate Model Version 4.2 (RegCM4.2)

To investigate the ability of dynamical seasonal climate predictions for Vietnam, the RegCM4.2 is employed to perform seasonal prediction of 2 m mean (T2m), maximum (Tx), and minimum (Tn) air temperature for the period from January 2012 to November 2013 by downscaling the NCEP Climate Forecast System (CFS) data. For model bias correction, the model and observed climatology is constructed using the CFS reanalysis and observed temperatures over Vietnam for the period 1980–2010, respectively. The RegCM4.2 forecast is run four times per month from the current month up to the next six months. A model ensemble prediction initialized from the current month is computed from the mean of the four runs within the month. The results showed that, without any bias correction (CTL), the RegCM4.2 forecast has very little or no skill in both tercile and value predictions. With bias correction (BAS), model predictions show improved skill. The experiment in which the results from the BAS experiment are further successively adjusted (SUC) with model bias at one-month lead time of the previous run showed further improvement compared to CTL and BAS. Skill scores of the tercile probability forecasts were found to exceed 0.3 for most of the target months