Creep fracture behaviour of SUS304H steel with vanadium addition based on small punch creep testing

The high-temperature creep fracture behaviour and creep strength of SUS 304H containing a minor addition of V were investigated in this study. A series of small punch (SP) creep and uniaxial creep tests were performed at 700 °C. The load and punch displacement rates obtained from the SP creep tests were used to derive conversion equations to determine the equivalent stress and creep strain rates. A converting equation is suggested in this study so that Norton’s secondary power law creep constants obtained from the SP creep testing can be in agreement with those obtained from the uniaxial tensile creep tests. The creep strength of the modified SUS 304H steel containing V was shown to be superior to that without V based on the current results and other available results for type 304H steel.     

Effect of the measurement errors on two one-sided Shewhart control charts for monitoring the ratio of two normal variables

Monitoring the ratio between two random normal variables plays an important role in many industrial manufacturing processes. In this paper, we suggest designing two one-sided Shewhart control charts monitoring this ratio. The numerical results show that the one-sided charts have more advantages compared with the two-sided Shewhart chart proposed previously in the literature. Moreover, we investigate the effect of measurement error on the performance of these control charts where the measurement error is supposed to follow a linear covariate error model. The change of model parameters from an in-control condition to an out-of-control is presented without using a strict assumption about the independence of the shift size from measurement errors. A valuable finding from this study is that taking multiple measurements per item is not an effective way to reduce the negative effect of measurement error on the Shewhart charts' performance.     

Multicompartment Tubular Micromotors Toward Enhanced Localized Active Delivery

A tubular micromotor with spatially resolved compartments is presented toward efficient site-specific cargo delivery, with a back-end zinc (Zn) propellant engine segment and an upfront cargo-loaded gelatin segment further protected by a pH-responsive cap. The multicompartment micromotors display strong gastric-powered propulsion with tunable lifetime depending on the Zn segment length. Such propulsion significantly enhances the motor distribution and retention in the gastric tissues, by pushing and impinging the front-end cargo segment onto the stomach wall. Once the micromotor penetrates the gastric mucosa (pH ≥ 6.0), its pH-responsive cap dissolves, promoting the autonomous localized cargo release. The fabrication process, physicochemical properties, and propulsion behavior are systematically tested and discussed. Using a mouse model, the multicompartment motors, loaded with a model cargo, demonstrate a homogeneous cargo distribution along with approximately four-fold enhanced retention in the gastric lining compared to monocompartment motors, while showing no apparent toxicity. Therapeutic payloads can also be loaded into the pH-responsive cap, in addition to the gelatin-based compartment, leading to concurrent delivery and sequential release of dual cargos toward combinatorial therapy. Overall, this multicompartment micromotor system provides unique features and advantages that will further advance the development of synthetic micromotors for active transport and localized delivery of biomedical cargos.     

Hydration-Effect-Promoting Ni–Fe Oxyhydroxide Catalysts for Neutral Water Oxidation

Oxygen evolution reaction (OER) catalysts that function efficiently in pH-neutral electrolyte are of interest for biohybrid fuel and chemical production. The low concentration of reactant in neutral electrolyte mandates that OER catalysts provide both the water adsorption and dissociation steps. Here it is shown, using density functional theory simulations, that the addition of hydrated metal cations into a Ni–Fe framework contributes water adsorption functionality proximate to the active sites. Hydration-effect-promoting (HEP) metal cations such as Mg²⁺ and hydration-effect-limiting Ba²⁺ into Ni–Fe frameworks using a room-temperature sol–gel process are incorporated. The Ni–Fe–Mg catalysts exhibit an overpotential of 310 mV at 10 mA cm⁻² in pH-neutral electrolytes and thus outperform iridium oxide (IrO₂) electrocatalyst by a margin of 40 mV. The catalysts are stable over 900 h of continuous operation. Experimental studies and computational simulations reveal that HEP catalysts favor the molecular adsorption of water and its dissociation in pH-neutral electrolyte, indicating a strategy to enhance OER catalytic activity.     

Minimizing Warpage for Macro-Size Fused Deposition Modeling Parts

In this study, we investigated warpage and corner lifting minimization for three-dimensional printed parts generated by macro-size fused deposition modeling (FDM). First, the reasons for warpage were theoretically elucidated. This approach revealed that the thermal deformation and differential volumetric shrinkage of the extruded molten plastic resulted in warpage of FDM parts. In addition, low adhesion between the deposited model and the heated or non-heated printing bed may intensify warpage further. As a next step, initial small-size and medium-size models were used to identify parameters to manage and minimize warpage in a way that would reduce material consumption and running time. Finally, a macro-size model was built to experimentally investigate and verify the technical solutions to minimize the warpage of FDM parts. In conclusion, an improved part with reduced warpage was efficiently produced after detailed consideration of thermal effects and adhesion force. Potential exists to widen the application scope of FDM technology in manufacturing for processes like thermoforming that involve mold core fabrication with heating. This technology, which has applications not only in mechanical engineering but also in related engineering fields, is convenient and could readily be applied to practical manufacturing industries.     

Prediction of BRIC Stock Price Using ARIMA,SutteARIMA, and Holt-Winters

The novel coronavirus has played a disastrous role in many countries worldwide. The outbreak became a major epidemic, engulfing the entire world in lockdown and it is now speculated that its economic impact might be worse than economic deceleration and decline. This paper identifies two different models to capture the trend of closing stock prices in Brazil (BVSP), Russia (IMOEX.ME), India (BSESN), and China (SSE), i.e., (BRIC) countries. We predict the stock prices for three daily time periods, so appropriate preparations can be undertaken to solve these issues. First, we compared the ARIMA, SutteARIMA and Holt-Winters (H-W) methods to determine the most effective model for predicting data. The stock closing price of BRIC country data was obtained from Yahoo Finance. That data dates from 01 November 2019 to 11 December 2020, then divided into two categories--training data and test data. Training data covers 01 November 2019 to 02 December 2020. Seven days (03 December 2020 to 11 December 2020) of data was tested to determine the accuracy of the models using training data as a reference. To measure the accuracy of the models, we obtained the means absolute percentage error (MAPE) and mean square error (MSE). Prediction model Holt-Winters was found to be the most suitable for forecasting the Brazil stock price (BVSP) while MAPE (0.50) and MSE (579272.65) with Holt-Winters (smaller than ARIMA and SutteARIMA), model SutteARIMA was found most appropriate to predict the stock prices of Russia (IMOEX.ME), India (BSESN), and China (SSE) when compared to ARIMA and Holt-Winters. MAPE and MSE with SutteARIMA: Russia (MAPE:0.7; MSE:940.20), India (MAPE:0.90; MSE:207271.16), and China (MAPE: 0.72; MSE: 786.28). Finally, Holt-Winters predicted the daily forecast values for the Brazil stock price (BVSP) (12 December to 14 December 2020 i.e., 115757.6, 116150.9 and 116544.1), while SutteARIMA predicted the daily forecast values of Russia stock prices (IMOEX.ME) (12 December to 14 December 2020 i.e., 3238.06, 3241.54 and 3245.01), India stock price (BSESN) (12 December to 14 December 2020 i.e.,. 45709.38, 45828.71 and 45948.05), and China stock price (SSE) (11 December to 13 December 2020 i.e., 3397.56, 3390.59 and 3383.61) for the three time periods.     

Fuzzy Decision Model: Evaluating and Selecting Open Banking Business Partners

The finance supply chain has always been a different supply chain compared to product supply chain being a service supply chain. Open Banking (OB) is one of the most important milestones since the beginning of financial technology innovation and service supply chain. As these are activities provided by traditional banks, non-bank financial institutions also provide financial service with access to consumer banking, transactional and other financial data to develop financial applications and services tailored to their customers. The development of financial technology, “Open banking”, promotes financial services to begin this transformation. However, evaluating and selecting open banking business partners from multiple perspectives for banks are underexplored. Thus, the authors in this research proposed a hybrid multi-criteria decision-making model which includes a Spherical Fuzzy Analytical Hierarchy Process (SF-AHP) model and a Multi-Attributive Ideal-Real Comparative Analysis (MAIRCA) model with supports from seasoned domain experts. The contribution of this research is a proposition of a fuzzy decision model for evaluating and selecting open banking business partners. The model successfully determined a suitable open bank provider in order to assist decision makers decide objectively.     

Conceptual design of efficient heat conductors using multi-material topology optimization

Conductive heat transfer plays an important role in dissipating thermal energy to achieve lower operating temperatures in various devices. Topology optimization has the potential to provide efficient structural solutions for such devices. The traditional topology optimization approach considers a single material. Adding additional materials with unique properties not only can expand the design options but also may improve the structural performance of the final structure. In this work, a multi-resolution topology optimization approach is employed to design multi-material structures for efficient heat dissipation. The implementation blends an efficient multi-resolution approach to obtain high-resolution designs with an alternating active phase algorithm to handle multi-material giving greater design flexibility. It solves the steady-state heat equation using finite element analysis and iteratively minimizes thermal compliance (maximizes conductivity). Several examples are presented to show the efficacy of the numerical implementation, which involves benchmark problems. Results indicate good prospects when quantitatively compared with single-material structures.