Improved frictional modeling for the pressure-time method

The pressure-time method is classified as a primary method for measuring discharge in hydraulic machinery. The uncertainty in the discharge determined using the pressure-time method is typically around $\pm 1.5$ %; however, despite dating back almost one hundred years in time, there still exists potential to reduce this uncertainty. In this paper, an improvement of the pressure-time method is suggested by implementing a novel formulation to model the frictional losses arising in the evaluation procedure. By analyzing previously obtained data from CFD, laboratory and full-scale pressure-time measurements it is shown that the new friction model improves the accuracy of the flow rate calculation by approximately 0.1–0.2% points, compared to currently utilized friction models. Despite being a small absolute improvement, the new friction model presents an important development of the pressure-time method because the relative improvement is significant.     

Extending interior-point methods to nonlinear second-order cone programming: Application to finite-strain elastoplasticity

Interior-point methods (IPMs) are well suited for solving convex nonsmooth optimization problems which arise for instance in problems involving plasticity or contact conditions. This work attempts at extending their field of application to optimization problems involving either smooth but nonconvex or nonsmooth but convex objectives or constraints. A typical application for such kind of problems is finite-strain elastoplasticity which we address using a total Lagrangian formulation based on logarithmic strain measures. The proposed interior-point algorithm is implemented and tested on 3D examples involving plastic collapse and geometrical changes. Comparison with classical, Newton-Raphson/return mapping methods show that the IPM exhibits good computational performance, especially in terms of convergence robustness. Similar to what is observed for convex small-strain plasticity, the IPM is able to converge for much larger load steps than classical methods.     

Drag Power Loss Investigation in Cylindrical Roller Bearings Using CFD Approach

In high-speed rolling element bearings, the drag forces can be prominent and it is demonstrated in this investigation that the classical models may not be appropriate for correctly estimating this power loss contribution. A modification of the models is thus proposed, including the usual drag forces formulation relying upon the drag coefficient to be evaluated from a numerical computational fluid dynamics (CFD) approach. A three-dimensional approach that considers both the rings and the cylinder ends seems the only adequate approach to be used because a two-dimensional approach predicts a drag coefficient value that is too low. When using the former computed drag coefficient for the evaluation of the total power losses, high values of oil volume fraction must be employed to recover the measured power losses.     

Optimisation of the spark plasma sintering process for high volume fraction SiCp/Al composites by orthogonal experimental design

Based on orthogonal experimental design (OED), the effects of the sintering pressure, sintering temperature and holding time on the mechanical properties of 50 vol% silicon carbide particle (SiCp)/2024Al composites prepared by spark plasma sintering (SPS) were investigated. The sintering pressure had the greatest effect on the density and bending strength of the material among these three factors, followed by sintering temperature and holding time. The optimised process conditions for producing the 50 vol% SiCp/2024Al were sintering at 550 °C for 5 min under 40 MPa, which resulted in a composite material with a density of 99.7% and good interface bonding with a comparatively high bending strength of 766.65 MPa. This work provides a promising method to produce high volume fraction composites that can meet high strength requirements.     

Impact of the occurrence probability of carbon black agglomerates on the measured and predicted durability of filled elastomers

This work analyses the impact of the sample geometry on the stress or strain concentration and the occurrence of big agglomerates in the investigated test volume. Although the three investigated dumbbell test specimens were loaded at the same stress level, there were significant differences in measured lifetime. These differences in the lifetime are due to the occurrence of the large agglomerates in the tested volume. The probability of occurrence of large agglomerates increases with increase in the investigated volume. In the lifetime prediction by Monte Carlo method, this effect is realized by changing the quantity of the distributed agglomerates in the mesh of the simulated model. The prediction of the different sample geometries shows a very good agreement with the measurement points. The numerical simulations illustrate the stress increase for the three used lifetime test samples.     

Sintering of WC-Ni nanocomposite powder: Experimental and artificial neural networks modeling study

The sintering behavior of WC-Ni nanocomposite powder was evaluated through experimental and statistical approaches to study the contribution of involving parameters of chemical composition (Ni wt. %) and sintering temperature on sinterability of system by assessing the resulted densification and microhardness. The experimental process was designed based on factorial experimental design for independent effective parameters of Ni percentage (12, 18 and 23 wt %), and sintering temperature (8 different values within 1350–1485 °C). The resulted products of experimental testing after compaction and sintering were analyzed by FESEM and EDX to image the microstructure and evaluate the chemical composition and elemental distribution. The density and microhardness were measured as well. An artificial neural network (ANN) was applied to describe the corresponding individual and mutual impacts on sintering. The ANN model was developed by feed-forward back propagation network including topology 2:5:2 and trainlm algorithm to model and predict density and microhardness. A great agreement was observed between the predicted values by the ANN model and the experimental data for density and microhardness (regression coefficients (R²) of 0.9983 and 0.9924 for target functions of relative density and microhardness, respectively). Results showed that the relative importance of operating parameters on target functions (relative density and microhardness) was found to be 62% and 38% for sintering temperature and Ni percentage, respectively. Also, ANN model exhibited relatively high predictive ability and accuracy in describing nonlinear behavior of the sintering of WC-Ni nanocomposite powder. The experimental results confirmed that the appropriate sintering temperature was influenced by Ni content. The optimum parameters were found to be 12 wt % Ni sintered at 1460 °C with the highest microhardness and relative density.     

Structural transformation in Mn-substituted Sr2Bi2Ta2TiO12 Aurivillius phase synthesized by hydrothermal method: A comparative study and dielectric properties

In this study, a hydrothermal method was applied to synthesize the three-layer Aurivillius phase Sr₂Bi₂Ta₂TiO₁₂ (SBTTO) and Mn-substituted Sr_1·5Bi_2·5Ta₂Ti_0·5Mn_0·5O₁₂ (SBTTMO), with the use of NaOH as a mineralizer. The crystal structure, morphology, dielectric properties, and the correlation between the structural transformation and dielectric properties were investigated. The XRD data reveal that the SBTTO sample adopts a tetragonal crystal structure with the I4/mmm space group and is then transformed into an orthorhombic structure with the B2cb space group for SBTTMO. The morphology of both samples was observed by SEM, which showed anisotropic plate-like grains. With the Mn substitution, the ferroelectric transition temperature (T_c) significantly increases as the influence of the 6s² lone pair of Bi³⁺ increases, and this in turn further induces the relaxor-ferroelectric behavior. Consequently, the increase in T_c confirms the structural transformation from the paraelectric-tetragonal to the ferroelectric-orthorhombic phase.     

Leaf-to-Whole Plant Spread Bioassay for Pepper and Ralstonia solanacearum Interaction Determines Inheritance of Resistance to Bacterial Wilt for Further Breeding

Bacterial wilt (BW) disease from Ralstonia solanacearum is a serious disease and causes severe yield losses in chili peppers worldwide. Resistant cultivar breeding is the most effective in controlling BW. Thus, a simple and reliable evaluation method is required to assess disease severity and to investigate the inheritance of resistance for further breeding programs. Here, we developed a reliable leaf-to-whole plant spread bioassay for evaluating BW disease and then, using this, determined the inheritance of resistance to R. solanacearum in peppers. Capsicum annuum ‘MC4′ displayed a completely resistant response with fewer disease symptoms, a low level of bacterial cell growth, and significant up-regulations of defense genes in infected leaves compared to those in susceptible ‘Subicho’. We also observed the spreading of wilt symptoms from the leaves to the whole susceptible plant, which denotes the normal BW wilt symptoms, similar to the drenching method. Through this, we optimized the evaluation method of the resistance to BW. Additionally, we performed genetic analysis for resistance inheritance. The parents, F₁ and 90 F₂ progenies, were evaluated, and the two major complementary genes involved in the BW resistance trait were confirmed. These could provide an accurate evaluation to improve resistant pepper breeding efficiency against BW.     

E7766, a Macrocycle-Bridged Stimulator of Interferon Genes (STING) Agonist with Potent Pan-Genotypic Activity

A strategy for creating potent and pan-genotypic stimulator of interferon genes (STING) agonists is described. Locking a bioactive U-shaped conformation of cyclic dinucleotides by introducing a transannular macrocyclic bridge between the nucleic acid bases leads to a topologically novel macrocycle-bridged STING agonist (MBSA). In addition to substantially enhanced potency, the newly designed MBSAs, exemplified by clinical candidate E7766 , exhibit broad pan-genotypic activity in all major human STING variants. E7766 is shown to have potent antitumor activity with long lasting immune memory response in a mouse liver metastatic tumor model. Two complementary stereoselective synthetic routes to E7766 are also described.