Alloying Effect on Transformation Strain and Martensitic Transformation Temperature of Ti-Based Alloys from Ab Initio Calculations.

The accurate prediction of alloying effects on the martensitic transition temperature () is still a big challenge. To investigate the composition-dependent lattice deformation strain and the upon the to ″ phase transition, we calculate the total energies and transformation strains for two selected Ti-Nb-Al and Ti-Nb-Ta ternaries employing a first-principles method. The adopted approach accurately estimates the alloying effect on lattice strain and the by comparing it with the available measurements.

Online prediction of total sugar content and optimal control of glucose feed rate during chlortetracycline fermentation based on soft sensor modeling.

In the process of chlortetracycline (CTC) fermentation, no instrument can be used to measure the total sugar content of the fermentation broth online due to its high viscosity and large amount of impurities, so it is difficult to realize the optimal control of glucose feed rate in the fermentation process. In order to solve this intractable problem, the relationship between on-line measurable parameters and total sugar content (One of the parameters that are difficult to measure online) in fermentation tank is deeply analyzed, and a new soft sensor model of total sugar content in fermentation tank and a new optimal control method of glucose feed rate are proposed in this paper. By selecting measurable variables of fermentation tank, determining different fermentation stages, constructing recursive fuzzy neural network (RFNN) and applying network rolling training method, an online soft sensor model of total sugar content is established.

Contribution to Improvement of Fatigue Properties of Zr-4 Alloy: Gradient Nanostructured Surface Layer versus Compressive Residual Stress.

The gradient nanostructured (GNS) layer forms beneath the surface of Zr-4 samples by the surface mechanical grinding treatment (SMGT) process, which increases the fatigue strength apparently due to the synergistic effect of the gradient nanostructured layer and compressive residual stress. The SMGTed Zr-4 samples are subjected to annealing to remove residual stress (A-SMGT) and the individual effect of the GNS layer and compressive residual stress can be clarified. The results show that the gradient nanostructure in the surface is stable after annealing at 400 °C for 2 h but residual stress is apparently removed.

Study on soft sensor modeling method for sign of contaminated fermentation broth in Chlortetracycline fermentation process.

During Chlortetracycline fermentation, contamination of fermentation broth by non-target bacteria is an unavoidable problem. There is no online analytical instrument to determine whether the fermentation broth has been contaminated. Only the results of manual sampling analysis can be used to determine whether the fermentation broth is contaminated.

Adaptive Volume Control in Titanium Alloy for High Temperature Performance.

With the increase of time, the shrinkage of materials at fixed temperature could enhance the failure of fasteners. We report a potential way to alter the volume/length of alloy automatically through isothermal aging due to pseudospinodal decomposition mechanism. The volume of Ti-10V-2Fe-3Al alloy first shrunk and then expanded during isothermal aging at 550 °C.

Study on the prediction of the contamination symptoms in the fermentation process of Chlortetracycline based on soft sensor modeling method.

Background: How to accurately predict the occurrence of contamination in the fermentation process of Chlortetracycline? How to prompt field operators to take effective measures in time? This is a difficult problem that the fermentation process of Chlortetracycline has not been solved well.

Objective: The aim of this paper is to effectively predict whether the fermentation process of Chlortetracycline is contaminated or not.

Methods: A Gaussian process regression soft sensor modeling method with real time integration learning is studied in depth by combining two local learning strategies, namely just-in-time learning (JITL) method and integrated learning method, and a multi-model weighted Gaussian process regression (MWGPR) soft sensor modeling method based on real-time integration learning is proposed in the paper.

Superior plasticity stability and excellent strength in Ti-55531 alloy micropillars via harmony slip in nanoscale α/β phases.

Excellent stability of plasticity and high strength are acquired in Ti55531 alloy micropillars via introducing a high density of deformable nanoscale α phase into a β matrix. The yield strength of the pillars is as high as 2.26 GPa irrespective of pillar sizes ranging from 6 to 0.

Rotatable precipitates change the scale-free to scale dependent statistics in compressed Ti nano-pillars.

Compressed nano-pillars crackle from moving dislocations, which reduces plastic stability. Crackling noise is characterized by stress drops or strain bursts, which scale over a large region of sizes leading to power law statistics. Here we report that this "classic" behaviour is not valid in Ti-based nanopillars for a counterintuitive reason: we tailor precipitates inside the nano-pillar, which "regulate" the flux of dislocations.