A Fast Simulation Method for Evaluating the Single-Event Effect in Aerospace Integrated Circuits

With the continuous progress in integrated circuit technology, single-event effect (SEE) has become a key factor affecting the reliability of aerospace integrated circuits. Simulating fault injection using the computer simulation technique effectively reflects the SEE in aerospace integrated circuits. Due to various masking effects, only a small number of faults will result in errors; the traditional method of injecting one fault in one workload execution is inefficient. The method of injecting multiple faults in one workload execution will make it impossible to judge which fault results in errors because the propagation characteristic of SEE and faults may affect each other. This paper proposes an improved multi-point fault injection method to improve simulation efficiency and solve the problems of the general multi-point fault injection method. If one workload execution does not result in errors, multiple faults can be verified by one workload execution. If one workload execution results in errors, a specific grouping method can be used to determine which faults result in errors. The experimental results show that the proposed method achieves a good acceleration effect and significantly improves the simulation efficiency.

A Large-Scale Sensor Layout Optimization Algorithm for Improving the Accuracy of Inverse Finite Element Method

The inverse finite element method (iFEM) based on fiber grating sensors has been demonstrated as a shape sensing method for health monitoring of large and complex engineering structures. However, the existing optimization algorithms cause the local optima and low computational efficiency for high-dimensional strain sensor layout optimization problems of complex antenna truss models. This paper proposes the improved adaptive large-scale cooperative coevolution (IALSCC) algorithm to obtain the strain sensors deployment on iFEM, and the method includes the initialization strategy, adaptive region partitioning strategy, and gbest selection and particle updating strategies, enhancing the reconstruction accuracy of iFEM for antenna truss structure and algorithm efficiency. The strain sensors optimization deployment on the antenna truss model for different postures is achieved, and the numerical results show that the optimization algorithm IALSCC proposed in this paper can well handle the high-dimensional sensor layout optimization problem.

Relationship between serotypes and genotypes based on the hypervariable region of the S1 gene of infectious bronchitis virus

To group infectious bronchitis virus (IBV) isolates, a genetic grouping method based on hypervariable region 1 (HVR 1, nucleotides 168 to 197) was compared with that based on the whole S1 gene. Both methods resulted in the same grouping data. So the grouping method based on HVR 1 could represent the grouping method based on the whole S1 gene. Taiwan isolates could not be placed within the existing groups. In order to test the correlation between genotype and serotype, a one-way neutralization test was used to compare 9 Taiwan isolates selected from different genotypes with Massachusetts (Mass) (H120) and Connecticut (Conn) standard strains. In addition, a two-way cross-neutralization test was performed in embryonated eggs with the beta method (constant-virus, diluted-serum) and the reciprocal neutralization titers were calculated to give the relatedness (r) values. The results of two kinds of neutralizing tests showed that the serotypes of 9 isolates were different from Mass or Conn. Based on the r-values, 9 isolates were divided into two serotypes which were correlated with their genotypes. From pathogenicity tests, IBV Taiwan isolates could be divided into high, intermediate, and low pathogenicity according to their pathogenicity indexes. However, no relationship exists between pathotype and genotype. In conclusion, the genetic typing method based on HVR 1 can be used for typing IBV isolates.