Initiation and growth of corrosion fatigue cracks from corrosion pits using elasto-plastic notch analysis

Corrosion pits are known to act as precursors for fatigue crack initiation under corrosive environment. The transition from pit to crack growth under corrosion fatigue is of considerable interest for many engineering structures. Several predictive methodologies have been developed. As the Pits grow with large aspect ratio, they behave like local stress/strain concentrations accentuating the crack initiation and growth. In this paper, we extend our recent analysis of crack initiation at the elastic-plastic notch tip stress fields* to evaluate its applicability to pit to crack transition. Ref: K. Sadananda, A. Arcari, A.K. Vaudevan, Eng. Frac. Mech., 2017, 176 pp.144-16

An integrated microring circuit design for optoelectronic transformer applications

The on-chip scale circuit of the optoelectronic transformer is designed and manipulated using the microring resonator system. By using the monochromatic input light source, the electro-optic signals can be generated and functioned as the step up and down conversion by mean of the on-chip optoelectronic transformer. The step up and down of the electro-optic related power conversions can be obtained via the input and drop port connections. The results obtained have shown that the flexible up and down electro-optic conversion ratios of 1: 5 and 10:1 for the step up and down conversions, respectively. The uses light source wavelength source was centered at 800 nm, where the conversion stability of 1600 fs is noted. The linearity trend of the conversion stability is confirmed

A review of the health status and diseases of cultured Penaeus indicus in Sistan-o-Baluchistan Province, Iran

The health status and diseases of Penaeus indicus in Sistan-o-Baluchistan culture ponds of Guater Site were assessed during the year 2005. Over the shrimp culture period, two ponds were selected from two farms, and 19 shrimp specimens were caught randomly each month from each pond. The specimens were immediately transferred to lab for further investigation. After recording abnormal signs including color change of cuticle and gills, presence of white or black spots on the body, the specimens were studied for bacterial, fungal and parasitic infections. Bacterial infections included Citobacter, Pseudomonas, Aeromonas, Actinobacter, Proteus, Vibrio alginolyticus, V. harveyi, V. parahaemolyticus, V. spelendidus and Vibrio sp. Fungal infections of the cultured P. indicus included Fuzarium spp., Mucor, Cladosporium, Aspergillus spp., Penicllinium spp., sterilized hyphae and yeast. The parasites found included Zoothamnium, Epistylis, andVorticella. Since the second month of shrimp culture onwards around 10-65% of shrimps showed white and opaque spots on abdominal muscle which started from the sixth segment. Sometimes, the dots covered the whole abdomen, giving the shrimps a cooked look and a yellowish watery sac on hepatopancreas under the carapace of the specimens could be observed. There was no evidence of disease agents based on microbial, parasitic and environmental studies. The food which was used for shrimp culture was analyzed and showed anion and cation imbalance. Our results showed Idiopathic Muscle Necrosis Syndrome (IMNS) and Subcarapace Watery Sac Syndrome (SWSS) sings in the cultured shrimps

Feature Relevance Assessment Of Multispectral Airborne Lidar Data For Tree Species Classification

Abstract. The presented experiment investigates the potential of Multispectral Laser Scanning (MLS) point clouds for single tree species classification. The basic idea is to simulate a MLS sensor by combining two different Lidar sensors providing three different wavelngthes. The available data were acquired in the summer 2016 at the same date in a leaf-on condition with an average point density of 37 points/m2. For the purpose of classification, we segmented the combined 3D point clouds consisiting of three different spectral channels into 3D clusters using Normalized Cut segmentation approach. Then, we extracted four group of features from the 3D point cloud space. Once a varity of features has been extracted, we applied forward stepwise feature selection in order to reduce the number of irrelevant or redundant features. For the classification, we used multinomial logestic regression with L1 regularization. Our study is conducted using 586 ground measured single trees from 20 sample plots in the Bavarian Forest National Park, in Germany. Due to lack of reference data for some rare species, we focused on four classes of species. The results show an improvement between 4–10 pp for the tree species classification by using MLS data in comparison to a single wavelength based approach. A cross validated (15-fold) accuracy of 0.75 can be achieved when all feature sets from three different spectral channels are used. Our results cleary indicates that the use of MLS point clouds has great potential to improve detailed forest species mapping. </jats:p

A Critical Review on Improving the Fatigue Life and Corrosion Properties of Magnesium Alloys via the Technique of Adding Different Elements

Magnesium is the eighth-most abundant element in the world and its alloys have a widespread application in various industries such as electronic and transport (i.e., air, land, and sea) engineering, due to their significant mechanical properties, excellent machinability, high strength to weight ratios, and low cost. Although monolithic Mg metal is known as the lightest industrial metal (magnesium density is 30% less than the density of the aluminum, and this unique property increases the attractiveness of its usage in the transportation industry), one of the significant limitations of magnesium, which affects on its applications in various industries, is very high reactivity of this metal (magnesium with an electronegativity of 31.1 can give electrons to almost all metals and corrodes quickly). To overcome this problem, scholars are trying to produce magnesium (Mg) alloys that are more resistant to a variety of loads and environmental conditions. In this regard, Mg alloys include well-known materials such as aluminum (Al), Zinc (Zn), Manganese (Mn), Silicon (Si), and Copper (Cu), etc., and their amount directly affects the properties of final products. In the present review paper, the authors attempted to present the latest achievements, methods, and influential factors (finish-rolling, pore defects, pH value, microstructure, and manufacturing processes, etc.) on the fatigue life and corrosion resistance of most significant Mg alloys, including AM50, AM60, AZ31, AZ61, AZ80, AZ91, ZK60, and WE43, under various conditions. The summarized results and practical hints presented in this paper can be very useful to enhance the reliability and quality of Mg-made structures

Applications of ultrasonic testing and machine learning methods to predict the static & fatigue behavior of spot-welded joints

© 2020 The Society of Manufacturing Engineers. This manuscript is made available under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International licence (CC BY-NC-ND 4.0). For further details please see: https://creativecommons.org/licenses/by-nc-nd/4.0/Ultrasonic Testing (UT) is one of the well-known Non-Destructive Techniques (NDT) of spot-weld inspection in the advanced industries, especially in automotive industry. However, the relationship between the UT results and strength of the spot-welded joints subjected to various loading conditions isunknown. The main purpose of this research is to present an integrated search system as a new approach for assessment of tensile strength and fatigue behavior of the spot-welded joints. To this end, Resistance Spot Weld (RSW) specimens of three-sheets were made of different types of low carbon steel. Afterward, the ultrasonic tests were carried out and the pulse-echo data of each sample were extracted utilizing Image Processing Technique (IPT). Several experiments (tensile and axial fatigue tests) were performed to study the mechanical properties of RSW joints of multiple sheets. The novel approach of the present research is to provide a new methodology for static strength and fatigue life assessment of three-sheets RSW joints based on the UT results by utilizing Artificial Neural Network (ANN) simulation. Next, Genetic Algorithm (GA) was used to optimize the structure of ANN. This approach helps to decrease the number of tests and the cost of performing destructive tests with appropriate reliability.Peer reviewe

The effects of extender type, freezing and thawing rates on fertility of the cryopreserved semen of the Caspian brown trout (Salmo trutta caspius)

Cryopreservation of semen from the Caspian brown trout (Salmo trutta caspius) and effects of extender type, freezing and thawing rates on fertilization ability were studied. After assessment of semen quality, one part of semen was diluted with three parts of different extender and decanted into 0.5ml straws. Freezing was carried out at two freezing levels, 1.5cm and 2cm above surface of liquid nitrogen. The semen was thawed at 5°C for 90s, 15°C for 45s or 25°C for 30s in water baths and used for fertilization. Using the extender: 0.3 M glucose+10% methanol+10% egg yolk, and 0.6 M sucrose 10% DMSO + 10% egg yolk, yielded the highest post-thaw fertilization rates, with 67.05%±8.76 and 59.78%±5.08 eyeing rates, respectively. No significant differences were found in the fertilization rates with two freezing levels (P>0.05), however eyeing and hatching rates were higher for 2cm above the surface of the liquid nitrogen than for 1.5cm. Thawing of cryopreserved semen was best using the 25°C water bath for 30s and significant differences were seen in the eyeing rates between 25°C and 5°C or 15°C (P<0.05). Significant interactions (P<0.05) were found between effects of extender type and thawing rates and extender type and freezing rates