Bharat Forge (Germany)

Rock salt, claystone and crystalline rock are considered as potential host rocks for the disposal of high-level radioactive waste in Germany. Rock types, properties, and composition determine how these potential geologic barriers contribute to the containment, isolation, and retardation of the radioactive waste. Crystalline rocks are anisotropic and heterogeneous due to the presence of discontinuities. Therefore, the consideration of discontinuities in numerical models is crucial with regard to the performance assessment of radioactive waste repository systems. The project aims at developing a modelling strategy that enables effective modelling of fractures in crystalline rock. The continuum modelling approach using a Ubiqitous-Joint model is adopted to model the rock fractures. Its applicabilty for large-scale anyalses of anisotropic rock masses is being investigated by developing the numerical models based on predefined structural-geologic information. The influence of fracture orientations on the modelling of the rock masses will be studied, and their impact on performance assessments for the safe disposal of high-level radioactive waste in crystalline rock will be assessed.

Abstract Seed health is an indispensable prerequisite of food security. While the toolkit of plant protection products is currently limited, evidence suggests that the seed microbiome could protect seeds from pathogens. Thus, given their possible disease suppressive potential, we tested 11 different pathosystems to achieve the following proof-of-concept: seed microbiomes can be beneficial for seed health through conferring disease suppression. This study focused on beetroot, onion, spinach, pepper, coriander, red fescue and perennial ryegrass seeds, with each crop being challenged with one or two from a total of six pathogens, namely Pythium ultimum (or a Pythium sp.), Setophoma terrestris, Fusarium oxysporum, Phytophthora capsici, Laetisaria fuciformis and a mix of Puccinia sp. isolates. Each seed lot of each crop was tested with and without treatment with a disinfectant as a proxy for comparing intact seed microbiomes with seed microbiomes after partial elimination by disinfection. We found disease suppression in two pathosystems. Beetroot and spinach seed lots were able to suppress disease caused by P. ultimum when their microbiomes were intact but not after seed disinfection. We speculate that this relates to the microorganisms residing on and in the seed. Yet, seed microbiome disease suppression was not found in all pathosystems, highlighting the variation in seed morphology, plant cultivars, pathogens and seed disinfection treatments. A holistic understanding of the characteristics of seeds that harbour suppressive microbiomes as well as the pathogens that are sensitive to suppression could lead to more targeted and informed seed processing and treatment and, consequently, to the sustainable management of seedling diseases.

Detection of living beings through wall or under the rubble/debris is difficult in Radar due to low signal to noise ratio (SNR). To improve SNR and extract vital signs from Radar echo signal advanced signal processing techniques are required. The existing methods focus on detection of vital sign for single target only. This paper proposes an improvised method to detect multiple vital signs by determining the number of targets and their breathing frequency behind the wall using fast Fourier transform (FFT). Additionally an alternative technique using deep learning has been proposed for faster pre-processing and classification of number of targets. The proposed convolutional neural network (CNN) model is compared with other machine learning classifiers. It is found that if we used CNN as a feature extractor layer and Random Forest (RF) classifier it works the best with 94.38% accuracy (for two targets) and 73.33% accuracy (for three targets) without any pre-processing on Radar data. This method reduces the detection time needed as compared to the conventional algorithms available in literature

Deep cryogenic treatment (DCT) is one of the most recent processes being used to treat tool steels. It is a supplementary treatment where components are treated below subzero temperatures for several cryo-soaking hours. This paper focuses on to study the effect of deep cryogenic treatment on Thermo mechanical properties of AISI H-13 tool steel. Deep cryogenic treatment at 32 hours of cryo-soaking time is applied and thermo mechanical performance of tool steel was analyzed by using pin on disk high temperature wear testing and stress rupture testings. The microstructural evolutions during DCT were evaluated by using scanning electron microscope (SEM). It was observed that microstructural modifications like increase in carbide density, fine and uniform martensitic structure during DCT had significantly improved properties.

This study demonstrates crankshaft counterweight profile optimization to achieve better dynamic balancing. Balancing simulation was carried to predict initial unbalance. During balancing of actual crankshaft, the position of unbalance is sometimes shifted due to machining stock distribution towards non-favorable direction resulting into more number of balancing holes, thus productivity loss. To reduce this, counterweight profile optimized. After balancing, bending fatigue test carried out. Crankshaft exhibited pre-mature failure at unusual location. To determine the reason of failure, stress analysis was performed using FEA. Design enhancement solution proposed to reduce the stresses & subsequently enhance bending fatigue strength.

Ultrasonic assisted turning (UAT) is a novel manufacturing technology, where high frequency vibrations are imposed on the movement of a cutting tool. A 2D FE transient simulation is developed in DEFORM, where ultrasonic vibrations of frequency 20 kHz and amplitude of 20 μm are provided to the cutting tool in the direction of cutting velocity. The prediction of residual stress distribution is carried out using elasto-plastic finite element simulations. Experimental analysis is carried out in measuring the strain at the cutting tool during CT and UAT along with the chip mechanism and chip microstructure study to validate the residual stress distribution. The ultrasonic vibrations yield a considerable improvement in compressive residual stresses which ultimately benefits in improving fatigue life of titanium alloys.