Current Issue : October - December Volume : 2018 Issue Number : 4 Articles : 5 Articles
The quality assessment and prediction becomes one of the most critical requirements\nfor improving reliability, efficiency and safety of laser welding.\nAccurate and efficient model to perform non-destructive quality estimation is\nan essential part of this assessment. This paper presents a structured and comprehensive\napproach developed to design an effective artificial neural network\nbased model for weld bead geometry prediction and control in laser welding of\ngalvanized steel in butt joint configurations. The proposed approach examines\nlaser welding parameters and conditions known to have an influence on geometric\ncharacteristics of the welds and builds a weld quality prediction model\nstep by step. The modelling procedure begins by examining, through structured\nexperimental investigations and exhaustive 3D modelling and simulation efforts,\nthe direct and the interaction effects of laser welding parameters such as\nlaser power, welding speed, fibre diameter and gap, on the weld bead geometry\n(i.e. depth of penetration and bead width). Using these results and various statistical\ntools, various neural network based prediction models are developed and\nevaluated. The results demonstrate that the proposed approach can effectively\nlead to a consistent model able to accurately and reliably provide an appropriate\nprediction of weld bead geometry under variable welding conditions....
Modern transport systems have the challenge to integrate more and more\nfunctions. This increases the weight of the structures. On the other hand demands\nand the legal regulations for emissions can only be fulfilled if the\nweight is reduced. This results in an ongoing increase of the usage of lightweight\nmaterials. Due to its low density and high strength Aluminium Alloys\nare the most used lightweight metals. However, some other physical properties\nhamper the processing of these alloys. The publication shows ways to\novercome these challenges applying appropriate material preparation and\nhandling in combination with specialized welding equipment for Aluminium\nwelding. Application examples demonstrate the state of the art in Aluminium\nwelding....
The effects of ambient temperature and shaft power variations on creep life\nconsumption of compressor turbine blades of LM2500+ industrial gas turbine\nengine are investigated in this work. An engine model was created in PYTHIA\n(Cranfield University�s gas turbine software) for the analysis. Blade thermal\nand stress models were developed and used together with Larson-Miller Parameter\nmethod for life analysis. Mean life reduction index, which is the propensity\nof a given effect to reduce engine life by half, is developed for each effect\nand applied in this research to compare the impacts of the different effects\non the blade creep life. It was observed that blade life will be halved when ambient\ntemperature is increased by 8.11 units while 13.64% increase in shaft\npower reduces blade life by a factor of 2. The results of this work will guide\nengine operators in making decisions concerning operating at part loads....
Low cycle fatigue life consumption analysis was carried out in this work. Fatigue\ncycles accumulation method suitable even if engine is not often shut\ndown was applied together with the modified universal sloped method for estimating\nfatigue cycles to failure. Damage summation rule was applied to estimate\nthe fatigue damage accumulated over a given period of engine operation.\nThe concept of fatigue factor which indicates how well engine is operated\nwas introduced to make engine life tracking feasible. The developed fatigue\nlife tracking method was incorporated in PYTHIA, Cranfield University\nin-house software and applied to 8 months of engine operation. The results\nobtained are similar to those of real engine operation. At a set power level, fatigue\nlife decreases with increase in ambient temperature with the magnitude\nof decrease greater at higher power levels. The fatigue life tracking methodology\ndeveloped could serve as a useful tool to engine operators....
One advantage of the adaptive cycle engine (ACE) is its ability of throttling with constant airflow by the combined control of\nvariable geometries, resulting in an improvement of spillage drag. However, the improvement is achieved at risk of a complex\ntechnical solution and control. This article investigates the selection scheme of variable geometries and engine configuration. It\nfocuses on the performance of a three-stream ACE during throttling, whose configuration and control schedule are simpler than\nother types of ACEs. Five variable geometries are selected from seven available options through comparison analysis. The\nuninstalled thrust decreases from 100% to 60.36% during the subsonic throttling and to 59.81% during the supersonic throttling.\nBenefitting from the decreased spillage drag, the installed performance of the three-stream ACE is improved to some degree\nduring throttling. This improvement is less than the result of a three-bypass ACE, whose configuration and control schedule are\nmore complex. Thus, the three-stream ACE is a compromise design considering the technical risk and variable cycle\ncharacteristic, which is a better platform to verify the component technology and control schedule for the further research on a\nmore complex type of ACE....
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