Stephen J. Pinchak and Asok Ray
The goal of the paper is to present an enhancement of the existing on‐board ground collision avoidance system (GCAS) that is designed to increase pilot safety in USAF A‐10…
Abstract
The goal of the paper is to present an enhancement of the existing on‐board ground collision avoidance system (GCAS) that is designed to increase pilot safety in USAF A‐10 aircraft. The A‐10 is a single‐seat, twin‐engine aircraft with a 30mm, seven‐barreled Gatling gun and 11 weapon pylons designed to fly at low level in close air support missions. The GCAS system provides both visual and aural cues for a pilot‐initiated recovery. The proposed algorithm of GCAS enhancement is built on a simple linear regression model that predicts the recovery height of the aircraft following a warning call and allows pilots to compare their own training events with flight test standards. This paper presents a discussion of model development, validation and comparison of the model predictions with actual flight test events. A comparison of recovery techniques and pilot options is included. A series of recommendations and possible usage for Air Force pilot training are also discussed.
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Bikash Routh, Rathindranath Maiti and Asok Kumar Ray
In a harmonic drive during assembly of its components like strain wave generating (SWG) cam, flexspline (FS) and circular spline, a gap is formed between the cam’s outer surface…
Abstract
Purpose
In a harmonic drive during assembly of its components like strain wave generating (SWG) cam, flexspline (FS) and circular spline, a gap is formed between the cam’s outer surface and the FS cup inner surface due to mismatching. This gap, which is known as “Coning”, plays a vital role in the flow of lubricant at that interface. This paper aims to analyse the coning phenomenon and the lubrication mechanism.
Design/methodology/approach
In the present investigation, the geometry of the coning gap and its variation with the SWG cam rotation are established. Essentially, the deflection of FS cup and deformation of SWG cam (bearing outer race) are derived to find the gap due to coning. Next, the hydrodynamic lubrication equation is solved to get pressure profiles for this gap under suitable boundary conditions assuming non-Newtonian lubrication.
Findings
Methods of estimating the coning gap and lubrication pressure profiles are established. Effects of non-Newtonian terms (coupling number and non-dimentionalized characteristic length) and SWG length (finite, long and short) on pressure profiles are also shown. All analyses are done in non-dimensionalized form.
Originality/value
Establishing the geometry of coning and non-Newtonian hydrodynamic lubrication aspects in the coning in the FS cup and SWG cam interface are the originality of the present investigation.
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The task of metal removal from steel castings may often be repetitive, and has to be carried out in the unpleasant environment of cleaning rooms. To achieve improved productivity…
Abstract
The task of metal removal from steel castings may often be repetitive, and has to be carried out in the unpleasant environment of cleaning rooms. To achieve improved productivity in metal removal, an automation concept has been developed and a machine designed to implement that concept.
The present study spotlights the single and multicriteria decision-making (MCDM) methods to determine the optimal machining conditions and the predictive modeling for surface…
Abstract
Purpose
The present study spotlights the single and multicriteria decision-making (MCDM) methods to determine the optimal machining conditions and the predictive modeling for surface roughness (Ra) and cutting tool flank wear (VB) while hard turning of AISI 4340 steel (35 HRC) under dry environment.
Design/methodology/approach
In this study, Taguchi L16 design of experiments methodology was chosen. The experiments were performed under dry machining conditions using TiSiN-TiAlN nanolaminate PVD-coated cutting tool on which Taguchi and responses surface methodology (RSM) for single objective optimization and MCDM methods like the multi-objective optimization by ratio analysis (MOORA) were applied to attain optimal set of machining parameters. The predictive models for each response and multiresponse were developed using RSM-based regression analysis. S/N ratios, analysis of variance (ANOVA), Pareto diagram, Tukey's HSD test were carried out on experimental data for profound analysis.
Findings
Optimal set of machining parameters were obtained as cutting speed: at 180 m/min., feed rate: 0.05 mm/rev., and depth of cut: 0.15 mm; cutting speed: 145 m/min., feed rate: 0.20 mm/rev. and depth of cut: 0.1 mm for Ra and VB, respectively. ANOVA showed feed rate (96.97%) and cutting speed (58.9%) are dominant factors for Ra and VB, respectively. A remarkable improvement observed in Ra (64.05%) and VB (69.94%) after conducting confirmation tests. The results obtained through the MOORA method showed the optimal set of machining parameters (cutting speed = 180 m/min, feed rate = 0.15 mm/rev and depth of cut = 0.25 mm) for minimizing the Ra and VB.
Originality/value
This work contributes to realistic application for manufacturing industries those dealing with AISI 4340 steel of 35 HRC. The research contribution of present work including the predictive models will provide some useful guidelines in the field of manufacturing, in particular, manufacturing of gear shafts for power transmission, turbine shafts, fasteners, etc.