Department of Mechanical Engineering

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High-temperature oxidation behavior of different power plant steels (P22, P91, and SS304L) was investigated under the exposure of different molten salt mixtures at a temperature of 950 °C. Cyclic corrosion study of 50 h were performed on the different specimens by applying 3–5 mg/cm 2 salt mixtures (Na 2 SO 4 + 60% V 2 O 5 , K2 S O 4 + 60% NaCl, Na 2 SO 4 + 50% NaCl, 10% NaCl +10% KCl + 40% Na 2 SO 4 + 40% K 2 SO 4 ) on the surface. XRD, SEM, and EDS analysis were performed on the post corroded specimens. The results indicate that steel with low Cr content undergoes a heavy oxide scaling leading to higher weight gain due to the absence of protective Cr 2 O 3 inner scale. Thus, steel with higher Cr content possesses better corrosion resistant properties. Moreover, addition of chlorine to the alkali salt causes an immediate drop in the melting temperature of the salt mixture, which increases the melt and leads to a more corrosive environment. Salt mixtures with higher chlorine content severely affects the corrosion resistance of each alloy. Additionally, higher weight gain was observed for the steel specimens which were exposed to the salt mixture containing a higher amount of chlorine in combination with Na 2 SO 4 . © 2019 Elsevier Ltd

World University root node

Engineering Failure Analysis

Hot corrosion studies of boiler steels exposed to different molten salt mixtures at 950 °C

Repeatability measurement and kinematic identification of LBR iiwa 7 R800 using monocular camera

Effect of ‘conventional normalizing and tempering’ (CNT) and ‘double austenitization based normalizing and tempering’ (DNT) process on microstructure characteristic and mechanical behavior was studied forP92 steel. In CNT heat treatment, P92 steel is normalized at 1040 °C/air cool and tempered with 760 °C/2 h/air cool. In DNT heat treatment, initially normalizing was performed at 1040 °C for 1 h followed by water quenching. After that sample was normalized in the temperature range of 950–1150 °C for 1 h and tempered at 760 °C/2 h/air cool (950 °C-DNT1, 1050 °C-DNT2, 1150 °C-DNT3).Grain size for CNT and DNT1 treatment were measured 17 ± 7 μm and 12 ± 5 μm. A DNT treatment resulted in homogeneous microstructure formation that led to improved mechanical properties as compared to CNT treatment. The DN based heat treatment produced complete martensitic microstructure formation by complete dissolution of carbide precipitates. The optimized room temperature condition was obtained for the DNT 1 heat treatment. © 2018 Elsevier Ltd

Study on effect of double austenitization treatment on fracture morphology tensile tested nuclear grade P92 steel

In the present work, a numerical analysis of conjugate heat transfer and fluid flow in vortex generator (VG) enhanced double-fin and tube heat exchanger is carried out. The enhanced design aims to improve the heat transfer performance of a conventional double-fin and tube heat exchanger for waste heat recovery applications. A threedimensional (3D) numerical model is developed using ANSYS CFX to simulate fluid flow and conjugate heat transfer process. Numerical simulations with rectangular winglet vortex generators (RWVGs) at five different angles of attack (-20 deg ≤ α ≤ 20 deg) are performed for the Reynolds number range of 5000 ≤ Re ≤ 11,000. Salient performance characteristics are analyzed in addition to the temperature distribution and flow fields. Based on the numerical results, it is concluded that the overall performance of the double-fin and tube heat exchanger can be improved by 27-91% by employing RWVGs at α = -20 deg for the range of Reynolds number investigated. The study provides useful design information and necessary performance data that can be adopted for the design development of the heat exchanger at a lower manufacturing cost. Copyright © 2019 by ASME.

Journal of Heat Transfer

Investigation of vortex generator enhanced double-fin and tube heat exchanger

The packed-bed thermal energy storage technology has gained a significant market worldwide as it offers a huge potential for high-temperature air based storage with no adverse environmental impact. The present paper numerically investigates a high-temperature 175,000 m3 truncated conical shaped packed-bed thermal energy storage. One-dimensional, two-phase model is developed to simulate the transient behavior of the storage where the energy balance of both phases, the fluid and the solid, are based on modified equations of the Schumann model. The model developed is used to carry out a parametric study where it is subjected to different design and operating parameters such as storage shape, rock diameter, charge-discharge rate and insulation thickness. The storage performance is assessed through energy and exergy efficiencies taking energy stored and recovered into account. The model satisfactorily predicts the dynamic behavior of a large-scale packed-bed storage system within the range of parameters investigated. Results obtained denote that the truncated conical shaped storage with rock diameter of 3 cm, insulation thickness up to 0.6 m and charging-discharging rate of 553 kg/s leads to lower thermal losses estimated under 1% of the energy recovered during discharge. Furthermore, energy and exergy efficiencies of thermal cycles are found to exceed 98% for most of the selected parameters in the study. The model developed can assist in identifying more advance and cost-effective storage design solutions for a large-scale application. © 2019 Elsevier Ltd

Applied Energy

Investigation on transient performance of a large-scale packed-bed thermal energy storage

This paper presents an adaptive backstepping motion control of a sitting- type lower limb rehabilitation robot (LLRR). The kinematics and dynamics of the proposed robot is discussed and its motion control design in the taskspace based on an adaptive backstepping control strategy is derived herein. The closed-loop system stability of the proposed motion control scheme is demonstrated by the Lyapunov’s direct method. Further performance analysis of the proposed system along with the proposed motion control design is demonstrated using computer based numerical simulations. For numerical simulations and to validate the effectiveness of the motion control strategy and the proposed lower limb rehabilitation robot design, the clinically obtained test gait data is used for the desired motion trajectory. © 2019, Springer Nature Switzerland AG.

Mechanisms and Machine Science

Adaptive Backstepping Motion Control of a New Sitting-type Lower Limb Rehabilitation Robot

In this paper, we present a finite element formulation for simulating the electromechanical behavior of nonlinear visco-hyperelastic dielectric elastomers undergoing isochoric finite strain deformations. The incompressible nature of dielectric elastomer results in the problem of volumetric locking. In order to alleviate this problem various techniques, such as selective reduce integration method, F-bar method, and mixed formulation have been used. In the present numerical framework, we treat this problem by adapting the computationally efficient J-bar method. This method of alleviating locking is based on the assumption of the dependence of volumetric density function only on the smoothed volumetric part of the multiplicatively decomposed deformation gradient. A staggered solution algorithm is used for solving the coupled nonlinear equations by decoupling displacement and electric potential fields. The present formulation is implemented into an in-house finite element program. Firstly, the finite element implementation of the proposed formulation is validated and demonstrated by investigating the effect of viscosity parameter on the electromechanical phenomenon of homogeneously deforming dielectric elastomers, i.e., voltage driven creep and pull-in instability. Further, for an in-homogeneously deforming bi-layered bending actuator, the computational efficiency of the proposed J-bar method employed in conjunction with the staggered solution approach is established over the conventional F-bar and multi-field formulations used with the monolithic solution scheme. Finally, we utilize the proposed formulation for investigating the effect of visco-elasticity on the electromechanical response of complex dielectric elastomeric actuators involving inhomogeneous deformations such as, bilayer bending actuators, grippers, and buckling pumps, when subjected to monotonic and constant electrical loads. © 2019 Elsevier B.V.

Computer Methods in Applied Mechanics and Engineering

A computationally efficient locking free numerical framework for modeling visco-hyperelastic dielectric elastomers

Non-linear turbulence closures were developed that improve the prediction accuracy of wake mixing in low-pressure turbine (LPT) flows. First, Reynolds-averaged Navier-Stokes (RANS) calculations using five linear turbulence closures were performed for the T106A LPT profile at exit Mach number 0.4 and isentropic exit Reynolds numbers 60,000 and 100,000. None of these RANS models were able to accurately reproduce wake loss profiles, a crucial parameter in LPT design, from direct numerical simulation (DNS) reference data. However, the recently proposed kv2w transition model was found to produce the best agreement with DNS data in terms of blade loading and boundary layer behavior and thus was selected as baseline model for turbulence closure development. Analysis of the DNS data revealed that the linear stress-strain coupling constitutes one of the main model form errors. Hence, a geneexpression programming (GEP) based machine-learning technique was applied to the high-fidelity DNS data to train non-linear explicit algebraic Reynolds stress models (EARSM). In particular, the GEP algorithm was tasked to minimize the weighted difference between the DNS and RANS anisotropy tensors, using different training regions. The trained models were first assessed in an a priori sense (without running any CFD) and showed much improved alignment of the trained models in the region of training. Additional RANS calculations were then performed using the trained models. Importantly, to assess their robustness, the trained models were tested both on the cases they were trained for and on testing, i.e. previously not seen, cases with different flow features. The developed models improved prediction of the Reynolds stress, TKE production, wake-loss profiles and wake maturity, across all cases, in particular those trained on just the wake region. © 2018 ASME.

Journal of Turbomachinery

Development and Use of Machine-Learnt Algebraic Reynolds Stress Models for Enhanced Prediction of Wake Mixing in Low-Pressure Turbines

This paper presents a robust method to track a moving object under occlusion using an off-the-shelf monocular camera and a 6 Degree of Freedom (DOF) articulated arm. The visual servoing problem of tracking a known object using data from a monocular camera can be solved with a simple closed loop controller. However, this system frequently fails in situations where the object cannot be detected and to overcome this problem an estimation based tracking system is required. This work employs an Adaptive Kalman Filter (AKF) to improve the visual feedback of the camera. The role of the AKF is to estimate the position of the object when it is occluded/out of view and remove the noise and uncertainties associated with visual data. Two estimation models for the AKF are selected for comparison and among them, the Mean-Adaptive acceleration model is implemented on a 6-DOF UR5 articulated arm with a monocular camera mounted in eye-in-hand configuration to follow the known object in 2D cartesian space (without using depth information). © 2019 Association for Computing Machinery.

ACM International Conference Proceeding Series

Vision-based control of UR5 robot to track a moving object under occlusion using Adaptive Kalman Filter

Electro discharge machining (EDM) is a popular unconventional machining process widely employed in die-making industries. Careful selection of process parameters such as pulse current, voltage, on and off time, etc. is essential for machining of hard and conductive materials using EDM. Previous researchers working in the area of EDM have extensively analyzed the machining performance through experimental study, modeling, and simulation and also by theoretical analysis. This article discusses the significant summary of the work performed by earlier researchers through a detailed literature survey. Relevant literature on EDM and impact of process parameters on performance measures such as surface quality, tool wear rate and material removal rate are reviewed. The challenge and limitation of EDM process are also highlighted in this article. It is observed that optimization of process parameters is essentially required for effective and economical machining. So, this article addresses the various issues related to EDM and also provides brief insight into some of the current generation applications of EDM process explored in various industries. © 2019 B. Nahak and A. Gupta, Published by EDP Sciences.