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Article
Publication date: 25 June 2019

Gus Nasif, R.M. Barron, Ram Balachandar and Julio Villafuerte

Application of cold spray technology may exhibit significant benefits for the additive manufacturing process, particularly for producing intricate objects. To ascertain…

Abstract

Purpose

Application of cold spray technology may exhibit significant benefits for the additive manufacturing process, particularly for producing intricate objects. To ascertain the feasibility of such an application, this paper aims to present a numerical investigation of the effect of scaling down a convergent-divergent (de Laval) nozzle, which is typically used in the cold spray industry, on the compressible flow parameters and thermal characteristics.

Design/methodology/approach

The Navier–Stokes equations and energy equation governing compressible flow are numerically solved using a finite volume method with a coupled solver. The conjugate heat transfer technique is used to couple fluid and solid heat transfer domains and predict the local heat transfer coefficient between the solid and fluid. The use of various RANS turbulence models has also been investigated to quantify the effect of the turbulence model on the simulation.

Findings

The numerical results reveal that the flow and thermal characteristics are altered as the convergent-divergent nozzle is scaled down. The static pressure and temperature profiles at any section in the nozzle are shifted toward higher values, while the Mach number profile at any section in the nozzle is shifted toward a lower Mach number. The turbulent kinetic energy at the nozzle exit increases with the scaling down of the nozzle geometry. This study also provides convincing evidence that the adiabatic approach is still suitable even though the temperature of the nozzle wall is extremely high, as required for industrial application. Results indicate that it is feasible to use the available capabilities of the cold spray technology for additive manufacturing after scaling down the nozzle.

Originality/value

The idea of adopting cold spray technology for additive manufacturing is new and innovative. To develop this idea into a viable commercial product, a thorough understanding of the flow physics within a cold spray nozzle is required. The simulation results discussed in this paper demonstrate the effect that scaling down of a convergent-divergent nozzle has on the flow characteristics in the nozzle.

Details

International Journal of Numerical Methods for Heat & Fluid Flow, vol. 29 no. 7
Type: Research Article
ISSN: 0961-5539

Keywords

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Article
Publication date: 17 January 2018

Balachandar Pandiyan, Sivarajan Ganesan, Nadanasabapathy Jayakumar and Srikrishna Subramanian

The ever-stringent environmental regulations force power producers to produce electricity at the cheapest price and with minimum pollutant emission levels. The electrical…

Abstract

Purpose

The ever-stringent environmental regulations force power producers to produce electricity at the cheapest price and with minimum pollutant emission levels. The electrical power generation from fossil fuel releases several contaminants into the air, and this becomes excrescent if the generating unit is fed by multiple fuel sources (MFSs). Inclusion of this issue in operational tasks is a welcome perspective. This paper aims to develop a multi-objective model comprising total fuel cost and pollutant emission.

Design/methodology/approach

The cost-effective and environmentally responsive power system operations in the presence of MFSs can be recognised as a multi-objective constrained optimisation problem with conflicting operational objectives. The complexity of the problem requires a suitable optimisation tool. Ant lion algorithm (ALA), the most recent nature-inspired algorithm, was used as the main optimisation tool because of its salient characteristics. The fuzzy decision-making mechanism has been integrated to determine the best compromised solution in the multi-objective framework.

Findings

This paper is the first to propose a more precise and practical operational model for studying a multi-fuel power dispatch scenario considering valve-point effects and CO2 emission. The modern meta-heuristic algorithm ALA is applied for the first time to address the economic operation of thermal power systems with multiple fuel options.

Practical implications

Power companies aim to make profit by abiding by the norms of the regulatory board. To achieve economic benefits, the power system must be analysed using an accurate operational model. The proposed model integrates total fuel cost, valve-point loadings and CO2 emission, which are prevailing power system operational objectives. The economic advantages of the operational model can be observed through economic deviation indices, and the performed analysis validates that the developed model corresponds to the actual power operation.

Originality/value

The realistic operational model is proposed by considering total fuel and pollutant emission, and the ALA is applied for the first time to address the proposed multi-objective problem. To validate the effectiveness of ALA, it is implemented in standard test systems with varying generating units (10-100) and the IEEE 30 bus system, and various kinds of power system operations are performed. Moreover, the comparison and performance analysis confirm that the current proposal is found enhanced in terms of solution quality.

Details

International Journal of Energy Sector Management, vol. 12 no. 1
Type: Research Article
ISSN: 1750-6220

Keywords

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Article
Publication date: 24 August 2018

Hongbin Liu, Xinrong Su and Xin Yuan

Adopting large eddy simulation (LES) to simulate the complex flow in turbomachinery is appropriate to overcome the limitation of current Reynolds-Averaged Navier–Stokes…

Abstract

Purpose

Adopting large eddy simulation (LES) to simulate the complex flow in turbomachinery is appropriate to overcome the limitation of current Reynolds-Averaged Navier–Stokes modelling and it provides a deeper understanding of the complicated transitional and turbulent flow mechanism; however, the large computational cost limits its application in high Reynolds number flow. This study aims to develop a three-dimensional GPU-enabled parallel-unstructured solver to speed up the high-fidelity LES simulation.

Design/methodology/approach

Compared to the central processing units (CPUs), graphics processing units (GPUs) can provide higher computational speed. This work aims to develop a three-dimensional GPU-enabled parallel-unstructured solver to speed up the high-fidelity LES simulation. A set of low-dissipation schemes designed for unstructured mesh is implemented with compute unified device architecture programming model. Several key parameters affecting the performance of the GPU code are discussed and further speed-up can be obtained by analysing the underlying finite volume-based numerical scheme.

Findings

The results show that an acceleration ratio of approximately 84 (on a single GPU) for double precision algorithm can be achieved with this unstructured GPU code. The transitional flow inside a compressor is simulated and the computational efficiency has been improved greatly. The transition process is discussed and the role of K-H instability playing in the transition mechanism is verified.

Practical/implications

The speed-up gained from GPU-enabled solver reaches 84 compared to original code running on CPU and the vast speed-up enables the fast-turnaround high-fidelity LES simulation.

Originality/value

The GPU-enabled flow solver is implemented and optimized according to the feature of finite volume scheme. The solving time is reduced remarkably and the detail structures including vortices are captured.

Details

Engineering Computations, vol. 35 no. 5
Type: Research Article
ISSN: 0264-4401

Keywords

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Article
Publication date: 15 June 2010

Emad Samadiani and Yogendra Joshi

The purpose of this paper is to review the available reduced order modeling approaches in the literature for predicting the flow and specially temperature fields inside…

Abstract

Purpose

The purpose of this paper is to review the available reduced order modeling approaches in the literature for predicting the flow and specially temperature fields inside data centers in terms of the involved design parameters.

Design/methodology/approach

This paper begins with a motivation for flow/thermal modeling needs for designing an energy‐efficient thermal management system in data centers. Recent studies on air velocity and temperature field simulations in data centers through computational fluid dynamics/heat transfer (CFD/HT) are reviewed. Meta‐modeling and reduced order modeling are tools to generate accurate and rapid surrogate models for a complex system. These tools, with a focus on low‐dimensional models of turbulent flows are reviewed. Reduced order modeling techniques based on turbulent coherent structures identification, in particular the proper orthogonal decomposition (POD) are explained and reviewed in more details. Then, the available approaches for rapid thermal modeling of data centers are reviewed. Finally, recent studies on generating POD‐based reduced order thermal models of data centers are reviewed and representative results are presented and compared for a case study.

Findings

It is concluded that low‐dimensional models are needed in order to predict the multi‐parameter dependent thermal behavior of data centers accurately and rapidly for design and control purposes. POD‐based techniques have shown great approximation for multi‐parameter thermal modeling of data centers. It is believed that wavelet‐based techniques due to the their ability to separate between coherent and incoherent structures – something that POD cannot do – can be considered as new promising tools for reduced order thermal modeling of complex electronic systems such as data centers

Originality/value

The paper reviews different numerical methods and provides the reader with some insight for reduced order thermal modeling of complex convective systems such as data centers.

Details

International Journal of Numerical Methods for Heat & Fluid Flow, vol. 20 no. 5
Type: Research Article
ISSN: 0961-5539

Keywords

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Article
Publication date: 3 October 2019

Dharmendra B.V., Shyam Prasad Kodali and Nageswara Rao Boggarapu

The purpose of this paper is to adopt the multi-objective optimization technique for identifying a set of optimum abrasive water jet machining (AWJM) parameters to achieve…

Abstract

Purpose

The purpose of this paper is to adopt the multi-objective optimization technique for identifying a set of optimum abrasive water jet machining (AWJM) parameters to achieve maximum material removal rate (MRR) and minimum surface roughness.

Design/methodology/approach

Data of a few experiments as per the Taguchi’s orthogonal array are considered for achieving maximum MRR and minimum surface roughness (Ra) of the Inconel718. Analysis of variance is performed to understand the statistical significance of AWJM input process parameters.

Findings

Empirical relations are developed for MRR and Ra in terms of the AWJM process parameters and demonstrated their adequacy through comparison of test results.

Research limitations/implications

The signal-to-noise ratio transformation should be applied to take in to account the scatter in the repetition of tests in each test run. But, many researchers have adopted this transformation on a single output response of each test run, which has no added advantage other than additional computational task. This paper explains the impact of insignificant process parameter in selection of optimal process parameters. This paper demands drawbacks and complexity in existing theories prior to use new algorithms.

Practical implications

Taguchi approach is quite simple and easy to handle optimization problems, which has no practical implications (if it handles properly). There is no necessity to hunt for new algorithms for obtaining solution for multi-objective optimization AWJM process.

Originality/value

This paper deals with a case study, which demonstrates the simplicity of the Taguchi approach in solving multi-objective optimization problems with a few number of experiments.

Details

Multidiscipline Modeling in Materials and Structures, vol. 16 no. 2
Type: Research Article
ISSN: 1573-6105

Keywords

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