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Accurate measurements of the temperature distributions in hot section components are indispensable for the prognostic and health management of gas turbines. Thin film thermocouple (TFTC) sensors, directly fabricated on the surface of a component, add negligible mass and create little or no disturbance to airflow, and therefore, can provide accurate measurements of fast temperature fluctuations of gas turbines. The purpose of this paper is to evaluate TFTC sensors fabricated by combining pulsed laser deposition (PLD) and micromachining techniques (LM).

The “dry” PLD/LM fabrication approach allows for excellent control of the chemical composition and physical characteristics of the constituent layers and their interfaces, thus achieving good adhesion of the layers to the substrate.

The results of thermal cyclic durability testing of the fabricated TFTC sensors demonstrated that the proposed PLD-based approach can be used to fabricate sensors that are fully functional at temperatures up to 750°C. Analyses of the sensor performance during durability testing revealed: the existence of a threshold temperature below which accurate temperature measurements were achieved; an abrupt drop in the sensor output occurring when the sensor temperature exceeded the threshold value, with a fast recovery of the sensor output once the temperature was reduced below the threshold level; and sensor “training” capable of increasing the threshold value of the TFTC through its exposure to above-the-threshold temperatures.

The work is the first time to demonstrate that simple PLD and LM processes can be used to fabricate TFTC that are fully functional at temperatures up to 750°C.

The learning outcomes are to remember the overall context of global supply chain management from a stakeholder perspective, to understand the context of material handling movement in a mining industry, to apply the overall knowledge of linear programming in a supply chain context, to analyze the different constraints with flow of goods at different nodes in various location hubs and convert the same into the optimization problem and to evaluate carefully the different costs associated at different levels and then finding the optimal solution that minimizes the total cost.

This case proposes a mixed integer multi-echelon analytical model integrated with the scenario tree analysis. The integrated model is used to optimize the allocation of volumes at various stages of the supply chain of exporters of bulk materials like iron ore from Goa, India, to various countries in Asia. The scenario tree analysis is then used to evaluate decisions under certainty with demand as the stochastic parameter. The proposed integrated model has potential for collaboration in the supply chain and facilitating network design, inventory and transportation planning and policy analysis.

This course is suitable at the MBA level for the following courses: Operations Research (Focus/Session: Applications on Supply Chain Management), Supply Chain Management (Focus/Session: Global Supply Chain Management, Logistics Planning, Distribution Network), Logistics Management (Focus/Session: Transportation Planning) nd Operations Strategy (Focus/Session: Location Node Strategy).

Teaching Notes are available for educators only.

CSS 9: Operations and Logistics.

Purpose – This chapter asks what we should make of the gift exchanges that take place between workers and their managers on the floor of a massive offshore manufacturing unit in South India. Such exchanges appear anomalous in the ethnography of global manufacturing yet here they underpinned the organisation of hyper-intensive production processes.

Findings – Following diverse acts of giving, this chapter shows how these transactions constituted the performative and relational grounds on which workers came to know themselves and sought to shape the world around them. In doing so it extends the anthropology of work and labour by showing that acts of giving are integral to global commodity production.

The learning outcomes of this paper are as follows: to understand the context of seaport logistics and supply chain design structure, to apply Monte Carlo simulation in the interface of the supply chain and to analyze the Monte Carlo simulation algorithm and statistical techniques for identifying the key seaport logistics factors.

It was 9:00 p.m. on November 10, 2020, and Nishadh Amonkar, the CEO of OCTO supply chain management (SCM) was glued to the television watching the final cricket match of the Indian Premier League, 2020. Amonkar’s mobile phone rang and it was a call from Vinod Nair, a member Logistics Panel of Ranji Industries Federation. Nair informed Amonkar that it was related to the rejection of several export consignments of agricultural products from Ranji (in the western part of India). The rejection was due to the deterioration in the quality of the exported agricultural products during transit from Ranji to various locations in Europe.

This course is suitable at the MBA level for the following courses: Operations research (Focus/Session: Applications on Monte Carlo Simulation). SCM (Focus/Session: Global SCM, Logistics Planning, Distribution Network). Logistics management (Focus/Session: Transportation Planning). Business statistics (Focus/Session: Application of Hypothesis Testing).

Teaching Notes are available for educators only.

CSS 9: Operations and logistics.

This case introduces the context of seaport logistics supply chain management with a focus on the issues of risk management in handling and transportation of dangerous goods (DG). The authors present the following learning objectives under the overarching framework of Bloom’s Taxonomy as follows: To understand the severity of handling and transportation of DG in the export supply chain context. To understand the relevance of multi-criteria decision-making in risk assessment. To apply Delphi Technique to appropriately explain the process of risk assessment in a supply-chain context.

It was midnight on December 21, 2020, and Nishadh Amonkar, Chief Executive Officer, Yorokobi, was still awake recollecting his telecon with Tushar Rane, the Head-Materials, Western Maharashtra site of Crop Life Pvt Ltd. The organization was developing and manufacturing pesticides and other specialty chemicals for its clients worldwide. As new and diverse products were being manufactured in the organization, transportation of the products was becoming challenging. The case highlights the need for a data driven risk assessment approach to manage supply chains that were prone to product driven risks such as the handling and transportation of DG.

This course is suitable at the Master of Business Administration level for the following courses: Supply Chain Management (Focus/Session: Supply Chain Risk Management), Logistics Management (Focus/Session: Risks in Logistics and Supply Chain), Research Methodology (Focus/Session: Application of Delphi Technique).

Teaching notes are available for educators only.

CSS 9: Operations and logistics.

This study aims to investigate the effects of thermal buoyancy and flow incidence angles on mixed convection heat transfer and vortex-induced vibration (VIV) of an elastically mounted circular cylinder. The focus is on understanding how varying these parameters influences the vibration amplitudes in both the x and y directions and the overall heat transfer performance.

The research involves a numerical simulation of thermal fluid-structure interactions by integrating rigid-body motion equations with heat and fluid flow solvers. The cylinder operates at a lower temperature than the mainstream flow, and flow incidence angles range from 0° (opposing gravity) to 90° (perpendicular to gravity). The methodology is validated by comparing the results with established data on VIV for a cylinder vibrating in one direction under thermal buoyancy effects.

The study reveals that, without buoyancy (Ri = 0), increasing the flow angle from 0° to 90° decreases the vibration amplitude along the x-direction (A_x) while increasing it along the y-direction (A_y) across various reduced velocities (U_r). When buoyancy effects are introduced (Ri = −1), A_x peaks at specific U_r values depending on the flow angle, with significant variations observed. The maximum increase in A_x at Ri = −1 is over 15 times at U_r = 9 for a 0° angle, and A_y shows a more than 10-fold increase at U_r = 8 for a 30° angle. Additionally, adjusting the flow angle results in up to an 8% increase in the mean Nusselt number at Ri = −1.

This research provides novel insights into the combined effects of flow incidence angles and thermal buoyancy on VIV and heat transfer in an elastically mounted cylinder.

In clinical analysis, medical image segmentation is an important step to study the anatomical structure. This helps to diagnose and classify abnormality in the image. The wide variations in the image modality and limitations in the acquisition process of instruments make this segmentation challenging. This paper aims to propose a semi-automatic model to tackle these challenges and to segment medical images.

The authors propose Legendre polynomial-based active contour to segment region of interest (ROI) from the noisy, low-resolution and inhomogeneous medical images using the soft computing and multi-resolution framework. In the first phase, initial segmentation (i.e. prior clustering) is obtained from low-resolution medical images using fuzzy C-mean (FCM) clustering and noise is suppressed using wavelet energy-based multi-resolution approach. In the second phase, resultant segmentation is obtained using the Legendre polynomial-based level set approach.

The proposed model is tested on different medical images such as x-ray images for brain tumor identification, magnetic resonance imaging (MRI), spine images, blood cells and blood vessels. The rigorous analysis of the model is carried out by calculating the improvement against noise, required processing time and accuracy of the segmentation. The comparative analysis concludes that the proposed model withstands the noise and succeeds to segment any type of medical modality achieving an average accuracy of 99.57%.

The proposed design is an improvement to the Legendre level set (L2S) model. The integration of FCM and wavelet transform in L2S makes model insensitive to noise and intensity inhomogeneity and hence it succeeds to segment ROI from a wide variety of medical images even for the images where L2S failed to segment them.

The purpose of this paper is to investigate the influence of forced, in-line oscillation of a circular cylinder on an incoming incompressible flow field at different Reynolds numbers.

A space-time finite element approach is employed to model the flow around an oscillating cylinder.

The results show that two (2S), four (2P, two pair) and three vortices (P+S, one pair and one single) are shed in each cycle. In addition, a 2P _o mode is also observed, which is similar to the 2P mode but the vortices of the 2P _o mode differ in strength. The 2P mode of vortex shedding is observed along the entire wake of the flow field and 2P _o mode in the far wake. In some cases, the vortex street is transformed as it travels towards the exit to produce new patterns. One such pattern is observed for the first time in the present work, which is referred to as 2P _o* mode. The drag and lift coefficients observed are perfectly periodic at a Reynolds number of 200 and they reach a chaotic pattern as the Reynolds number is increased to a value of 350.

Originality of the paper lies in the observation of 2P vortex shedding mode or its variants in the downstream of the cylinder.