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This paper explores the barriers which hamper the utilization and the routinization of product lifecycle management (PLM) practices in manufacturing organizations. The paper aims to confirm the barriers and their rank in order to improve the PLM institutionalization status in firms. Core barriers have been explored in an automotive firm by applying multicriteria decision-making techniques. Further, the significance of these barriers were corroborated with the executives in the broader PLM domain through a t-test. This study confirmes the “lack of advanced IT infrastructure,” “lack of integration and interoperability,” and “training on the PLM systems” as the top three barriers to PLM utilization and routinization in manufacturing firms in India. [ABSTRACT FROM AUTHOR]

Gyrotrons are high-frequency, high-power microwave sources with potential applications in plasma generation, energy generation, spectroscopy, and security. The Department of Science and Technology initiated the development of a 42 GHz, 200 kW, continuous wave (CW) gyrotron for the Indian Tokamak system through a multi-institutional project. The activity is targeted toward indigenous development of India’s first high-power gyrotron. In gyro-devices, frequency of operation is determined by the cyclotron frequency, and thereby the magnetic field. The development of a high-field intensity normal conducting cavity magnet was an imperative step during the testing and integration of the gyrotron tube assembly to achieve the desired beam transmission with a moderate operating cost. A high and spatially homogeneous magnetic field (1.61 T) is required to be established in the beam–wave interaction region by the cavity magnet. The desired magnetic field, as a function of axial distance from the gun to the collector, is governed by the requirements of gun optics, focusing field in the interaction region, and the adiabatic expansion of the beam into the collector. A water cooled electromagnet has been designed to produce the requisite magnetic field in the cavity region over an axial length of 40 mm with field homogeneity better than ±0.35%. Magnet design was optimized to meet the field requirements in the cavity and cathode gun. Magnetic field simulations were carried out in conjunction with the electrostatic field and space charge analysis. This paper presents finite element computations, design optimization, development and testing of a continuous duty iron core electromagnet for a first harmonic interaction mode (TE03) gyrotron cavity. Magnetic, electrical, thermal, and hydraulic design of the electromagnet is discussed in this paper. [ABSTRACT FROM AUTHOR]

In multi-MW three-level neutral point clamped back-to-back (3L-NPC) power converters, power semiconductor devices are considered as most vulnerable components due to its thermo-mechanical fatigue stress. Particularly, rotor side converter (RSC) in doubly fed induction machine (DFIM) experiences high thermal stress during its operation around synchronous speed. It degrades the performance of power converter and reduces the lifetime availability of the drive. In practice, stabilization of temperature fluctuation across each power semiconductor device improves the efficiency and reliability of power converter. With respect to this prime aim, this paper proposes a carrier-based active thermal control method to regulate temperature fluctuation across power semiconductor devices in a multi-MW (5 x 5 MW) 3L-NPC power converters serving to a 250 MW asynchronous hydro-generating unit. To test the proposed active thermal control method, different operating conditions of a 250 MW DFIM hydro-generating unit (to be commissioned in Tehri pumped storage plant, India) are examined in MATLAB/PLECS environment. The designed active thermal control method effectively regulates mean junction temperature and temperature fluctuation of power semiconductor devices within a safe operating limit. The practical feasibility and adoptability of proposed active thermal control is examined through a 2.2-kW DFIM laboratory prototype. [ABSTRACT FROM AUTHOR]

This paper presents a clustering technique to rank the dominant modes of low frequency oscillations in power systems under model order uncertainty of the signal. The rotational invariance property of the signal subspace is utilized to obtain the modes of oscillations. Rotational invariance of the signal under multiple shifts is considered to obtain the preliminary estimates of the modes. Subsequently, the modes are clustered to obtain the dominant modes that belong to the signal subspace. A signal subspace participation index (SSPI) is used to rank the modes according to their dominance in signal subspace. Thereafter, the convex combination of the preliminary modes, estimated from the multiple shifts of the signal subspace, is used to obtain the final mode estimates. The simulation results are presented for signal generated using the modes obtained from a two-area system. Additionally, the methodology is also tested on field data obtained from the PMU installed at a generating station in India. [ABSTRACT FROM AUTHOR]

In order to enable a variable-speed operation in existing synchronous-machine-based fixed-speed pumped-storage power plant (PSPP), full-scale power converters are required. But it is not economical in case of large-size PSPP. Furthermore, full-scale power converters lead to increase the complexity of civil construction in case of underground powerhouses. Therefore, a doubly fed induction machine (DFIM) with a slip power rated power converter is an acceptable option for the storage dams with wide variation in water head (for e.g., Tehri Dam, India). In view of the reliability of converters used in such projects, thermal stress across the power semiconductor devices is a major cause for the failure of power converters. It is reported that 55% of failures in electric drives are due to thermal cycling or temperature rise in semiconductor devices. In consideration of this issue, this paper analyses active-thermal-control-based reactive power circulation in a five-channel parallel-connected back-to-back power converter fed 250-MW DFIM system (data collected from a 4 × 250 MW PSPP under construction at Tehri dam, India). The allowable limit of reactive power range is calculated in consideration of an operational strategy to be adopted, and the reactive power among the converters is circulated using the vector control technique. It is concluded that because of reactive power circulation among parallel-connected converters, temperature fluctuation is effectively stabilized. PLECS Blockset in MATLAB/Simulink software is used for this analysis. Experimental validation is carried out through a 2.2-kW scale-down DFIM laboratory prototype. [ABSTRACT FROM AUTHOR]

This paper presents a category theoretic ontology of Carnatic music. Our goals here are twofold. First, we will demonstrate the power and flexibility of conceptual modeling techniques based on a branch of mathematics called category theory (CT), using the structure of Carnatic music as an example. Second, we describe a platform for collaboration and research sharing in this area. The construction of this platform uses formal methods of CT (colimits) to merge our Carnatic ontology with a generic model of music information retrieval tasks. The latter model allows us to integrate multiple analytical methods, such as hidden Markov models, machine learning algorithms, and other data mining techniques like clustering, bagging, etc., in the analysis of a variety of different musical features. Furthermore, the framework facilitates the storage of musical performances based on the proposed ontology, making them available for additional analysis and integration. The proposed framework is extensible, allowing future work in the area of rāga recognition to build on our results, thereby facilitating collaborative research. Generally speaking, the methods presented here are intended as an exemplar for designing collaborative frameworks supporting reproducibility of computational analysis and simulation. [ABSTRACT FROM AUTHOR]

Wildfires are one of the most destructive disasters on the planet. They also significantly impact the land surface. Satellite data have been widely used to detect the outbreak and monitor the expansion of fire incidents for damage assessment and disaster management. Polar-orbiting satellite data have been used for several decades but data from geostationary satellites, which can provide observations with a high temporal resolution, have received much less attention. This paper utilizes data from FengYun-2G, a Chinese geostationary satellite, to detect wildfires in two selected research regions in January 2016. The detection algorithm systemizes image-based analysis to filter out obvious nonfire pixels and temporal analysis to confirm the true detections. Fire detection is based on comparisons between predicted and observed values. The results show that the proposed method has some advantages compared with the use of polar-orbiting satellite data, including early detection and continuous observation. The validation work is conducted based on the collection 6.1 Global Monthly Fire Location Product generated from fire detections by Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. The average accuracy within the target time is 56%, while the omission error rate is over 78%. In detail, the algorithm has a lower omission error rate in Australia while it fails in detecting most of the fire pixels in India. The dominance of small fire incidents, as well as low spatial resolution greatly limit the detection ability. Many small fires were beyond the ability of Stretched Visible and Infrared Spin Scan Radiometer (S-VISSR) data when no significant fire characteristics could be captured. Future development of the algorithm will focus on improving the results by enhancing the adaption to different regions, as well as, including multisource data sets. [ABSTRACT FROM AUTHOR]

The Soil Moisture Active Passive (SMAP) mission currently provides three surface soil moisture products based solely on instrument measurements. The three soil moisture products are: 1) the radiometer-only 36 km gridded; 2) a radiometer-only enhanced product gridded at 9 km; and 3) a high-resolution (3 km) SMAP-Sentinel active–passive product. It is important to validate these released SMAP soil moisture products over various land covers and hydroclimatic domains before they are routinely used in scientific research and applications. This paper evaluates SMAP-based soil moisture products for typical Indian conditions of extreme seasonal variability that leads to changes from very wet to dry soil, especially for the paddy dominated region. The assessment metrics indicate that the enhanced passive-only soil moisture product meets the SMAP accuracy requirement of 0.04 m3/m3 during the nongrowing season (NGS) with unbiased root-mean-square error (ubRMSE) values ranging between 0.025 and 0.036 m3/m3. However, this product underperformed during the paddy growing season (GS) with ubRMSE values ranging between 0.063 and 0.097 m3/m3. In addition, the SMAP-Sentinel active–passive soil moisture product shows satisfactory performance during the NGS (ubRMSE, 0.017–0.051 m3/m3), but during the GS, ubRMSE ranged between 0.089 and 0.104 m3/m3. Use of the vegetation water content climatology and low clay fraction in SMAP baseline algorithm (auxiliary database) that mismatched with the actual values may be the possible source of errors and biases in the SMAP soil moisture products. The reported study provides guidelines for the application of enhanced SMAP soil moisture products in India, especially for the tropical region, and provides information that can be used to improve the retrieval algorithm. [ABSTRACT FROM AUTHOR]

Increase penetration of intermittent renewable sources causes reduction and time variation in system inertia, forcing dynamic changes in system coherency status. Besides increased penetration levels, other factors like intermittent generation and change in distribution of renewables also influence the system coherency that needs to be addressed. This paper examines the impact of variability of renewables on system coherency and proposes a coherency identification method based on spectrum similarity approach. The proposed method uses discrete cosine Stockwell transform to derive multiple time-frequency (TF) features that captures pair-wise similarity between synchrophasor frequency signals. Thereafter, mean shift spectral clustering is used to cluster the buses with most homogeneous TF spectrum. The proposed method is validated with renewable generation in the IEEE-39 bus system and a real transmission system of India grid. [ABSTRACT FROM AUTHOR]

Common information model (CIM) in vogue represents transmission and distribution components, and market operations in the perspective of electrical system, as unified modeling language (UML) objects. UML is object centric. CIM can offer interoperability and facilitate model exchange for large systems and is being adopted by many utilities. However, dealing effectively with multiple business processes is the backbone of the restructured power systems. Since CIM lacks chronological process sense, this has to be superimposed on CIM models, which is not easy due to inherent limitations of UML. To overcome this, this paper proposes to utilize business process modeling notation (BPMN) standards as a kind of pre-processor. BPMN is used to represent process centric interoperability requirements as business objects. UML object representation in CIM model is derived subsequently from it. The proposal is illustrated with an application use case—deriving CIM model of day-ahead market (DAM) transaction of distribution company, from its business process representation. Semantic model of DAM transaction using CIM IEC 62325 (Markets) and extensions required are presented with a sample Indian system. DAM models in BPMN and CIM can be utilized to build an efficient software application. [ABSTRACT FROM PUBLISHER]

One of the responses to the fight against climate change by the developing world has been the large-scale adoption of solar energy. The adoption of solar energy in countries like India is propagating mainly through the development of energy producing photovoltaic farms. The realization of solar energy producing sites involves complex decisions and processes in the selection of sites whose knowhow may not rest with all the stakeholders supporting (e.g., banks financing the project) the industry value chain. In this article, we use the region of Bangalore in India as the case study to present how open innovation using satellite imagery can provide the necessary granularity to specifically aid in an independent initial assessment of the solar photovoltaic sites. We utilize the established analytical hierarchy process over the information extracted from open satellite data to calculate an overall site suitability index. The index takes into account the topographical, climatic, and environmental factors. Our results explain how the intervention of satellite imagery-based big data analytics can help in buying the confidence of investors in the solar industry value chain. Our study also demonstrates that open innovation using satellites can act as a platform for social product development. [ABSTRACT FROM AUTHOR]

Contribution: This study identifies the attributes of complexity that can be incorporated into engineering design problems at first-year undergraduate engineering projects. The findings are compiled as a set of guidelines to aid engineering educators in crafting design problems. Background: Engineering professionals solve complex problems like design problems, troubleshooting problems, system-analysis problems, and decision-making problems. To develop proficiency in solving such problems, accreditation bodies for engineering education mandate the development of knowledge and skills for solving complex problems. The literature presents several attributes of complexity, but it does not clearly state which of these attributes are relevant for first-year engineering problem-solving and incorporate them into the engineering curriculum. Research Question: This study qualitatively investigates the research question, “How to craft engineering design problems with known attributes of complexity for first-year undergraduate engineering education?” Methodology: The study is situated in a project-based learning course offered at first-year engineering at a university in India. It identifies the attributes of complexity in interdisciplinary (mechatronic) design projects (prototypes) through thematic analysis of faculty interviews. Further, this was validated by analyzing the prototypes. Findings: Several themes of complexity emerged; this article presents only two themes: 1) knowledge and 2) skills related to solving the engineering design problem and the types of relationships between the prototype’s functions. [ABSTRACT FROM AUTHOR]

Large-scale deployment of electric vehicles (EVs) is deleterious for distribution system operations. Unplanned installation of EV charging station (EVCS) deteriorates the voltage stability, reliability, and power quality of the distribution system leading to customer discontentment. This article proposes a novel approach for the proper placement of EVCS in a distribution network maintaining the system performance. The design of a test station with vehicle-to-grid (V2G) capability is outlined in this work. The test station is developed with five charging columns taking into consideration the standards and guidelines outlined in the Government of India EV policy. The charging station is connected to the power grid by a dc bus to which numerous EVs are attached. EVCS placement in the IEEE-33 bus radial distribution system is performed by developing six test scenarios. The test case results substantiate the potency of the reliability-index based approach for allocating EVCS both slow and fast chargers in a distribution network. Further, the maximal threshold value for placing the EVCS in various buses in a distribution system is determined using a novel electric vehicle placement index (EVPI). The novelty of the approach lies in the fact that it can include all operational parameters influenced owing to EV deployment, thereby maintaining the overall system performance without any physical restructuring of the network. The efficacy of the approach and the severity level of EVCS placement are validated for a real-time distribution system in Kerala, India. [ABSTRACT FROM AUTHOR]

By studying the spectral reflectance features of different land cover types and leveraging information of primarily “BLUE” band along with “RED” and “NIR” bands, this article seeks to introduce a new built-up index such as powered B1 built-up index (PB1BI). The proposed index, while being conceptually simple and computationally inexpensive, can extract the built-up areas from Landsat7 satellite images efficiently. For Landsat7 satellite imagery, classification performances of the proposed index along with support vector machine (SVM), artificial neural network (ANN), and three existing built-up indices have been examined for three study sites of 1° Latitude $\times 1^\circ $ Longitude ($\approx 12\,100~{\mathrm {sq}}\cdot {\mathrm {km}}$) area from three diverse geographical regions in India. The computed value of the M-Statistics for PB1BI is consistently greater than 1.80, indicating a better spectral separability between built-up and nonbuilt-up classes by the index. In order to improve the performance of the built-up indices, this article has suggested a bootstrapping method for threshold estimation in addition to the existing Otsu’s method for the same. It has been found that using bootstrapping method instead of Otsu’s method for threshold estimation has helped to improve the classification performance of built-up indices up to 17.75% and 40.49% in terms of overall accuracy and kappa ($\kappa $) coefficient, respectively. It has been observed that for the validation set, average overall accuracy (97.45%) and kappa ($\kappa $) coefficient (0.907) of PB1BI for considered study sites are not only significantly higher than existing indices but also comparable with the same of SVM (99.10% and 0.942) and ANN (87.24% and 0.450). This article has also shown that the proposed index provides a stable performance for multitemporal analysis of the study sites and is able to capture growth in built-up region in time horizon. The classification performance of PB1BI has also been verified for Landsat8 imagery across 11 study sites from different continents around the globe, and the results show overall accuracy and $\kappa $ to be consistently more than 90% and 0.75, respectively. For considered study sites, the reported values of average accuracy and $\kappa $ of PB1BI for built-up classification using Landsat8 satellite data are 95.7151% and 0.8843, respectively. [ABSTRACT FROM AUTHOR]

Presents information on the ISTAS 2016 conference. [ABSTRACT FROM PUBLISHER]

Recent growth in seaborne trade has increased the tugboat operation cycle to maneuver incoming marine vessels at port. To meet the tugboat load demand for maneuvering, multiple power sources are being employed on-board. This necessitates a coordinated control strategy for the effective operation of these multiple power sources. To design an effective coordinated control strategy, this article initially estimates multiple power sources capacities (doubly fed induction machine (DFIM) and battery storage system) for a diesel-electric tugboat system based on a real-time tugboat operation cycle obtained from Visakhapatnam port, India. With respect to these multiple power sources, a coordinated control strategy for a better fuel efficiency is proposed based on a state machine control algorithm. The proposed control strategy operates a variable speed diesel-electric generator (diesel engine coupled DFIM) at a minimum specific fuel consumption value and battery based on its state of charge. To show the efficacy of the proposed variable speed diesel-electric system, fuel consumption is computed, which resulted in 26.42% of saving in comparison with a traditionally used diesel-mechanical tugboat. To evaluate the real-time system (2 MW DFIM + 150 kWh battery), MATLAB/Simulink tool is used and an experimental demonstration is performed on a laboratory prototype. [ABSTRACT FROM AUTHOR]

Background: Although effective communication has been the most important attribute of success in the workplace, poor communication has hindered employees from performing well. This outcome worsens when communication occurs between cross-generational groups in an organization. Literature review: Prior research suggests that Millennials, who make up a large cohort of the population in workplaces, are technologically savvy, multitasking, and result-oriented but considered to be deficient in their communication skills. There exists a divergence between Millennials and previous generations in terms of their attitude, behavior, and value system. Research questions: 1. Is there a significant difference in the communication styles of Millennials and their predecessors in India? 2. Are Millennials communication deficient? 3. Do their Gen X predecessors lack the skills to recognize different generational preferences in order to effectively lead a multigenerational workforce? Research methodology: For this investigation, a 36-item questionnaire measured 12 interpersonal styles through three items each on a Likert-type scale. Results: The results presented in this study are not limited to generational stereotyping but rather claim to be accurate and context-sensitive. Millennials defied general stereotypes in several ways. The findings confirmed that although Millennials are different, they are not necessarily communication deficient. Conclusion: To flourish, Millennials and their predecessor and successor generations should strive to adapt to each other by avoiding stereotypes. [ABSTRACT FROM AUTHOR]

Electric power demand is growing at an exponential rate due to establishment of industries and economic growth in the country. Central electricity authority of India (CEA) has estimated per capita electricity consumption will increase at a rate of 6 percent per annum, this will increase the load on the transmission and distribution system. Limitations of Right of Way (ROW) has made it difficult to construct new lines, particularly in metropolitan and densely populated cities, hence high temperature low sag (HTLS) conductors are being used adopted, several projects in the country are being executed to overcome the problem of burdening of transmission/distribution system. HTLS conductors operate at 2–3 times higher ampacity and thermal rating, hence can be used for higher power transmission without upgrading the existing towers and infrastructure. The present investigation aims to understand and estimate the conductor temperature and ampacity dependent on different parameters like wind velocity, wind angle, emissivity and fault current level. The investigation highlights the dynamic thermal rating of HTLS conductor with change in wind velocity and angle, thermal performance of conductor during fault condition and thermal rating with emissivity, absorptivity and ambient temperature during flow of fault current is presented. A new experimental setup is established to investigate the performance of HTLS and Traction copper conductor in the laboratory, attempt has been made to study effect of magnetic fields and conduct EBSD analysis, some important conclusions drawn from the investigations are analyzed and presented. [ABSTRACT FROM AUTHOR]

Large capacity hydrogenerators are operated at overloads during the period of excess water flow in the river or frequency support to the grid at peak hours. The extensive conditions may extend to six weeks with 20% overload for a typical hydropower plant located in the northern region of India. High-power, low-speed, direct-driven hydroturbine synchronous generators (HTSGs) are having resistance in rising temperature and self-cooling techniques to withstand the multiple loading points. This article presents a 250-MW CB 870/300-28 HTSG machine modeling along with electromagnetic design and simulations through a three-dimensional finite-element analysis software. The temperature distribution of the machine, operates at 10% and 20% continuous overloads, are explored via a coupled thermal and fluid-dynamical analysis. The simulated thermal results at continuous overloads are presented and are validated with a case plant's test report. A parallel study when the load goes unbalanced at overloads is done through simulation and a prototype validation of a 2.2-kW machine is substantiated in addition. The strength and flexibility of the operation of this machine assist the generalized results to operate at 20% overload continuously with the utility of thermal distribution. [ABSTRACT FROM AUTHOR]

The Government of India has undertaken the ambitious target of 175-GW installed capacity of renewable power by 2022 as part of its climate treaty commitments.1 This will amount to 37% of projected installed capacity, second to coal and lignite (45%) and more than hydropower (11%). It has also undertaken a program of universal electricity access to all through the scheme called "Pradhan Mantri Sahaj Bijli Har Ghar Yojana" or "Saubhagya." [ABSTRACT FROM AUTHOR]

Accurate soil moisture data, critical for many applications such as agriculture and estimation of ground water, is limited worldwide, and particularly over India, by the absence of sustained multisite observations. A long-term sustained soil moisture observation at four vertical levels (5, 15, 50, and 100 cm) is now available at several locations over India under a multi-institutional program Climate Observations and Modeling Network (COMoN) led by CSIR, India. At the same time, a high resolution (0.1^\circ\times 0.1^\circ ) daily (moving 5-day mean) surface relative soil moisture data set has now become available from the Advanced Scatterometer (ASCAT) . However, there is a need to compare remotely sensed data and in situ observations to ensure consistency and quantify uncertainties. This is particularly true for India characterized by diverse climatic zones. We present a comparative analysis of gridded ASCAT soil moisture data and in situ COMoN station data over six locations in India during the period 2010–2013. A multiscale analysis is carried out involving daily, weekly, monthly, and seasonal timescales at different geographical locations. Analyses show that the two data sets are generally consistent, although there are seasonalities in the agreement; the correlation coefficient is higher for the wet season (summer, autumn), and moderate for dry season (winter, spring) . The correlation coefficients are ranged from 0.73 to 0.91 and above 99% significance level. The results quantify the reliability and robustness of ASCAT soil moisture over different climatic regions in India; the results also identify certain differences between the two data sets. [ABSTRACT FROM PUBLISHER]

Discusses the social and societal implications of biometric registration in India. [ABSTRACT FROM PUBLISHER]