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Techno-Economic analysis of solar thermal seasonal thermochemical storage for Indian Himalayan cities
No full textThermochemical reactor-based seasonal energy storage is a promising technology that ensures reliable and sustainable space heating in the challenging remote locations of the Indian Himalayan Region. However, the deployment of such solutions is currently at the nascent stage owing to a lack of application-specific techno-economic analysis. In this study, a modular radial flow annular reactor using the strontium bromide hexahydrate-monohydrate conversion reaction is designed for long-term energy storage, and performance analysis is conducted for eight cities from the Indian Himalayan Region, each with distinct meteorological characteristics, to evaluate the system’s suitability. A fixed-sized room is chosen as the representative conditioned space to evaluate heating demands using a building simulation model. The City of Leh in the Greater Himalayas exhibits the highest heating demand of 7824 kWh annually, paired with the highest solar irradiance of ∼2100 kWh/m2. The numerical model developed for simulating the reactor is validated against a small-scale reactor setup and is used further for hourly performance analysis. The year-long charging and discharging efficiencies are nearly location-independent, with consistent values of ∼35 % and ∼74 %, respectively. The system configuration with direct solar heating capabilities exhibits better overall system efficiency and economic feasibility, with the levelized cost of heating in the range of INR 33–51/kWh. The heating cost is higher than that of conventional electric systems but is competitive with diesel-based heating (>INR 40/kWh). The higher system utilization in Leh leads to the lowest levelized costs of heating (INR 31/kWh) and CO2 avoidance (INR 29,093 /mtCO2). The comprehensive multi-location analysis provides key insights regarding the applicability and viability of the proposed systems for space heating in remote regions
Random Heterogeneous Neurochaos Learning Architecture for Data Classification
Full text linkInspired by the human brain's structure and function, Artificial Neural Networks (ANN) were developed for data classification. However, existing Neural Networks, including Deep Neural Networks, do not mimic the brain's rich structure. They lack key features such as randomness and neuron heterogeneity, which are inherently chaotic in their firing behavior. Neurochaos Learning (NL), a chaos-based neural network, recently employed one-dimensional chaotic maps like Generalized Lüroth Series (GLS) and Logistic map as neurons. For the first time, we propose a random heterogeneous extension of NL, where various chaotic neurons are randomly placed in the input layer, mimicking the randomness and heterogeneous nature of human brain networks. We evaluated the performance of the newly proposed Random Heterogeneous Neurochaos Learning (RHNL) architectures combined with traditional Machine Learning (ML) methods. On public datasets, RHNL outperformed both homogeneous NL and fixed heterogeneous NL architectures in nearly all classification tasks. RHNL achieved high F1 scores on the Wine dataset (1.0), Bank Note Authentication dataset (0.99), Breast Cancer Wisconsin dataset (0.99), and Free Spoken Digit Dataset (FSDD) (0.98). These RHNL results are among the best in the literature for these datasets. We investigated RHNL performance on image datasets, where it outperformed stand-alone ML classifiers. In low training sample regimes, RHNL was the best among stand-alone ML. Our architecture bridges the gap between existing ANN architectures and the human brain's chaotic, random, and heterogeneous properties. We foresee the development of several novel learning algorithms centered around Random Heterogeneous Neurochaos Learning in the coming days
Doctoral Research Programs in India: Bridging Policy Gaps for Knowledge Economy’s Imperative
No full textThe Doctoral Program of any country is the central pillar of higher education. The conspicuous absence of a well-thought-out doctoral program in India's national research policy has resulted in asymmetries in policies and practices related to research and development. The history of doctoral research in India presents a unique trajectory with a mixed influence of the colonial past and isolated efforts of genuine intellectuals who have thrived in an environment of deep motivation and passion that defined their research pursuits. India will have to ask more profound questions regarding the quality of doctoral education and the nature of students being produced/created. How does one enhance quality, and what is the role of faculty, students, and institutions? What is the role of doctoral research in influencing learning, pedagogic practices, and curriculum in preparing a citizenry to influence growth and development at the national and global levels? While reviewing global practices and policies, this chapter attempts to draw on best practices while also addressing the opportunities and challenges that reflect the realities of developing countries, particularly India
The Afghanistan Earthquake of 21 June 2022: The Role of Compressional Step-Overs in Seismogenesis
No full textThe Afghanistan earthquake of 21 June 2022 ruptured a ~10 km-long fault segment in the North Waziristan–Bannu fault system (NWBFS) located towards the north of the Katawaz Basin. The earthquake was shallow and reportedly caused widespread devastation. In this article, we investigated the long-term, i.e., geological and geomorphological, evidence of deformation along the earthquake segment. For comparison, we also studied the short-term space geodetic and remote sensing results documenting a visible offset between the fault traces. Focusing on the fault modelling and on the published results, it is thus clear that the earthquake rupture did not reach the surface; instead, it stopped in the shallow sub-surface at ~1 km depth. Moreover, the InSAR analyses show some technical issues, such as coherence loss, etc., likely due to severe ground-shaking leaving some gaps in the results; geological and geomorphological evidence complemented this information. As an outcome of this research, we confirmed that InSAR results could generally capture the overall fault geometry at depth, even in cases of blind faulting, whereas the detailed geometry of the tectonic structure, in this case with a right stepping en-echelon pattern, could be successfully captured by combining it with geological and geomorphological approaches and optical remote sensing observations. Accordingly, the right stepping fault generates a restraining bend in the dominantly left-lateral shear zone. Therefore, such fault stepovers are capable of localizing strain and could act as loci for seismic ruptures, bearing strong implications for the seismic hazard assessment of the region, as well as of other strike-slip fault zones
A Strategy for Migrant Workers
No full textAs millions of agriculturists leave agriculture without adequate non-agricultural activities in the vicinity of their villages they are forced to travel across India for work. The uncertainty of their urban jobs as well as the high cost of living in the city ensure that they only travel to the city for specific assignments. This chapter notes the implications of these trends and calls for interventions that increase the possibility of non-agricultural opportunities emerging closer to the regions where workers are moving out of agriculture
Skills Training, Migration and Employment: The Case of Raichur in Northern Karnataka
No full textResponding to India's continuing employment crisis, despite high rates of economic growth, the Skill India policy enacted in 2009, and re-enacted in 2014 as the Pradhan Mantri Kaushal Vikas Yojana (PMKVY), was designed to train both rural and urban youth, who have high school diplomas or college degrees, in vocational skills. Skirting the issue of the lack of growth of jobs in India, the purpose of Skill India was to prepare a young workforce to meet the needs of the emerging urban economy, particularly the service sector, which leads economic growth in the current phase. This paradigm of creating a workforce, rather than work, speaks to several critical debates framing India's development; thus, a central question that has been asked is, can services indeed lead to growth in the context of a labour surplus economy? This question becomes moot given that the growth of jobs in services has been mainly in the lower rungs, or in low-value-added work. Service jobs at lower levels are typically in the informal sector with low salaries and unprotected tenures. Finally, if skills are seen as the bridge that will bring unemployed rural youth into the fold of cities, the validity of this vision is deeply challenged given the low quality of jobs and lives that the urban informal sector offers, often compelling young men and women to return to their villages. Youth have turned their backs on agriculture but remain deeply connected to their rural roots, not only as home but as a possible place from where better lives can be built if sustainable work can be found. It is in this space that the Skill Indi
A case study on the feasibility and optimization of wind farm deployment in India
No full textA major share of the global energy demand is currently met by fossil fuels. However, environmental concerns and dwindling reserves have necessitated a progressive shift toward renewable energy. Ranked fourth globally in wind power installed capacity, India plans to implement a new wind farm design in Anjugramam, Tamil Nadu. The present study provides a novel, systematic pre-installation feasibility assessment for this specific, sanctioned onshore wind farm, focusing on the deployment of large, utility-scale onshore turbines (Siemens SWT-4.0–120), an area that is not adequately explored in the Indian context compared to studies on smaller, localized applications. The assessment considers turbine placement, space, and environmental impacts, and a modern simulation package like WindPro software is employed. Key parameters, including wind strength, energy output, noise distribution, shadow flicker, visual impact, and greenhouse gas (GHG) emissions, are evaluated. For the proposed Anjugramam wind farm comprising two 4 MW Siemens onshore wind turbines, the study projects an annual energy production (AEP) of 43,388.1 MWh. This level of clean energy generation is estimated to achieve an annual GHG emission reduction of 22,822.14 tonnes of CO2 equivalent compared to conventional energy sources. Noise modeling indicated levels between 55–58 dB within the wind farm array, and zone of visual influence (ZVI) analysis showed that at least one turbine would be visible from 91.8% of the surrounding viewpoints. Further economic analysis projects a levelized cost of energy (LCOE) for the wind farm at approximately ¢2.42–2.64/kWh (excluding monetized carbon benefits), which is found competitive against existing benchmark biomass LCOE studies. This study contributes a technology-driven framework designed for broader applicability in assessing the viability of similar wind energy projects, aimed at optimizing larger turbine deployment for maximized regional energy output while minimizing negative impacts, thereby offering a transferable approach beyond singular site-specific studies
DiffusionScore: A Framework for Assessing Institutional Research Impact Through Influence Diffusion
Get PDFAssessing an institution’s research output has traditionally relied mostly on the opinion of peers, but as the field of scientometrics progressed dramatically in recent years, the evolution of quantitative indicators gained popularity and became essential. The present approaches for evaluating an institution’s research output rely on citation data, that has been quantitatively analyzed and are predominantly data-centric models. It is observed that research productivity and impact are taken into account by many ranking systems, and the measurement of research impact is mostly dependent on citation-counting techniques and the volume of research produced. The recent ranking systems evaluate the reputation of academic institutions by employing network-based algorithms, like Page Rank which examine the citation network at the institution level. An Article’s outreach and causal impact are not completely taken into consideration by the aforementioned approaches which leads to incomplete quantification of metrics. In this study, we propose a framework that uses a data-agnostic influence diffusion model to measure the academic impact of the institutions in the citation network. The diffusion model is inspired by the phenomenon of heat diffusion. The suggested framework investigates the citation trajectory for each article published by the university in the research area, analyses its influence diffusion in citation networks, and provides methods, metrics, and processes that others could apply to similar problems or datasets. By leveraging transfer entropy-based techniques, our research goes beyond citation mapping to investigate the causal link between academic influence and the reputation of publication venues employed by universities
Population Dynamics of a Lion-Tailed Macaque (Macaca silenus) Population in a Rainforest Fragment in the Southern Western Ghats of India
No full textDemographic analysis is often used for the effective management of wildlife, especially for species facing human-caused disturbances to their habitat, such as habitat fragmentation. The objective of this long-term study was, therefore, to gain insights into the status of a lion-tailed macaque (Macaca silenus) population, inhabiting the Puthuthottam estate near Valparai in the Western Ghats of southwestern India, by documenting demographic factors, such as group numbers, group size and age/sex composition, as well as estimating growth, birth, and mortality rates. We documented the demography of five resident groups of this species, comprising 5% of the remaining wild lion-tailed macaque populations. In this paper, we present a demographic history of the Puthuthottam population through comparisons with studies conducted by various research groups, beginning in the 1970s, and report a five-fold increase in population size over a period of four decades. Using Generalized Linear Mixed Models, we analyze and discuss the effects of population demographic parameters on birth rates, including a moderately reduced growth- and birth rate, as compared to previous records for the population. The most frequent contributor to mortality, especially of the vulnerable juvenile age class, was found to be roadkill deaths, followed by other anthropogenic causes, including electrocution on exposed electric lines. We also report a shift in the social system, pervasive across this population, from unimale–multifemale to multimale–multifemale social groups. We strongly believe that the observed drastic alterations to the socioecological profile of the study population, as a result of habitat fragmentation and increased utilization of human habitats, have major implications for the long-term survivability of this macaque population. We hope the information presented in this paper will aid in the effective management of the remaining lion-tailed macaque populations across their distribution range, particularly as they become increasingly exposed to human-altered habitats