Resultaten voor 'bose'

1. Sujoy Bose
2. Chandan Das

Introduction to Ceramics

This textbook discusses ceramic raw materials, properties of ceramics, fabrication techniques of ceramics and testing of ceramics.

Recent Advances in Additive Manufacturing, Volume 1

This book presents the select proceedings of the 1st International Conference on Additive Manufacturing (ICAM 2024). It covers the applications of additive and advanced manufacturing in the various areas such as materials, automotive, aerospace, electronics and medicine. Various topics covered in this book are additive manufacturing modeling and simulation, need for design in additive manufacturing, environment and sustainability aspects of additive manufacturing, standardisation and qualification of additive manufacturing parts, computational and analytical methods in additive manufacturing and many more. This volume will prove a valuable resource for those in academia and industry working in the area of additive manufacturing.

1. Sumit , Roy
2. Ajoy Kumar , Das
3. Probir Kumar , Bose

Optimización del rendimiento y las emisiones de un motor CRDI utilizando PSO

Teniendo en cuenta las observaciones sobre las características inherentes de compensación entre PM-NOx-BSFC proporcionadas por CRDI con estrategias de GNC y EGR durante la experimentación, se establece un posible contexto para examinar un enfoque de optimización pionero en su género con el fin de potenciar la compensación entre GNC y EGR mediante su aplicación simultánea en un motor diésel existente con sistema de inyección de combustible common rail. Se eligieron FIP, EGR, CES y la carga del motor como variables de control para el estudio de optimización. Se constituyó una función de mérito adaptativa (AMF) como función objetivo a optimizar y se utilizó una red neuronal artificial (ANN) para correlacionar la función objetivo con las variables de control elegidas, mientras que se eligió Latin-Hypercube como programador DoE para proporcionar la muestra de población inicial para la secuencia de iteración de optimización. Se eligió PSO como algoritmo de optimización debido a su simplicidad y eficiencia inherentes para producir una convergencia asegurada de la función objetivo con un coste computacional significativamente menor. El diseño inherente de la función objetivo AMF garantizó que todos esos valores óptimos de compensación cumplieran simultáneamente las expectativas de los mandatos PM y NHC de la EPA Tier 4.

3D Printing of Biomaterials

Susmita Bose is a Professor in the School of Mechanical and Materials Engineering, an affiliate professor in the Department of Chemistry at Washington State University (WSU). In 2004, Dr. Bose received the prestigious Presidential Early Career Award for Scientist and Engineers (PECASE, the highest honor given to a young scientist by the US President at the White House) award from the National Science Foundation. Dr. Bose was named as a “Kavli fellow by the National Academy of Sciences. In 2009, she received the prestigious Schwartzwalder-Professional Achievement in Ceramic Engineering (PACE) Award, and in 2014 Richard M. Fulrath Award, which is an international award given to one academician in the US annually (below age 45), from the American Ceramic Society. Dr. Bose is editorial board member for several international journals, including Acta Biomaterialia, Journal of the American Ceramic Society, Journal of Materials Chemistry B, International Journal of Nanomedicine and Additive Manufacturing. Dr. Bose has published over 200 technical papers with ~ 5000 citations, “h index 40. Dr. Bose is a fellow of the American Institute for Medical and Biological Engineering (AIMBE) and the American Ceramic Society (ACerS). Prof. Bandyopadhyay is Herman and Brita Lindholm Endowed Chair Professor at the School of Mechanical and Materials Engineering, Washington State University (WSU), also a Fellow of the National Academy of Inventors (NAI), American Ceramic Society (ACerS), American Society for Materials (ASM International), American Institute for Medical and Biological Engineering (AIMBE) and American Association for the Advancement of Science (AAAS). He has published over 250 technical papers including over 170 journal papers. He holds 11 US patents and several patent applications are currently pending at the United States Patent and Trademark Office. He has edited 8 books.His research expertise lies with additive manufacturing of metallic and ceramic materials and their composites towards structural, bio- and piezoelectric materials.

1. Goutam Kumar , Bose
2. Indrajeet , Sen

Bibliometric and Network Analysis of Fused Deposition Modelling (FDM)

This book provides a data-driven, sweeping overview of Fused Deposition Modelling (FDM) research using bibliometric methods and network analysis. It based its mappings of publication patterns, top authors, institutions, countries, and leading journals; measured influence in terms of citation, co-authorship and co-citation metrics; and uncovered thematic clusters through keyword co-occurrence and topic networks. Identified key topics are material development (composites, polymers, biopolymers), process-parameter optimisation, mechanical properties and anisotropy, post-processing, applications (tooling, biomedical, aerospace), and sustainability. Network metrics and visualisations (generated using tools such as VOSviewer/Gephi) shed light on collaboration trends, upcoming hotspots, and knowledge gaps. The book finishes with strategic advice for future FDM research-standardisation, multimaterial printing, process-property modelling, and lifecycle assessment-making it a useful guidebook for researchers, policy makers, and industry players who are looking for a disciplined overview of the development of the field and its future directions.

1. Sumit , Roy
2. Ajoy Kumar , Das
3. Probir Kumar , Bose

Anwendung künstlicher Intelligenz auf einen CRDI-Dieselmotor

Die vorliegende Studie untersucht das Potenzial künstlicher neuronaler Netze zur Vorhersage der Leistung und der Abgasemissionen eines bestehenden Einzylinder-Viertakt-CRDI-Motors unter verschiedenen CNG- und EGR-Strategien. Auf der Grundlage der experimentellen Daten wird ein ANN-Modell entwickelt, um die Leistungs- und Emissionsparameter des Versuchsmotors vorherzusagen. Die Studie wurde durchgeführt, wobei 70 % der gesamten experimentellen Daten für das Training des neuronalen Netzwerks ausgewählt wurden, 15 % für die Kreuzvalidierung des Netzwerks und die restlichen 15 % der Daten für die Prüfung der Leistung des trainierten Netzwerks verwendet wurden. Die entwickelten ANN-Modelle waren in der Lage, die Leistung und die Emissionen des Versuchsmotors mit ausgezeichneter Übereinstimmung vorherzusagen.