Sustainable Energy Imaginaries: Utilizing Mie Optics to Reengineer Photobioreactors and Reimagine the Socio-spatial Conditions of Autonomous Energy Production

In order to build a more sustainable future, society must transition toward carbon negative energy production and infrastructure. Algae photobioreactors have proven to be an efficient producer of lipid rich oil which can be synthesized into carbon neutral biodiesel. However, the neutrality of such a technology rests in its ability to yield adequate algal biomass through photosynthesis. In order to reach maximum quantum efficiency of algal cells, solar flux must be transformed so that photon absorption can occur without oversaturating the constituent matter. This project looks at the scattering effects of iridocyte-like structures and their potential to create cost effective solar transformers by utilizing the principles of geometrical optics, spherical harmonics, and Mie theory. Additionally, the socioeconomic implications of energy autonomy are considered across communal scales, along with a reimagining of the socio-spatial arrangements behind decentralized energy production. In this way, the project serves as a model of multidisciplinary collaboration and the importance of use value in technological analysis–both of which will prove vital as we reorganize grid infrastructures to accommodate renewable energy

Cuban energy system development – Technological challenges and possibilities

This eBook is a unique scientific journey to the changing frontiers of energy transition in Cuba focusing on technological challenges of the Cuban energy transition. The focus of this milestone publication is on technological aspects of energy transition in Cuba. Green energy transition with renewable energy sources requires the ability to identify opportunities across industries and services and apply the right technologies and tools to achieve more sustainable energy production systems. The eBook is covering a large diversity of Caribbean country´s experiences of new green technological solutions and applications. It includes various technology assessments of energy systems and technological foresight analyses with a special focus on Cuba

DECISION SUPPORT FRAMEWORK FOR TRANSFORMING URBAN BUILDINGS AT MULTIPLE SCALES

Due to the increasing population, cities are requiring more energy. Among urban elements, buildings account for about 40% of energy demands and 30% of carbon dioxide emissions globally. To address the increase of energy demands and environmental responsibility, existing buildings should be transformed into highly energy efficient forms. This research explores how to support decisions that affect performance-driven smart and resilient urban systems focusing on building renovations. The research scope covers the redevelopment of existing built forms at multiple scales. Since urban objects influence urban patterns at other scales, both individual and collective performances of buildings at larger scales should be evaluated to support proper redevelopment decisions. In addition, the transformation of existing buildings will encounter different problems and challenges at different scales in urban areas. On an individual building level, the selection of different envelope options can project the future architectural environment of buildings. On a block level, the performance will be changed along with combinations of building typologies such as land use, height, floor area, etc., and therefore changes to building typologies should be managed collectively to improve the performance. When PV are applied in buildings and hourly electricity demands are recognized, the dynamic energy flows on a community level will become complex to manage. In this respect, this research is devised to identify and address redevelopment problems at different scales: individual buildings, block, and community. On the individual building level, this research studies how to support decision-making when optimizing the selection of building envelopes by using a Genetic Algorithm (GA). Based on the findings from optimizing at each scale, an interdependence of building parameters and multiple performance is observed. Therefore, decision frameworks across multiple scales are extrapolated to support community-driven and building-driven decisions. On the block level, this research explores how existing building typologies influence multiple performance indicators in a collective manner to support reconfiguring decisions using a Bayesian Multilevel Modeling. On the community level, this study addresses how the community can optimize block boundaries for resiliently managing the energy demand and supply of groups of buildings by using K-nearest neighbors (KNN) and community clustering algorithms. This research will contribute to making appropriate decisions for investment, regulations, or guidelines when renovating physical building assets at different scales in urban areas. The research findings will consolidate theoretical understandings about the relationships between building design and construction parameters considering multiple performance indicators at multiple scales in urban areas. Since many cities are at the tipping point trying to become more resilient, increasingly focusing on sustainability, economic feasibility, and human well-being, a better understanding of the impact of built forms at multiple scales will support urban development decisions for the future smart and connected communities.Ph.D

Advances in raw material industries for sustainable development goals

"""Advances in Raw Material Industries for Sustainable Development Goals"" presents the results of joint scientific research conducted in the context of the Russian-German Raw Materials Forum. Today Russia and Germany are exploring various forms of cooperation in the field of mining, geology, mineralogy, mechanical engineering and energy. Russia and Germany are equally interested in expanding cooperation and modernizing the economy in terms of sustainable development. The main theme of this article collection is connected with existing business ventures and ideas from both Russia and Germany. In this book the authors regard complex processes in mining industry from various points of view, including: - modern technologies in prospecting, exploration and development of mineral resources - progressive methods of natural and industrial mineral raw materials processing - energy technologies and digital technologies for sustainable development - cutting-edge technologies and innovations in the oil and gas industry. Working with young researchers, supporting their individual professional development and creating conditions for their mobility and scientific cooperation are essential parts of Russian-German Raw Materials Forum founded in Dresden 13 years ago. This collection represents both willingness of young researchers to be involved in large-scale international projects like Russian-German Raw Material Forum and the results of their long and thorough work in the promising areas of cooperation between Russia and Germany.

Experimental investigation and modelling of the heating value and elemental composition of biomass through artificial intelligence

Abstract: Knowledge advancement in artificial intelligence and blockchain technologies provides new potential predictive reliability for biomass energy value chain. However, for the prediction approach against experimental methodology, the prediction accuracy is expected to be high in order to develop a high fidelity and robust software which can serve as a tool in the decision making process. The global standards related to classification methods and energetic properties of biomass are still evolving given different observation and results which have been reported in the literature. Apart from these, there is a need for a holistic understanding of the effect of particle sizes and geospatial factors on the physicochemical properties of biomass to increase the uptake of bioenergy. Therefore, this research carried out an experimental investigation of some selected bioresources and also develops high-fidelity models built on artificial intelligence capability to accurately classify the biomass feedstocks, predict the main elemental composition (Carbon, Hydrogen, and Oxygen) on dry basis and the Heating value in (MJ/kg) of biomass...Ph.D. (Mechanical Engineering Science

Energy Development for Sustainability

Recently, energy development has received significant attention through the promising results of technology development, experimentation, computational modeling, and validation. However, it remains a persistent challenge to produce the needed energy while significantly reducing the environmental effects, such as the emission of greenhouse gases, which lead to climate change. Moreover, technological and economic limitations may also hinder energy development for sustainability. This book entitled Energy Development for Sustainability covers technologies, products, equipment, and devices as well as energy services based on software and data protected by patents and/or trademarks. This book will serve as a collection of the latest scientific and technological approaches to various energy development initiatives for sustainability encompassing novel sonocatalytic application and integrated algal and sludge-based wastewater treatment system, energy storage, sustainable building, gas absorption, organosolv pretreatment, energy usage and CO2 emission in transportation, coal regulation for energy, solar photovoltaic system, torrefaction for fuel production, energy management system, clean energy incubator, biofuels from microalgae, and the influence of COVID-19 on climate change. Overall, this book addresses researchers, advanced students, technical consultants, as well as decision-makers in industries and politics. This book contains comprehensive overview and in-depth technical research papers addressing recent progress in the area of energy development for sustainability. We hope the readers will enjoy this book

XLIII Jornadas de Automática: libro de actas: 7, 8 y 9 de septiembre de 2022, Logroño (La Rioja)

[Resumen] Las Jornadas de Automática (JA) son el evento más importante del Comité Español de Automática (CEA), entidad científico-técnica con más de cincuenta años de vida y destinada a la difusión e implantación de la Automática en la sociedad. Este año se celebra la cuadragésima tercera edición de las JA, que constituyen el punto de encuentro de la comunidad de Automática de nuestro país. La presente edición permitirá dar visibilidad a los nuevos retos y resultados del ámbito, y su uso en un gran número de aplicaciones, entre otras, las energías renovables, la bioingeniería o la robótica asistencial. Además de la componente científica, que se ve reflejada en este libro de actas, las JA son un punto de encuentro de las diferentes generaciones de profesores, investigadores y profesionales, incluyendo la componente social que es de vital importancia. Esta edición 2022 de las JA se celebra en Logroño, capital de La Rioja, región mundialmente conocida por la calidad de sus vinos de Denominación de Origen y que ha asumido el desafío de poder ganar competitividad a través de la transformación verde y digital. Pero también por ser la cuna del castellano e impulsar el Valle de la Lengua con la ayuda de las nuevas tecnologías, entre ellas la Automática Inteligente. Los organizadores de estas JA, pertenecientes al Área de Ingeniería de Sistemas y Automática del Departamento de Ingeniería Eléctrica de la Universidad de La Rioja (UR), constituyen un pilar fundamental en el apoyo a la región para el estudio, implementación y difusión de estos retos. Esta edición, la primera en formato íntegramente presencial después de la pandemia de la covid-19, cuenta con más de 200 asistentes y se celebra a caballo entre el Edificio Politécnico de la Escuela Técnica Superior de Ingeniería Industrial y el Monasterio de Yuso situado en San Millán de la Cogolla, dos marcos excepcionales para la realización de las JA. Como parte del programa científico, dos sesiones plenarias harán hincapié, respectivamente, sobre soluciones de control para afrontar los nuevos retos energéticos, y sobre la calidad de los datos para una inteligencia artificial (IA) imparcial y confiable. También, dos mesas redondas debatirán aplicaciones de la IA y la implantación de la tecnología digital en la actividad profesional. Adicionalmente, destacaremos dos clases magistrales alineadas con tecnología de última generación que serán impartidas por profesionales de la empresa. Las JA también van a albergar dos competiciones: CEABOT, con robots humanoides, y el Concurso de Ingeniería de Control, enfocado a UAVs. A todas estas actividades hay que añadir las reuniones de los grupos temáticos de CEA, las exhibiciones de pósteres con las comunicaciones presentadas a las JA y los expositores de las empresas. Por último, durante el evento se va a proceder a la entrega del “Premio Nacional de Automática” (edición 2022) y del “Premio CEA al Talento Femenino en Automática”, patrocinado por el Gobierno de La Rioja (en su primera edición), además de diversos galardones enmarcados dentro de las actividades de los grupos temáticos de CEA. Las actas de las XLIII Jornadas de Automática están formadas por un total de 143 comunicaciones, organizadas en torno a los nueve Grupos Temáticos y a las dos Líneas Estratégicas de CEA. Los trabajos seleccionados han sido sometidos a un proceso de revisión por pares

Intelligent Energy-Savings and Process Improvement Strategies in Energy-Intensive Industries

S tím, jak se neustále vyvíjejí nové technologie pro energeticky náročná průmyslová odvětví, stávající zařízení postupně zaostávají v efektivitě a produktivitě. Tvrdá konkurence na trhu a legislativa v oblasti životního prostředí nutí tato tradiční zařízení k ukončení provozu a k odstavení. Zlepšování procesu a projekty modernizace jsou zásadní v udržování provozních výkonů těchto zařízení. Současné přístupy pro zlepšování procesů jsou hlavně: integrace procesů, optimalizace procesů a intenzifikace procesů. Obecně se v těchto oblastech využívá matematické optimalizace, zkušeností řešitele a provozní heuristiky. Tyto přístupy slouží jako základ pro zlepšování procesů. Avšak, jejich výkon lze dále zlepšit pomocí moderní výpočtové inteligence. Účelem této práce je tudíž aplikace pokročilých technik umělé inteligence a strojového učení za účelem zlepšování procesů v energeticky náročných průmyslových procesech. V této práci je využit přístup, který řeší tento problém simulací průmyslových systémů a přispívá následujícím: (i)Aplikace techniky strojového učení, která zahrnuje jednorázové učení a neuro-evoluci pro modelování a optimalizaci jednotlivých jednotek na základě dat. (ii) Aplikace redukce dimenze (např. Analýza hlavních komponent, autoendkodér) pro vícekriteriální optimalizaci procesu s více jednotkami. (iii) Návrh nového nástroje pro analýzu problematických částí systému za účelem jejich odstranění (bottleneck tree analysis – BOTA). Bylo také navrženo rozšíření nástroje, které umožňuje řešit vícerozměrné problémy pomocí přístupu založeného na datech. (iv) Prokázání účinnosti simulací Monte-Carlo, neuronové sítě a rozhodovacích stromů pro rozhodování při integraci nové technologie procesu do stávajících procesů. (v) Porovnání techniky HTM (Hierarchical Temporal Memory) a duální optimalizace s několika prediktivními nástroji pro podporu managementu provozu v reálném čase. (vi) Implementace umělé neuronové sítě v rámci rozhraní pro konvenční procesní graf (P-graf). (vii) Zdůraznění budoucnosti umělé inteligence a procesního inženýrství v biosystémech prostřednictvím komerčně založeného paradigmatu multi-omics.Zlepšení průmyslových procesů, Model založený na datech, Optimalizace procesu, Strojové učení, Průmyslové systémy, Energeticky náročná průmyslová odvětví, Umělá inteligence.