Evaluation of System Performance for Microalga Cultivation in Photobioreactor with IOTs (Internet of Things)

Photobioreactors are a closed system concept of microalgae cultivation which is mostly done to control the development of intensive cultivation. The use of the internet to control microalgae has been carried out so that cyber physic interaction occurs by using the Internet of Things (IOTs) where this concept is an evolution of the concept of internet use that aims to expand the benefits of internet connectivity that is connected continuously with the ability to control remotely (remote control), data sharing (data sharing), continuous monitoring (real time monitoring) and up to date (up to date). This research aims to design a microalgae cultivation system as a source of food and energy for the future with a photobioreactor integrated with IOTs, so that it can be monitored continuously, controlled and used as a model for the development of greater microalgae cultivation technology. Development of automation in the cultivation of microalgae needs to be done to improve productivity and maintain quality so that the cultivation of microalgae can lead to industrialization, so that the development of microalgae as raw material for various needs can be optimized. Cultivation in a closed system photobioreactor, will produce microalgae that are not contaminated by external contaminants, growth analysis can be done based on the parameters that affect it, including the cultivation room temperature, lighting level (luminance), and the color of water in the process of photosynthesis microalgae, and also control of water circulation by using air lift (aerator). All processes carried out in this cultivation are done semi-automatically, because there is still a process of human interaction in setting parameters and controls in the process of harvesting microalgae. In this study microalgae was evaluated by using 4 cultivation tubes using 2 treatments giving fertilizer with different doses, where 2 tubes had the same dose, while 2 other tubes with different dosages. One tube with the same dose is used as a control. Visualization of controlled parameters includes, temperature parameters, light intensity, water color changes. The observed parameters will be displayed in a graphical user interface (GUI) in real time using the internet.  The liitation of this studi is how the system for microalga cultivation in a fotobioreactor can monitored by sensor and visualization in a remote monitoring such as computer connected to internet and also any ather devices.  The target of this research is to obtined time series data that can be analized  and monitored

Aplikasi untuk Mencari Kelayakan Siswa Penerima Bantuan Pendidikan dengan Metode Simple Additive Weighting (Studi Kasus : SMK NU Ma'arif Kudus)

Setiap periode SMK NU Ma’arif 2 Kudus melaksanakan program penyaluran bantuan kepada peserta didiknya yang kurang mampu. Dalam memberikan bantuan tersebut perlu dilakukan seleksi bagi para calon penerima. Permasalahan yang dihadapi panitia adalah seleksi dilakukan dengan menunjukpara peserta didik secara langsung dan acak sehingga mengalami kesulitan dalam menentukan siapa yang sebenarnya berhak menerima bantuan. Untuk mengatasi masalah tersebut dan mendapatkan calon yang berhak menerima serta mencapai standar yang diinginkan, maka diperlukan Sistem Seleksi Calon Penerima Bantuan Siswa Miskin (BSM) menggunakan Metode Simple Additive Weighting (SAW) sebagai pendukung keputusan.Metode SAW mencari penjumlahan terbobot berdasar pada kriteria penilaian yang telah ditentukan. Kriteria yang digunakan dalam sistem ini yaitu;jumlah penghasilan orang tua, nilai rata-rata rapor, jumlah kerabat/ saudara. Dari hasil pengujian sistem ini diperoleh luaran berupa perankingan nilai akhir mulai dari yang terbesar hingga terkecil. Hasil analisa perbandingan sistem ini dengan sistem lama terkait tingkat keakuratannya adalah 18 dari 30 siswa (60%) pada sistem lama, sedangkan sistem baru adalah 30 dari 30 siswa (100%). Hasil kuesioner terkait uji kelayakan sistem Seleksi Calon Penerima BSM menggunakan Metode SAWini sangat mudah digunakan (Perceived Ease Of Use) dengan nilai akhir 86,3%, dan sangat bermanfaat (Perceived Of Usefulness) dengan nilai akhir 88,3%.Penerapan sistem ini berkontribusi bagi SMK NU Ma’arif 2 Kudus dalam melaksanakan program penyaluran dana BSM secara optimal, transparan, tepat sasaran, dan berkeadilan serta dapat dijadikan sebagai pendukung keputusan bagi pemangku kepentingan.AbstractEvery period SMK NU Ma’arif 2 Kudus carries out educational aid distribution programs to students who are less fortunate. In providing this assistance, it is necessary to select prospective recipients. The problem faced by the committee is that the selection is carried out by directly and randomly appointing students so that they have difficulty determining who is actually entitled to receive assistance. To overcome this problem and get candidates who are entitled to receive and achieve the desired standards, it is necessary to apply the eligibility selection of students receiving educational assistance using the Simple Additive Weighting (SAW) method as decision support. The SAW method seeks a weighted addition based on predetermined assessment criteria. The criteria used in this system are; the amount of parents' income, the average value of report cards, the number of relatives / relatives. From the test results of this system, the output is in the form of a ranking of the final values ranging from largest to smallest. The results of the comparative analysis of this system with the old system regarding the level of accuracy are 18 out of 30 students (60%) in the old system, while the new system is 30 out of 30 students (100%). The results of the questionnaire related to the feasibility test of the application for selection of students receiving educational assistance using the SAW Method are very easy to use (Perceived Ease Of Use) with a final value of 86.3%, and very useful (Perceived Of Usefulness) with a final value of 88.3%. The contribution to SMK NU Ma’arif 2 Kudus in this study was the making of an application to find out the eligibility of student beneficiaries using the SAW method. This can assist the committee in implementing the education aid fund distribution program in an optimal, transparent, on target and equitable manner and can be used as decision support for stakeholders

DEVELOPMENT OF A DECISION SUPPORT SYSTEM FOR COMPANIES IN THE ENERGY FROM BIOMASS AREA, APPLYING CIRCULAR ECONOMY PRINCIPLES WITH A LIFE CYCLE THINKING APPROACH

The biomass supply chain (BSC) for energy production has emerged as a promising alternative to traditional fossil fuels, playing a crucial role in mitigating climate change and promoting sustainable development. Biomass utilisation offers numerous environmental, economic, and social benefits, including reduced greenhouse gas (GHG) emissions, enhanced energy security, and job creation in rural areas, which are known as important aspects of sustainable development. Moreover, the use of waste, by-products, and residue in BSC is essential to improving the circular economy (CE) in agriculture, wood, and paper processing industries, as well as waste treatment and management. Therefore, to further harness the potential of biomass energy production in sustainability and transition to the CE context, it is significant for companies in the BSC to apply circular business models (CBM).While the role of biomass in the CE has been confirmed, the gap still exists in evaluating the application of CE to the BSC. Up to the authors’ knowledge, currently, there is no set of circularity and sustainability indicators as standard for the company in the BSC. The variety of CE approaches and indicators makes it difficult to convert linear business models into circular ones. In addition, the variety of biomass materials, differences in biomass processing technology and multiple end-products lead to transformation into a CE model in many alternatives with many stages and different technology processes. Furthermore, some indicators assessing aspects of sustainability and circularity of different alternatives are subject to conflict and trade-offs. A more sustainable solution might not necessarily be better in terms of circularity and similar trade-offs exist within the pillars of sustainability. Given the trade-offs between sustainability and circularity, decision support systems (DSS) based on life cycle thinking with a standard set of indicators are promising tools for evaluating and selecting the best alternative of sustainability and circularity BSC.For what is above, this PhD research project was focused on developing a decision support system for a biomass company in the energy sector based on CE and sustainability models with a life cycle thinking approach. With the CE and sustainability model, a set of circularity and sustainability indicators is developed, and it is considered a criteria set to assess the circularity and sustainability of biomass companies and BSC. The life cycle thinking approach is employed to provide a comprehensive assessment for BSC. It is also basic to collect data from BSC and give value to indicators for assessing and ranking alternatives. The trade-off existing in alternatives is solved by using Multiple-criteria decision-making methods. That is integrated into the methodology framework of the decision support system.The PhD research project is structured around two main objectives. First, from CE and sustainability models, a set of circularity and sustainability is development. Secondly, a DSS tool is created. The set of developed indicators considers various stages during the BSC, such as feedstock plantation, processing, transportation, energy conversion, and end-of-life management, being aligned with the United Nations Sustainable Development Goals (SDGs) and the EC’s guidelines on the transition to CE. Meanwhile, the creation of a DSS includes proposing a methodology framework for DSS, creating software in MATLAB GUI and Script as a new tool for DSS, and applying this tool to the rice straw supply chain as testing for the case study.Regarding the case study, a rice straw supply chain for energy production in the Pavia region of Italy is selected. The data for the case study was collected during the internship period at the ENI company, such as parameters of the plant and process. The current of the rice straw supply chain is assessed by the DSS tool, and a re-edited version of this tool was taken. The alternatives of CE applications in the case study were performed through an external internship at the IMDEA Energy Institute (Spain). The data on alternatives is gathered based on the results of the simulation of the chemical process by Aspen plus@ at the IMDEA Energy Institute for suitable parameters of the current supply chain. The sustainability and circularity indicators methodology framework and case study developed during this PhD research project have been published in international journals and conference proceedings. The results of the application and details of the decision support system are present in this thesis. The results of calculating indicators for all indicators show that global warming potential (GWP) is 1.21E+03 ton CO2eq/yr to 55.7E+03 ton CO2eq/yr. Meanwhile, rice straw's acidification potential (AP) in this study ranges from 9.66 tonnes of SO2 eq/yr to 563 tonnes of SO2 eq/yr. The internal rate of return (IRR) of the rice straw supply chain is from 5.92% to 11.3%. In addition, the net present value (NPV) of the case study ranges from 0.72 to 5.79 million euros. Furthermore, the rate of informal labour is from 71.9% to 82.10%, while the percentage of recycling rate out of all waste is from 96.61% to 99.2%, the circular material use is from 54.8% to 88.2%, and the proportion of material losses in primary material is from 14.61% to 15.5%. The ranking results indicate that the digestate pyrolysis option has the best sustainability and circularity points among the other options.This PhD project research shows that the application of a comprehensive approach encompassing Life Cycle Assessment (LCA), Life Cycle Costing (LCC), and Social Life Cycle Assessment (SLCA) to identify sustainability indicators brings about significant advantages to the biomass supply chain. Existing research seldom integrates all three methodologies simultaneously. This integrated approach enhances the understanding of sustainability implications across the biomass supply chain, paving the way for a more holistic assessment.Moreover, the utilization of the Life Cycle Thinking (LCT) tool and Material Flow Analysis (MFA) for circularity indicators introduces a novel dimension to the existing literature. The incorporation of these tools instills confidence in simulating both circularity and sustainability, a consideration often overlooked in previous studies. The resulting circularity and sustainability indicators offer a standardised set that serves as a step-by-step guide for achieving Sustainable Development Goals (SDGs) and transitioning to a circular economy, aligning with the European Commission's roadmap.The development of a Decision Support System (DSS) methodology framework marks another crucial contribution, particularly by integrating circularity and sustainability within a unified framework for biomass companies in the supply chain. Unlike existing frameworks, this approach employs the PROMETHEE II and Entropy methods, leveraging life cycle results to enhance reliability and streamline calculations. Overcoming the limitations of PROMETHEE, this framework incorporates a multiple-criteria decision-making approach to address trade-offs in sustainability and circularity alternatives. This not only improves the robustness of the framework but also extends its applicability to general companies beyond the biomass sector.Furthermore, the accompanying software in this study presents a more practical and potent DSS tool for ranking alternatives. Its flexibility, allowing the use of the DSS tool for calculating sustainability and circularity indicators for individual alternatives, provides users with a versatile platform. The ability to choose indicator groups and methods for weighting indicators enhances the adaptability of the framework, making it applicable in various scenarios for policymakers and researchers committed to advancing circular economy and sustainability initiatives. In summary, based on methods for application, methodology framework and useful software, the DSS tool developed in this thesis can be used to support companies in the biomass supply chain, managers, practitioners, policy-makers, and researchers in assessing and selecting alternatives for application of CBMs to transfer into CE

DEVELOPMENT OF A DECISION SUPPORT SYSTEM FOR COMPANIES IN THE ENERGY FROM BIOMASS AREA, APPLYING CIRCULAR ECONOMY PRINCIPLES WITH A LIFE CYCLE THINKING APPROACH

The biomass supply chain (BSC) for energy production has emerged as a promising alternative to traditional fossil fuels, playing a crucial role in mitigating climate change and promoting sustainable development. Biomass utilisation offers numerous environmental, economic, and social benefits, including reduced greenhouse gas (GHG) emissions, enhanced energy security, and job creation in rural areas, which are known as important aspects of sustainable development. Moreover, the use of waste, by-products, and residue in BSC is essential to improving the circular economy (CE) in agriculture, wood, and paper processing industries, as well as waste treatment and management. Therefore, to further harness the potential of biomass energy production in sustainability and transition to the CE context, it is significant for companies in the BSC to apply circular business models (CBM).While the role of biomass in the CE has been confirmed, the gap still exists in evaluating the application of CE to the BSC. Up to the authors’ knowledge, currently, there is no set of circularity and sustainability indicators as standard for the company in the BSC. The variety of CE approaches and indicators makes it difficult to convert linear business models into circular ones. In addition, the variety of biomass materials, differences in biomass processing technology and multiple end-products lead to transformation into a CE model in many alternatives with many stages and different technology processes. Furthermore, some indicators assessing aspects of sustainability and circularity of different alternatives are subject to conflict and trade-offs. A more sustainable solution might not necessarily be better in terms of circularity and similar trade-offs exist within the pillars of sustainability. Given the trade-offs between sustainability and circularity, decision support systems (DSS) based on life cycle thinking with a standard set of indicators are promising tools for evaluating and selecting the best alternative of sustainability and circularity BSC.For what is above, this PhD research project was focused on developing a decision support system for a biomass company in the energy sector based on CE and sustainability models with a life cycle thinking approach. With the CE and sustainability model, a set of circularity and sustainability indicators is developed, and it is considered a criteria set to assess the circularity and sustainability of biomass companies and BSC. The life cycle thinking approach is employed to provide a comprehensive assessment for BSC. It is also basic to collect data from BSC and give value to indicators for assessing and ranking alternatives. The trade-off existing in alternatives is solved by using Multiple-criteria decision-making methods. That is integrated into the methodology framework of the decision support system.The PhD research project is structured around two main objectives. First, from CE and sustainability models, a set of circularity and sustainability is development. Secondly, a DSS tool is created. The set of developed indicators considers various stages during the BSC, such as feedstock plantation, processing, transportation, energy conversion, and end-of-life management, being aligned with the United Nations Sustainable Development Goals (SDGs) and the EC’s guidelines on the transition to CE. Meanwhile, the creation of a DSS includes proposing a methodology framework for DSS, creating software in MATLAB GUI and Script as a new tool for DSS, and applying this tool to the rice straw supply chain as testing for the case study.Regarding the case study, a rice straw supply chain for energy production in the Pavia region of Italy is selected. The data for the case study was collected during the internship period at the ENI company, such as parameters of the plant and process. The current of the rice straw supply chain is assessed by the DSS tool, and a re-edited version of this tool was taken. The alternatives of CE applications in the case study were performed through an external internship at the IMDEA Energy Institute (Spain). The data on alternatives is gathered based on the results of the simulation of the chemical process by Aspen plus@ at the IMDEA Energy Institute for suitable parameters of the current supply chain. The sustainability and circularity indicators methodology framework and case study developed during this PhD research project have been published in international journals and conference proceedings. The results of the application and details of the decision support system are present in this thesis. The results of calculating indicators for all indicators show that global warming potential (GWP) is 1.21E+03 ton CO2eq/yr to 55.7E+03 ton CO2eq/yr. Meanwhile, rice straw's acidification potential (AP) in this study ranges from 9.66 tonnes of SO2 eq/yr to 563 tonnes of SO2 eq/yr. The internal rate of return (IRR) of the rice straw supply chain is from 5.92% to 11.3%. In addition, the net present value (NPV) of the case study ranges from 0.72 to 5.79 million euros. Furthermore, the rate of informal labour is from 71.9% to 82.10%, while the percentage of recycling rate out of all waste is from 96.61% to 99.2%, the circular material use is from 54.8% to 88.2%, and the proportion of material losses in primary material is from 14.61% to 15.5%. The ranking results indicate that the digestate pyrolysis option has the best sustainability and circularity points among the other options.This PhD project research shows that the application of a comprehensive approach encompassing Life Cycle Assessment (LCA), Life Cycle Costing (LCC), and Social Life Cycle Assessment (SLCA) to identify sustainability indicators brings about significant advantages to the biomass supply chain. Existing research seldom integrates all three methodologies simultaneously. This integrated approach enhances the understanding of sustainability implications across the biomass supply chain, paving the way for a more holistic assessment.Moreover, the utilization of the Life Cycle Thinking (LCT) tool and Material Flow Analysis (MFA) for circularity indicators introduces a novel dimension to the existing literature. The incorporation of these tools instills confidence in simulating both circularity and sustainability, a consideration often overlooked in previous studies. The resulting circularity and sustainability indicators offer a standardised set that serves as a step-by-step guide for achieving Sustainable Development Goals (SDGs) and transitioning to a circular economy, aligning with the European Commission's roadmap.The development of a Decision Support System (DSS) methodology framework marks another crucial contribution, particularly by integrating circularity and sustainability within a unified framework for biomass companies in the supply chain. Unlike existing frameworks, this approach employs the PROMETHEE II and Entropy methods, leveraging life cycle results to enhance reliability and streamline calculations. Overcoming the limitations of PROMETHEE, this framework incorporates a multiple-criteria decision-making approach to address trade-offs in sustainability and circularity alternatives. This not only improves the robustness of the framework but also extends its applicability to general companies beyond the biomass sector.Furthermore, the accompanying software in this study presents a more practical and potent DSS tool for ranking alternatives. Its flexibility, allowing the use of the DSS tool for calculating sustainability and circularity indicators for individual alternatives, provides users with a versatile platform. The ability to choose indicator groups and methods for weighting indicators enhances the adaptability of the framework, making it applicable in various scenarios for policymakers and researchers committed to advancing circular economy and sustainability initiatives. In summary, based on methods for application, methodology framework and useful software, the DSS tool developed in this thesis can be used to support companies in the biomass supply chain, managers, practitioners, policy-makers, and researchers in assessing and selecting alternatives for application of CBMs to transfer into CE

Business intelligence in the electrical power industry

Nowadays, the electrical power industry has gained tremendous interest from both entrepreneurs and researchers due to its essential roles in everyday life. However, the current sources for generating electricity are astonishing decreasing, which leads to more challenges for the power industry. Based on the viewpoint of sustainable development, the solution should maintain three layers of economically, ecologically, and society; simultaneously, support business decision-making, increases organizational productivity and operational energy efficiency. In the smart and innovative technology context, business intelligence solution is considered as a potential option in the data-rich environment, which is still witnessed disjointed theoretical progress. Therefore, this study aimed to conduct a systematic literature review and build a body of knowledge related to business intelligence in the electrical power sector. The author also built an integrative framework displaying linkages between antecedents and outcomes of business intelligence in the electrical power industry. Finally, the paper depicted the underexplored areas of the literature and shed light on the research objectives in terms of theoretical and practical implications

Biorefarmeries: Milking ethanol from algae for the mobility of tomorrow

The idea of this project is to fully exploit microalgae to the best of its potential, possibly proposing a sort of fourth generation fuel based on a continuous milking of macro- and microorganisms (as cows in a milk farm), which produce fuel by photosynthetic reactions. This project proposes a new transportation concept supported by a new socio-economic approach, in which biofuel production is based on biorefarmeries delivering fourth generation fuels which also have decarbonization capabilities, potential negative CO2 emissions plus positive impacts on mobility, the automotive Industry, health and environment and the econom

Determination of Time Dependent Stress Distribution on Potato Tubers at Mechanical Collision

This study focuses on determining internal stress progression and the realistic representation of time dependent deformation behaviour of potato tubers under a sample mechanical collision case. A reverse engineering approach, physical material tests and finite element method (FEM)-based explicit dynamics simulations were utilised to investigate the collision based deformation characteristics of the potato tubers. Useful numerical data and deformation visuals were obtained from the simulation results. The numerical results are presented in a format that can be used for the determination of bruise susceptibility magnitude on solid-like agricultural products. The modulus of elasticity was calculated from experimental data as 3.12 [MPa] and simulation results showed that the maximum equivalent stress was 1.40 [MPa] and 3.13 [MPa] on the impacting and impacted tubers respectively. These stress values indicate that bruising is likely on the tubers. This study contributes to further research on the usage of numerical-methods-based nonlinear explicit dynamics simulation techniques in complicated deformation and bruising investigations and industrial applications related to solid-like agricultural products

Aquaculture Perspective of Multi-Use Sites in the Open Ocean: The Untapped Potential for Marine Resources in the Anthropocene

This volume addresses the potential for combining large-scale marine aquaculture of macroalgae, molluscs, crustaceans, and finfish, with offshore structures, primarily those associated with energy production, such as wind turbines and oil-drilling platforms. The volume offers a comprehensive overview and includes chapters on policy, science, engineering, and economic aspects to make this concept a reality. The compilation of chapters authored by internationally recognized researchers across the globe addresses the theoretical and practical aspects of multi-use, and presents case studies of research, development, and demonstration-scale installations in the US and EU

Biosystems and Food Engineering Research Review 28

The Twenty Eighth Annual Research Review describes the ongoing research programme in the School of Biosystems and Food Engineering at University College Dublin over the academic year 2022/23, from the collective research body within the school comprising our academic staff, technical staff, research staff and our early-stage researchers. The research programme covers two main focal areas: Food and Process Engineering as well as Energy and the Environment. Each of these areas is divided into sub-themes as indicated in the Table of Contents, which also includes the name of the research scholar (in bold); the title of the research and the nature of the research programme. The review also highlights the award winners for presentational excellence at the 28th Annual Biosystems and Food Engineering Research Seminar, which was held online in virtual format on Thursday 16th March 2023. The awardees for 2023 are listed in the Appendix A

Monitoring of biological processes in microalgae production using Fluorescence Spectroscopy

Microalgae industrial production is nowadays viewed as a solution for environmental conscious and sustainable alternative production of fuel, feed, food and chemicals. Throughout the years, several technological advances have been studied and implemented that increased the competitiveness of microalgae production. However, online monitoring and a real-time process control of a microalgae production factory still requires development to support economic sustainability. In this work, fluorescence spectroscopy coupled with chemometric modelling is studied as an online monitoring tool to be used in microalgae production. Fluorescence spectroscopy is a noninvasive and highly sensitive technique, able to detect instantaneously several natural fluorophores but also the interferences between them and the environmental media. Chemometric methods are often used to deconvolute the information within the fluorescence matrices, known as excitation-emission matrices (EMMs), and to determine the relationship between them and the parameters to be monitored. To prove the potential of fluorescence spectroscopy coupled with chemometric modelling techniques, different strategies are studied. Firstly, the EEMs of the spectra are used as raw data, without pre-treatment for removal of water scatter and inner-filter effects. Principal Component Analysis (PCA) is used to extract the meaningful information from the spectra, resulting in Principal Components (PCs). Through Projection to Latent Structures (PLS) modelling, prediction models are developed using the PCs from the fluorescence EEMs as inputs, to find linear correlations with the parameters to be monitored, the outputs. A second strategy is studied with pre-treated EEMs. With these EEMs, two input strategies in the PLS models are tested: using directly the EEMs in PLS or compressing the EEMs into PCs though PCA prior to PLS. Two marine microalgae are used in these studies, Dunaliella salina and Nannochloropsis oceanica. Five parameters are monitored – cell concentration, cell viability, pigments concentration, fatty acids composition and nitrogen concentration – in four different processes – cultivation, product formation (carotenoids and lipids), harvesting by membrane filtration and permeate recover. The combination of fluorescence spectroscopy, with its high sensitivity and resolution, coupled with chemometric analysis for data pre-treatment and development of prediction models, enhances th