scholarly journals PREDIS: innovative ways for predisposal treatment and monitoring of low and medium radioactive waste

2021 ◽  
Vol 1 ◽  
pp. 9-10
Author(s):  
Ernst Niederleithinger ◽  
Vera Lay ◽  
Christian Köpp ◽  
Erika Holt ◽  
Maria Oksa
Keyword(s):  
Radioactive Waste ◽  
Organic Waste ◽  
Pressure Sensors ◽  
Current Data ◽  
Added Value ◽  
Machine Learning Techniques ◽  
Waste Streams ◽  
Integrity Assessment ◽  
Technical Work ◽  
Global Vision

Abstract. The EURATOM PREDIS project (http://www.predis-h2020.eu, last access: 25 October 2021) targets the development and implementation of activities for predisposal treatment of radioactive waste streams other than nuclear fuel and high-level radioactive waste. It started on 1 September 2020 with a 4 year duration. The consortium includes 47 partners from 17 member states. The overall budget of the project is EUR 23.7 million, with EC contribution of EUR 14 million. The PREDIS project develops and increases the technological readiness level (TRL) of treatment and conditioning methodologies for wastes for which no adequate or industrially mature solutions are currently available, including metallic materials, liquid organic waste and solid organic waste. The PREDIS project also develops innovations in cemented waste handling and predisposal storage by testing and evaluating. The technical work packages align with priorities formulated within the Roadmap Theme 2 of EURAD (https://www.ejp-eurad.eu/sites/default/files/2021-09/2_Predisposal_Theme_Overview.pdf, last access: 15 October 2021), Nugenia Global Vision (https://snetp.eu/wp-content/uploads/2020/10/Global-vision-document-ves-1-april-2015-aa.pdf, last access: 15 October 2021) and with those identified by the project's industrial end users group (EUG). The PREDIS will produce tools guiding decision making on the added value of the developed technologies and their impact on the design, safety and economics of waste management and disposal. Four technical work packages are focusing on specific waste types: metallic, liquid organic, solid organic, and cemented wastes. For the first three, the main aim lies in processing, stabilizing, and packaging the different waste streams, e.g. by using novel geopolymers, to deliver items which are in line with national and international waste acceptance criteria. In contrast, the fourth technical work package has a different focus. To provide better ways for a safe and effective monitoring of cemented waste packages including prediction tools to assess the future integrity development during predisposal activities, several digital tools are evaluated and improved. Safety enhancement (e.g. less exposure of testing personnel) and cost-effectiveness are part of the intended impact. The work includes but is not limited to inspection methods, such as muon imaging, wireless sensors integrated into waste packages as well as external package and facility monitoring, such as remote fiber optic sensors. The sensors applied will go beyond radiation monitoring and include proxy parameters important for long-term integrity assessment (e.g. internal pressure). Sensors will also be made cost-effective to allow the installation of many more sensors compared to current practice. The measured data will be used in digital twins of the waste packages for specific simulations (geochemical, integrity) providing a prediction of future behavior. Machine learning techniques trained by the characterization of older waste packages will help to connect the models to the current data. All data (measured and simulated) will be collected in a joint database and connected to a decision framework to be used at actual facilities. The presentation includes detailed information about the various tools under consideration in the monitoring of cemented waste packages, their connection and first results of the research.

scholarly journals Valorization of Kiwi by-Products for the Recovery of Bioactive Compounds: Circular Economy Model

Proceedings ◽  
2020 ◽  
Vol 70 (1) ◽  
pp. 9
Author(s):  
Franklin Chamorro ◽  
María Carpena ◽  
Bernabé Nuñez-Estevez ◽  
Miguel A. Prieto ◽  
Jesus Simal-Gandara
Keyword(s):  
Bioactive Compounds ◽  
Circular Economy ◽  
Agricultural Production ◽  
Organic Waste ◽  
Antimicrobial Activities ◽  
Added Value ◽  
Economic Returns ◽  
Industrial Processing ◽  
Pharmaceutical Industries ◽  
By Products

Currently, agricultural production generates large amounts of organic waste, both from the maintenance of farms and crops, and from the industrialization of the product. Generally, these wastes are accumulated in landfills or burned, sometimes causing environmental problems. However, many scientific studies suggest that these residues are rich in bioactive compounds, so these matrices could be revalued for their use in food, cosmetic, or pharmaceutical industries. In this way, the circular and sustainable economy is favored, while obtaining products with high added value. In this case, this approach is applied to the residues generated from kiwi production, since numerous studies have shown the high content of kiwi in bioactive compounds of interest, such as phenolic compounds, vitamins, and carotenoids. These compounds have been reported for their antioxidant, anti-inflammatory, and antimicrobial activities, among other beneficial properties for health such as its use as prebiotic. Therefore, this article reviews the potential of residues derived from industrial processing and agricultural maintenance of kiwi as promising matrices for the development of new nutraceutical, cosmetic, or pharmacological products, obtaining, at the same time, economic returns and a reduction of the environmental impact of this industry, attaching it to the perspective of the circular economy.

scholarly journals Gap Filling of the CALYPSO HF Radar Sea Surface Current Data through Past Measurements and Satellite Wind Observations

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Adam Gauci ◽  
Aldo Drago ◽  
John Abela
Keyword(s):  
Oil Spills ◽  
Surface Current ◽  
Radar Data ◽  
Current Data ◽  
Hf Radar ◽  
Sea Surface ◽  
Machine Learning Techniques ◽  
Learning Techniques ◽  
Spatial Coverage ◽  
Essential Components

High frequency (HF) radar installations are becoming essential components of operational real-time marine monitoring systems. The underlying technology is being further enhanced to fully exploit the potential of mapping sea surface currents and wave fields over wide areas with high spatial and temporal resolution, even in adverse meteo-marine conditions. Data applications are opening to many different sectors, reaching out beyond research and monitoring, targeting downstream services in support to key national and regional stakeholders. In the CALYPSO project, the HF radar system composed of CODAR SeaSonde stations installed in the Malta Channel is specifically serving to assist in the response against marine oil spills and to support search and rescue at sea. One key drawback concerns the sporadic inconsistency in the spatial coverage of radar data which is dictated by the sea state as well as by interference from unknown sources that may be competing with transmissions in the same frequency band. This work investigates the use of Machine Learning techniques to fill in missing data in a high resolution grid. Past radar data and wind vectors obtained from satellites are used to predict missing information and provide a more consistent dataset.

A comprehensive overview and recent advances on polyhydroxyalkanoates (PHA) production using various organic waste streams

2021 ◽  
Vol 325 ◽  
pp. 124685
Author(s):  
Rijuta Ganesh Saratale ◽  
Si-Kyung Cho ◽  
Ganesh Dattatraya Saratale ◽  
Avinash A. Kadam ◽  
Gajanan S. Ghodake ◽  
...  
Keyword(s):  
Organic Waste ◽  
Waste Streams ◽  
Comprehensive Overview ◽  
Recent Advances ◽  
Pha Production

scholarly journals Integration of Fossil Fuel-based with Bio-based Industries: The Use of Waste Streams and Biomass to Produce Syngas and Added Value Products

2019 ◽  
Vol 52 (1) ◽  
pp. 616-621 ◽  
Author(s):  
Elham Ketabchi ◽  
Laura Pastor-Perez ◽  
Tomas Ramirez Reina ◽  
Harvey Arellano-Garcia
Keyword(s):  
Fossil Fuel ◽  
Added Value ◽  
Waste Streams

scholarly journals COMMUNITY-BASED ORGANIC WASTE PROCESSING USING BSF MAGGOT BIOCONVERSION

2021 ◽  
Vol 5 (2) ◽  
pp. 83-90
Author(s):  
Mohamad Satori ◽  
Ivan Chofyan ◽  
Yuliadi Yuliadi ◽  
Otong Rukmana ◽  
Ira Ayu Wulandari ◽  
...  
Keyword(s):  
Organic Waste ◽  
Waste Treatment ◽  
Animal Feed ◽  
Economic Value ◽  
Animal Husbandry ◽  
Boarding School ◽  
Added Value ◽  
Community Based ◽  
The People ◽  
Organic Waste Treatment

Organic waste is the largest composition of waste generated by the people of Indonesia, which is around 50-60%. This type of waste, especially food waste, is easy to smell if it is stored for too long so that it has the potential to pollute the environment. On the other hand, organic waste has good nutrients that can be generated, including through BSF (Black Soldier Fly) maggot bioconversion treatment. The BSF maggot bioconversion method is a method of processing organic waste which is carried out by converting organic matter into other products that are useful and have added value by utilizing biological processes from microorganisms and enzymes. Organic waste treatment with this method is generally carried out on a community-based basis and is integrated with the development of agriculture, fisheries and animal husbandry, because maggot cultivation produces commodities of economic value such as compost and maggot larvae. Compost contains very good nutrients so that it can be used for organic farming and maggot contains high protein that can be used for animal feed and fisheries. The implementation of this program was piloted in the boarding school community, namely the Az-Zakaria Islamic Boarding School which is managed by the Az-Zakaria Islamic Education Foundation (YPI) in Sindangbarang Village, Jalaksana District, Kuningan Regency. The result of this implementation is the formation of a new group of entrepreneurs engaged in the cultivation and utilization of BSF maggots.

scholarly journals A Preliminary Study: Identification of Stream Waste Quantity and Composition in Bali Province, Indonesia

2020 ◽  
Vol 148 ◽  
pp. 05005
Author(s):  
I Made Wahyu Widyarsana ◽  
Enri Damanhuri ◽  
Nida Ulhusna ◽  
Elprida Agustina
Keyword(s):  
Waste Management ◽  
Organic Waste ◽  
Management Policy ◽  
Waste Generation ◽  
Waste Streams ◽  
Textile Waste ◽  
Waste Management Policy ◽  
Administration Method ◽  
Preliminary Study ◽  
Waste Flow

Bali Province is an island of high tourist activity surrounded by the sea. Without a proper mainland waste management, waste problem will impact the aquatic environment. River and beach are waterways that become an important role in the waste flow that will end to the sea. Identification of waste in rivers and beaches is needed to determine the stream waste management policy. Measurements were made by adopting the NOAA (National Oceanic and Atmospheric Administration) method on 4 rivers and 4 beaches. Measurement of waste generation and composition represents the watershed and population density classification groups. The peak hour for the waste streams at 11.00-14.00 WITA (GMT+8). The dominant waste is organic waste (59.10% WW) and hazardous waste (17.12%WW). From the waste measurement on the beach, the waste density is around 0.087 tonnes/m3 and the composition of waste is dominated by plastic waste, paper waste, and textile waste. The average waste density in beach is around 0.007 kg/m2 or 0.53 items/m2. Yeh Gangga Beach is the dirtiest with 0.64 items waste/m2 and Lepang Beach is the cleanest beach with 0.27 items/m2.

scholarly journals Fermentation of Organic Residues to Beneficial Chemicals: A Review of Medium-Chain Fatty Acid Production

Processes ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 1571
Author(s):  
Panagiota Stamatopoulou ◽  
Juliet Malkowski ◽  
Leandro Conrado ◽  
Kennedy Brown ◽  
Matthew Scarborough
Keyword(s):  
Organic Waste ◽  
Chain Elongation ◽  
Organic Substrates ◽  
Industrial Chemicals ◽  
Waste Streams ◽  
Fatty Acid Production ◽  
Medium Chain ◽  
Renewable Feedstocks ◽  
History Of ◽  
Complex Organic

Medium-chain fatty acids (MCFAs) have a variety of uses in the production of industrial chemicals, food, and personal care products. These compounds are often produced through palm refining, but recent work has demonstrated that MCFAs can also be produced through the fermentation of complex organic substrates, including organic waste streams. While “chain elongation” offers a renewable platform for producing MCFAs, there are several limitations that need to be addressed before full-scale implementation becomes widespread. Here, we review the history of work on MCFA production by both pure and mixed cultures of fermenting organisms, and the unique metabolic features that lead to MCFA production. We also offer approaches to address the remaining challenges and increase MCFA production from renewable feedstocks.

Oxidation of Organic Radioactive Waste by Electrochemical Mediation

2001 ◽  
Author(s):  
E. Cantrel ◽  
A. Fonteyne ◽  
N. Impens ◽  
A. Rahier
Keyword(s):  
Radioactive Waste ◽  
Organic Waste ◽  
Hazardous Materials ◽  
Original Method ◽  
Mediation Process ◽  
Classical Approach ◽  
Acid Media ◽  
Volatile Products ◽  
Organic Radioactive Waste

Abstract Liquid as well as solid organic radioactive waste can be processed by means of combustion. However, this method presents several well-known drawbacks including the corrosion of the ovens, the production of radioactive ashes and radioactive or toxic volatile products. The electrochemical mediation process is an excellent alternative to combustion, especially when dealing with hazardous materials such as explosives, pesticides, drugs and nuclear organic waste. Nevertheless, using the silver(II) species as electrogenerated mediator, requires to work in concentrated nitric acid media, which results, via its electrolysis, in a continuous NOx emission. The classical approach, using absorption columns and scrubbers to trap NOx, impairs the attractiveness of this process. Therefore the SCK•CEN has developed and patented an original method to suppress in-situ any formation of NOx, conferring the process mobility and compactness.

Towards the collaborative development of machine learning techniques in planning support systems – a Sydney example

2020 ◽  
pp. 239980832093997 ◽  
Author(s):  
Oliver Lock ◽  
Michael Bain ◽  
Christopher Pettit
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Support System ◽  
Support Systems ◽  
Added Value ◽  
Machine Learning Techniques ◽  
Planning Support Systems ◽  
Planning Support ◽  
Learning Techniques ◽  
Planning Support System

The rise of the term ‘big data’ has contributed to recent advances in computational analysis techniques, such as machine learning and more broadly, artificial intelligence, which can extract patterns from large, multi-dimensional datasets. In the field of urban planning, it is pertinent to understand both how such techniques can advance our understanding of cities, and how they can be embedded within transparent and effective digital planning tools, known as planning support systems. This research specifically focuses on two related contributions. First, it investigates the role of planning support systems in supporting a participatory data analytics approach through an iterative process of developing and evaluating a planning support system environment. Second, it investigates how specifically machine learning planning support systems can be co-designed by built environment practitioners and stakeholders in this environment to solve a real planning issue in Sydney, Australia. This paper presents the results of applied research undertaken through the design and implementation of four workshops, involving 57 participants who were involved in a co-design process. The research follows a mixed-methods approach, studying a wide array of measures related to participatory analytics, task load, perceived added value, recordings and observations. The results highlight recommendations regarding the design and evaluation of planning support system environments for co-design and their coupling with machine learning techniques. It was found that consistency and transparency are highly valued and central to the design of a planning support system in this context. General attitudes towards machine learning and artificial intelligence as techniques for planners and developers were positive, as they were seen as both potentially transformative but also as simply another technique to assist with workflows. Some conceptual challenges were encountered driven by practitioners' simultaneous need for concrete scenarios for accurate predictions, paired with a desire for predictions to drive the development of these scenarios. Insights from this work can inform future planning support system evaluation and co-design studies, in particular those aiming to support democracy enhancement, greater inclusion and more efficient resource allocation through a participatory analytics approach.

Sign in / Sign up

Export Citation Format

Share Document