Sirvi Autor "Tkaczyk, Alan Henry" järgi

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A framework for including enhanced exposure to naturally occurring radioactive materials (NORM) in LCA
(The International Journal of Life Cycle Assessment, 2016-11-22) Joyce, Peter James; Goronovski, Andrei; Tkaczyk, Alan Henry; Björklund, Anna
Despite advances in the development of impact categories for ionising radiation, the focus on artificial radionuclides produced in the nuclear fuel cycle means that the potential impacts resulting from increased exposure to naturally occurring radioactive materials (NORM) are still only covered to a limited degree in life cycle assessment (LCA). Here, we present a potential framework for the inclusion of the exposure routes and impact pathways particular to NORM in LCA.
Development of CNN-Based Models for Short-Term Load Forecasting in Energy Systems
(Tartu Ülikool, 2020) Kurylenko, Oleksandr; Tkaczyk, Alan Henry; Dam, Florentin; Aakenes, Ulf Roar; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Tehnoloogiainstituut
In this work, two deep learning models based on convolutional neural networks (CNNs) are developed for one-day-ahead hourly electricity consumption forecasting for the next calendar day. One-day-ahead electricity consumption forecasting is done to perform baseline load evaluation for the assessment of Demand Response (DR) performance and to predict the availability of flexibility products. Using electricity consumption time series data for three regions in Norway, the developed CNNbased models are compared to four industry-standard baseline models (Asymmetric High Five of Ten, Similar Profile Five of Ten, Average, and Daily Profile). Additionally, comparisons are made to a Naive model and an Autoregressive Integrated Moving Average (ARIMA) model, which includes Fourier terms. Three evaluation metrics are used to estimate the models’ performance. A detailed description of the methodology, work pipeline, and results is provided. The conducted experiments were successful in developing and applying the CNN-based models to the problem of one-day-ahead hourly electricity consumption forecasting for the next calendar day. The developed CNN and combination “CNN + Long Short-Term Memory (LSTM)” models showed the best performance results among the predictive models which employ the Multiple-Input Multiple-Output (MIMO) strategy to forecast 24 hours ahead. The Daily Profile model showed the best performance among models which cannot forecast 24 hours ahead or do not necessarily employ the MIMO strategy. It is worth noting that the Average model showed the best performance in the baseline load evaluation among all the considered models. However, the Average model is only a reference comparison which does not actually perform forecasting, but rather uses post-event data. It can be concluded that the work was successful in developing and applying the CNN-based models to short-term load forecasting in energy systems, especially since the developed CNN and CNN+LSTM models outperformed other similar forecasting models. Two different paths could be chosen for future work: one that intends to explore more and improve the CNN-based models developed in this work, and the one which aims to explore new CNN-based architectures.
Distribution of uranium, thorium and potassium in the Bayer process
(2nd Bauxite Residue Valorisation and Best Practices Conference, 2018) Goronovski, Andrei; Vind, Johannes; Vassiliadou, Vicky; Panias, Dimitrios; Tkaczyk, Alan Henry
Uranium, thorium, potassium and their decay product mass flows were analysed in the Bayer process. Gamma-ray spectroscopy was used to measure the radionuclide content in samples provided by Aluminium of Greece and to model their mass flows. We observed that at any analysed stage, the radionuclide content does not exceed the allowed safety limits set in the European Basic Safety Standard. Another important observation is that a minor portion of uranium from bauxites (3%) ends up in alumina, while the rest is accumulated in the bauxite residue (BR). All of the 226Ra (long-lived decay product of uranium), as well as all decay products of thorium accumulated in the BR. We observed accumulation of 40K in the process liquors, while this radionuclide was not found in the alumina.
IMPACT ASSESSMENT OF ENHANCED EXPOSURE FROM NATURALLY OCCURRING RADIOACTIVE MATERIALS (NORM) WITHIN LCA
(Journal of Cleaner Production, 2018-01-20) Goronovski, Andrei; Joyce, Peter James; Finnveden, Göran; Tkaczyk, Alan Henry; Björklund, Anna
The potential impact of ionising radiation from enhanced exposure to Naturally Occurring Radioactive Materials (NORM) to humans and the environment is not currently accounted for sufficiently in Life Cycle Assessment (LCA). Here we present midpoint and endpoint characterisation factors resulting from the implementation of impact assessment models for human health and ecosystems for NORM exposure. These models build upon existing fate, exposure and effect models from the LCA and radiological literature. The newly developed models are applied to a theoretical study of the utilisation of bauxite residue, a by-product of alumina processing enriched in natural radionuclides, in building materials. The ecosystem models have significant sensitivity to uncertainties surrounding the differential environmental fate of parent and daughter radionuclides that are produced as a part of decay chains, and to assumptions regarding long term releases from landfill sites. However, conservative results for environmental exposure suggest that in addition to landfill of materials, power consumption (burning coal and mining uranium) is a potentially significant source of radiological impact to the environment. From a human perspective, exposure to NORM in the use phase of building materials is the dominant source of impact, with environmental releases of nuclides playing a comparatively minor role. At an endpoint level, the impact of NORM exposure is highly significant in comparison to other impact categories in the area of protection of human health. This highlights the importance within LCA of having sufficient impact assessment models to capture all potential impacts, such that issues of burden shifting between impact measures can be captured, interpreted and resolved in the optimisation of product systems.
Incorporating the radiological effects and environmental impact assessment of naturally occurring radioactive materials (NORM) into the life cycle environmental optimisation of bauxite residue (BR) valorisation
(Bauxite Residue Valorisation and Best Practices, 2015-10) Joyce, Peter James; Goronovski, Andrei; Tkaczyk, Alan Henry; Björklund, Anna
Bauxite Residue (BR) is a potentially valuable source of metals and construction materials, which the ETN REDMUD project aims to develop technologies to exploit. Bauxite contains low levels of Naturally Occurring Radioactive Materials (NORM), which are concentrated in BR, and could potentially be released during BR valorisation, or further concentrated in novel products resulting from BR valorisation. Life Cycle Assessment (LCA) is a well-established and standardised methodology to quantify the potential impacts arising from the life cycle of products and services, however it is not currently possible use it to assess the radiological impacts of NORM. The inclusion of NORM exposure in LCA is an important step to avoid burden shifting in the environmental optimisation of BR valorisation.
Radiological Assessment of the Bauxite Residue Valorization Chain
(Journal of Radioanalytical and Nuclear Chemistry, 2019-07-27) Goronovski, Andrei; Tkaczyk, Alan Henry
The behavior of radionuclides in the bauxite residue valorization chain has been analyzed, and accumulation ratios have been measured for secondary residues produced after recovery of valuable metals. Key analysis outcomes are valid specifically for the processes and raw materials in use at the Aluminium of Greece plant and are as follows: the processing of bauxite residue from the is unlikely to create secondary residues that would be hazardous from the radiological perspective, even if bauxite residue is processed successively multiple times to recover different metals. From a radiological perspective, there are no considerable limitations for the exploitation of specific BR for metal recovery. As some conclusions may be raw material or process dependent, future research could assess the possibility of applying these outcomes to other bauxite plants.
Radiological assessment of the Bayer process
(Minerals Engineering, 2019-04-13) Goronovski, Andrei; Vind, Johannes; Vassiliadou, Vicky; Panias, Dimitrios; Tkaczyk, Alan Henry
Naturally occurring radionuclides were studied through the Bayer process by calculating their mass flows. Aluminium of Greece (AoG) provided sample materials and plant data from several process stages. Measurements of radionuclide concentrations were carried out by gamma-ray spectroscopy. The performed measurements show that in the specific case of the AoG plant, the majority of the natural radionuclides were introduced with karst bauxites, which showed higher activity concentrations for nuclides compared to lateritic bauxites. Most of these nuclides accumulated in the bauxite residue, while only a minor portion of uranium isotope 238U was found in alumina, corresponding to 3% of its input value. Uranium was observed to partially dissolve in the process liquors similarly to 40K, whereas the latter was not associated with aluminium hydroxide. All the materials studied in the current research work had radionuclide concentrations well below the exemption limits set by EURATOM Basic Safety Standard, indicating that these naturally occurring radionuclides do not pose a radiological hazard for workers of the AoG plant or the public.
Teaduskultuur Tartu Ülikooli täppisteadlaste töörühmas
(Tartu Ülikool, 2019) Mäekivi, Dolores; Telve, Keiu; Tkaczyk, Alan Henry; Tartu Ülikool. Humanitaarteaduste ja kunstide valdkond; Tartu Ülikool. Etnoloogia osakond