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Publikasjoner (10 av 119) Visa alla publikasjoner
Petrovic, B., Eriksson, O., Zhang, X. & Wallhagen, M. (2024). Carbon Assessment of a Wooden Single-Family Building—Focusing on Re-Used Building Products. Buildings, 14(3), Article ID 800.
Åpne denne publikasjonen i ny fane eller vindu >>Carbon Assessment of a Wooden Single-Family Building—Focusing on Re-Used Building Products
2024 (engelsk)Inngår i: Buildings, E-ISSN 2075-5309, Vol. 14, nr 3, artikkel-id 800Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Previous research has shown a lack of studies with comparisons between primary (virgin) and secondary (re-used) building materials, and their embodied emissions. The creation of different scenarios comparing the environmental impact of virgin vs. re-used materials is also motivated by the scarcity of raw materials in the world and the emergency of mitigating greenhouse gas (GHG) emissions from buildings. The aim of this study was to investigate scenarios, including new vs. re-used building products, applying the LCA method for a wooden single-family building. The findings showed a 23% reduction potential for total released (positive) CO2e when comparing the Reference scenario with Scenario I, using re-used wooden-based materials. Further, Scenario II, using all re-used building materials except for installations, showed a 59% CO2e reduction potential compared to the Reference scenario. Finally, Scenario III, which assumes all re-used building products, showed a 92% decreased global warming potential (GWP) impact compared to the Reference scenario. However, when including biogenic carbon and benefits (A5 and D module), the Reference scenario, based on newly produced wooden building materials, has the largest negative GHG emissions. It can be concluded that the re-use of building products leads to significant carbon savings compared to using new building products.

Emneord
biogenic carbon; circularity; end-of-life (EOL); life cycle assessment (LCA); global warming potential (GWP); environmental impact; wood; single-family building
HSV kategori
Identifikatorer
urn:nbn:se:du-48303 (URN)10.3390/buildings14030800 (DOI)
Prosjekter
Dalarnas Villa
Tilgjengelig fra: 2024-03-26 Laget: 2024-03-26 Sist oppdatert: 2024-03-27bibliografisk kontrollert
Han, M., Canli, I., Shah, J., Zhang, X., Dino, I. G. & Kalkan, S. (2024). Perspectives of Machine Learning and Natural Language Processing on Characterizing Positive Energy Districts. Buildings, 14(2), Article ID 371.
Åpne denne publikasjonen i ny fane eller vindu >>Perspectives of Machine Learning and Natural Language Processing on Characterizing Positive Energy Districts
Vise andre…
2024 (engelsk)Inngår i: Buildings, E-ISSN 2075-5309, Vol. 14, nr 2, artikkel-id 371Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

The concept of a Positive Energy District (PED) has become a vital component of the efforts to accelerate the transition to zero carbon emissions and climate-neutral living environments. Research is shifting its focus from energy-efficient single buildings to districts, where the aim is to achieve a positive energy balance across a given time period. Various innovation projects, programs, and activities have produced abundant insights into how to implement and operate PEDs. However, there is still no agreed way of determining what constitutes a PED for the purpose of identifying and evaluating its various elements. This paper thus sets out to create a process for characterizing PEDs. First, nineteen different elements of a PED were identified. Then, two AI techniques, machine learning (ML) and natural language processing (NLP), were introduced and examined to determine their potential for modeling, extracting, and mapping the elements of a PED. Lastly, state-of-the-art research papers were reviewed to identify any contribution they can make to the determination of the effectiveness of the ML and NLP models. The results suggest that both ML and NLP possess significant potential for modeling most of the identified elements in various areas, such as optimization, control, design, and stakeholder mapping. This potential is realized through the utilization of vast amounts of data, enabling these models to generate accurate and useful insights for PED planning and implementation. Several practical strategies have been identified to enhance the characterization of PEDs. These include a clear definition and quantification of the elements, the utilization of urban-scale energy modeling techniques, and the development of user-friendly interfaces capable of presenting model insights in an accessible manner. Thus, developing a holistic approach that integrates existing and novel techniques for PED characterization is essential to achieve sustainable and resilient urban environments.

sted, utgiver, år, opplag, sider
MDPI, 2024
Emneord
Positive Energy District; machine learning; natural language processing; characterization
HSV kategori
Identifikatorer
urn:nbn:se:du-48012 (URN)10.3390/buildings14020371 (DOI)001172199400001 ()2-s2.0-85185706786 (Scopus ID)
Forskningsfinansiär
Vinnova, P2022-01000Swedish Energy Agency, 8569501
Tilgjengelig fra: 2024-02-10 Laget: 2024-02-10 Sist oppdatert: 2024-03-18bibliografisk kontrollert
Zhu, X., Zhang, X., Gong, P. & Li, Y. (2023). A review of distributed energy system optimization for building decarbonization. Journal of Building Engineering, 73, Article ID 106735.
Åpne denne publikasjonen i ny fane eller vindu >>A review of distributed energy system optimization for building decarbonization
2023 (engelsk)Inngår i: Journal of Building Engineering, E-ISSN 2352-7102, Vol. 73, artikkel-id 106735Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Building energy consumption has increased rapidly in the past decade, in particular for heat demand and electric vehicles, owning to the development of economy and improvement of living standard. Distributed Energy Systems (DESs), which can effectively improve the share of renewable energy in the energy mix, lower the energy cost and reduce environmental impact, is a promising approach to meet the increased energy demand. This paper presents a review of the system architecture of DESs for building decarbonization, including hybrid energy systems, energy storage technologies, building flexible loads, and electric vehicles. The uncertainties from both the environment and human interventions challenge the energy management due to the asynchrony between energy generation and energy consumption. Thus, the system should be optimally designed and operated to enhance the reliability, affordability, and flexibility of the DES. The paper highlights the adoption of optimization approaches. Finally, future trends and challenges are discussed. It is concluded that the digital transformation featured with IoT, AI, advanced machine learning, sophisticated optimization approaches, and Blockchain is the enabler for future smart cities. © 2023 Elsevier Ltd

sted, utgiver, år, opplag, sider
Elsevier Ltd, 2023
Emneord
Building decarbonization, DES, Digital twin, Energy optimization, Smart cities, Decarbonization, Electric loads, Electric vehicles, Energy management, Energy utilization, Environmental impact, Smart city, Building energy consumption, Decarbonisation, Distributed energy systems, Energy system optimizations, Heat demands, Living standards, Optimization approach, Renewable energies, Buildings
HSV kategori
Identifikatorer
urn:nbn:se:du-46118 (URN)10.1016/j.jobe.2023.106735 (DOI)2-s2.0-85159262587 (Scopus ID)
Tilgjengelig fra: 2023-06-02 Laget: 2023-06-02 Sist oppdatert: 2023-06-02bibliografisk kontrollert
Petrovic, B., Eriksson, O. & Zhang, X. (2023). Carbon assessment of a wooden single-family building – A novel deep green design and elaborating on assessment parameters. Building and Environment, 233, Article ID 110093.
Åpne denne publikasjonen i ny fane eller vindu >>Carbon assessment of a wooden single-family building – A novel deep green design and elaborating on assessment parameters
2023 (engelsk)Inngår i: Building and Environment, ISSN 0360-1323, E-ISSN 1873-684X, Vol. 233, artikkel-id 110093Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

The aim of this study was to investigate how the carbon accounting of a wooden single-family house is affected by (1) decreasing the carbon footprint by changes in building design, (2) differentiating biogenic carbon from fossil carbon and (3) including external benefits beyond the state-of-the-art system boundaries. The motivation of exploring different system boundaries, improved building design and investigating benefits aside of system boundaries rely on the fact of having the “full” picture of GHG emissions of building products. Changes in building design were analyzed by life cycle assessment (LCA) focusing on greenhouse gas (GHG) emissions, while the costs were assessed by using lice cycle cost (LCC). The findings showed that by including positive and negative emissions from the production phase for an improved building design within scenario 4 ‘Cradle to Gate + Biogenic Carbon + D module’ has the lowest embodied GHG emissions when compared to other approaches with −3.5 kg CO2e/m2/y50. Considering the impacts of the whole building, the lowest GHG emissions are within the scenario 8 ‘Cradle to Grave + Biogenic Carbon + D module‘ for the improved building design with −0.7 kg CO2e/m2/y50. The results suggest that a change to sustainable alternatives for building components that makes the whole building to be constructed by wood, could lead to significant reduction of GHG emissions compared to conventional material choices. Economically, testing sustainable solutions, the highlighted results are the construction costs that are almost double higher for CLT elements for the foundation compared to concrete. © 2023

Emneord
Biogenic carbon; Greenhouse gas (GHG); Life cycle assessment (LCA); Life cycle cost (LCC); Wood
HSV kategori
Identifikatorer
urn:nbn:se:du-45713 (URN)10.1016/j.buildenv.2023.110093 (DOI)000946735400001 ()2-s2.0-85150344074 (Scopus ID)
Tilgjengelig fra: 2023-03-27 Laget: 2023-03-27 Sist oppdatert: 2023-05-02bibliografisk kontrollert
Zhang, X., Shah, J. & Han, M. (2023). ChatGPT for Fast Learning of Positive Energy District (PED): A Trial Testing and Comparison with Expert Discussion Results. Buildings, 13(6), Article ID 1392.
Åpne denne publikasjonen i ny fane eller vindu >>ChatGPT for Fast Learning of Positive Energy District (PED): A Trial Testing and Comparison with Expert Discussion Results
2023 (engelsk)Inngår i: Buildings, E-ISSN 2075-5309, Vol. 13, nr 6, artikkel-id 1392Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Positive energy districts (PEDs) are urban areas which seek to take an integral approach to climate neutrality by including technological, spatial, regulatory, financial, legal, social, and economic perspectives. It is still a new concept and approach for many stakeholders. ChatGPT, a generative pre-trained transformer, is an advanced artificial intelligence (AI) chatbot based on a complex network structure and trained by the company OpenAI. It has the potential for the fast learning of PED. This paper reports a trial test in which ChatGPT is used to provide written formulations of PEDs within three frameworks: challenge, impact, and communication and dissemination. The results are compared with the formulations derived from over 80 PED experts who took part in a two-day workshop discussing many aspects of PED research and development. The proposed methodology involves querying ChatGPT with specific questions and recording its responses. Subsequently, expert opinions on the same questions are provided to ChatGPT, aiming to elicit a comparison between the two sources of information. This approach enables an evaluation of ChatGPT’s answers in relation to the insights shared by domain experts. By juxtaposing the outputs, a comprehensive assessment can be made regarding the reliability, accuracy, and alignment of ChatGPT’s responses with expert viewpoints. It is found that ChatGPT can be a useful tool for the rapid formulation of basic information about PEDs that could be used for its wider dissemination amongst the general public. The model is also noted as having a number of limitations, such as providing pre-set single answers, a sensitivity to the phrasing of questions, a tendency to repeat non-important (or general) information, and an inability to assess inputs negatively or provide diverse answers to context-based questions. Its answers were not always based on up-to-date information. Other limitations and some of the ethical–social issues related to the use of ChatGPT are also discussed. This study not only validated the possibility of using ChatGPT to rapid study PEDs but also trained ChatGPT by feeding back the experts’ discussion into the tool. It is recommended that ChatGPT can be involved in real-time PED meetings or workshops so that it can be trained both iteratively and dynamically. © 2023 by the authors.

Emneord
challenge, ChatGPT, communication and dissemination, impact, PED
HSV kategori
Identifikatorer
urn:nbn:se:du-46591 (URN)10.3390/buildings13061392 (DOI)001014319900001 ()2-s2.0-85163724827 (Scopus ID)
Tilgjengelig fra: 2023-08-03 Laget: 2023-08-03 Sist oppdatert: 2024-01-17
Han, Y., Wu, P., Geng, Z. & Zhang, X. (2023). Editorial: Energy efficiency analysis and intelligent optimization of process industry. Frontiers in Energy Research, 11, Article ID 1283021.
Åpne denne publikasjonen i ny fane eller vindu >>Editorial: Energy efficiency analysis and intelligent optimization of process industry
2023 (engelsk)Inngår i: Frontiers in Energy Research, E-ISSN 2296-598X, Vol. 11, artikkel-id 1283021Artikkel i tidsskrift, Editorial material (Annet vitenskapelig) Published
sted, utgiver, år, opplag, sider
Frontiers Media S.A., 2023
Emneord
efficiency analysis, energy systems, intelligent detection, intelligent optimization, process industry
HSV kategori
Identifikatorer
urn:nbn:se:du-47089 (URN)10.3389/fenrg.2023.1283021 (DOI)001074428200001 ()2-s2.0-85172190983 (Scopus ID)
Tilgjengelig fra: 2023-10-09 Laget: 2023-10-09 Sist oppdatert: 2023-10-20
Zhu, X., Gui, P., Zhang, X., Han, Z. & Li, Y. (2023). Multi-objective optimization of a hybrid energy system integrated with solar-wind-PEMFC and energy storage. Journal of Energy Storage, 72, Article ID 108562.
Åpne denne publikasjonen i ny fane eller vindu >>Multi-objective optimization of a hybrid energy system integrated with solar-wind-PEMFC and energy storage
Vise andre…
2023 (engelsk)Inngår i: Journal of Energy Storage, ISSN 2352-152X, E-ISSN 2352-1538, Vol. 72, artikkel-id 108562Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

The move towards achieving carbon neutrality has sparked interest in combining multiple energy sources to promote renewable penetration. This paper presents a proposition for a hybrid energy system that integrates solar, wind, electrolyzer, hydrogen storage, Proton Exchange Membrane Fuel Cell (PEMFC) and thermal storage to meet the electrical and heating demands of a student dormitory in Shanghai. The proposed system is optimized to simultaneously account for multiple objectives, including economy, environmental benefits, and grid interaction, measured by Equivalent Annual Cost (EAC) for the life cycle of 20 years, Primary Energy Saving Ratio (PESR) of the heating system and Grid Interaction Level (GIL) of the electrical system. The effectiveness of the optimization results from NSGA-II is verified and compared with MOPSO to determine the optimal installation configuration and operation strategies. The results highlight the significance of energy storage in enabling greater renewable integration and the potential of hydrogen to play a vital role in the transition to a low-carbon economy. The optimal design of the proposed hybrid system can meet the power and heat demand of a student dormitory with a floor area of 2679m2. The Pareto-optimal solutions of PESR and GIL for NSGA-II fall within the range of (89 %, 104 %) and (70 %, 88 %), respectively. A significant number of Pareto-optimal solutions cluster around an EAC of approximately 160 k RMB. The optimization by MOPSO exhibited the similar results. Additionally, the sensitivity analysis provides insights into the sensitivity of objectives to changes in optimal design parameters, facilitating the design and optimization of similar hybrid energy systems integrated with a closed loop for hydrogen production and utilization in the future. © 2023 Elsevier Ltd

sted, utgiver, år, opplag, sider
Elsevier, 2023
Emneord
Design optimization, Hybrid energy system, Multi-objective optimization, PEMFC, Sensitivity study, Carbon, Electronic structure, Energy conservation, Heat storage, Hybrid systems, Hydrogen production, Hydrogen storage, Life cycle, Optimal systems, Pareto principle, Proton exchange membrane fuel cells (PEMFC), Renewable energy resources, Sensitivity analysis, Solar power generation, Annual cost, Grid interaction, Interaction levels, Multi-objectives optimization, Primary energy savings, Proton-exchange membranes fuel cells, Sensitivity studies, Solar/wind, Multiobjective optimization
HSV kategori
Identifikatorer
urn:nbn:se:du-46708 (URN)10.1016/j.est.2023.108562 (DOI)001051721200001 ()2-s2.0-85166616843 (Scopus ID)
Tilgjengelig fra: 2023-08-14 Laget: 2023-08-14 Sist oppdatert: 2023-09-08bibliografisk kontrollert
Han, M., Shah, J. & Zhang, X. (2023). Review of natural language processing techniques for characterizing positive energy districts. In: journal of Physics; Conference series: . Paper presented at International Conference on the Built Environment in Transition, CISBAT 2023. Institute of Physics Publishing (IOPP), 2600(8), Article ID 082024.
Åpne denne publikasjonen i ny fane eller vindu >>Review of natural language processing techniques for characterizing positive energy districts
2023 (engelsk)Inngår i: journal of Physics; Conference series, Institute of Physics Publishing (IOPP), 2023, Vol. 2600, nr 8, artikkel-id 082024Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

The concept of Positive Energy Districts (PEDs) has emerged as a crucial aspect of endeavours aimed at accelerating the transition to zero carbon emissions and climate-neutral living spaces. The focus of research has shifted from energy-efficient individual buildings to entire districts, where the objective is to achieve a positive energy balance over a specific timeframe. The consensus on the conceptualization of a PED has been evolving and a standardized checklist for identifying and evaluating its constituent elements needs to be addressed. This study aims to develop a methodology for characterizing PEDs by leveraging natural language processing (NLP) techniques to model, extract, and map these elements. Furthermore, a review of state-of-the-art research papers is conducted to ascertain their contribution to assessing the effectiveness of NLP models. The findings indicate that NLP holds significant potential in modelling the majority of the identified elements across various domains. To establish a systematic framework for AI modelling, it is crucial to adopt approaches that integrate established and innovative techniques for PED characterization. Such an approach would enable a comprehensive and effective implementation of NLP within the context of PEDs, facilitating the creation of sustainable and resilient urban environments. © 2023 Institute of Physics Publishing. All rights reserved.

sted, utgiver, år, opplag, sider
Institute of Physics Publishing (IOPP), 2023
Emneord
modelling, natural language processing (NLP), NLP task, PED elements, positive energy districts, Energy efficiency, Natural language processing systems, Language processing, Modeling, Natural language processing, Natural language processing task, Natural languages, Positive energies, Positive energy district, Positive energy district element, Modeling languages
HSV kategori
Identifikatorer
urn:nbn:se:du-47653 (URN)10.1088/1742-6596/2600/8/082024 (DOI)2-s2.0-85180156963 (Scopus ID)
Konferanse
International Conference on the Built Environment in Transition, CISBAT 2023
Tilgjengelig fra: 2024-01-02 Laget: 2024-01-02 Sist oppdatert: 2024-01-02bibliografisk kontrollert
Saini, P., Huang, P., Fiedler, F., Volkova, A. & Zhang, X. (2023). Techno-economic analysis of a 5th generation district heating system using thermo-hydraulic model: A multi-objective analysis for a case study in heating dominated climate. Energy and Buildings, 296, Article ID 113347.
Åpne denne publikasjonen i ny fane eller vindu >>Techno-economic analysis of a 5th generation district heating system using thermo-hydraulic model: A multi-objective analysis for a case study in heating dominated climate
Vise andre…
2023 (engelsk)Inngår i: Energy and Buildings, ISSN 0378-7788, E-ISSN 1872-6178, Vol. 296, artikkel-id 113347Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

A 5th generation district heating (5GDH) system consists of a low-temperature network used as a heat source for de-centralized heat pumps to serve heating demand. Until now, there is a lack of studies looking into the economic aspect of implementing the 5GDH concept. The performance characteristics, system dynamics, and economic feasibility of the 5GDH system are insufficiently investigated in cold climates. This paper aims to bridge the research gap by performing the techno-economic analysis of a 5GDH system using a case study based in Tallinn, Estonia. A detailed thermo-hydraulic simulation model is constructed in TRNSYS and Fluidit Heat. In addition, the uncertainty and sensitivities on the economic performance are analysed using Monte Carlo method implemented in Python. The study further analyses the effectiveness of using solar power technologies in reducing the cost of heating. For designed boundary conditions, the system can deliver heat at levelised cost of heating (LCOH) of 80 €/MWh. Integration of photovoltaic up to a limited capacity results in 1 % reduction when compared to the base case LCOH. The economic benefit of photovoltaic thermal is lower compared to photovoltaic. This study can provide a benchmark for the application of 5GDH systems in heating dominated regions.

Emneord
5GDHC; Techno-economic analysis; Monte Carlo analysis; PV; PVT
HSV kategori
Identifikatorer
urn:nbn:se:du-46441 (URN)10.1016/j.enbuild.2023.113347 (DOI)001046454200001 ()2-s2.0-85164720487 (Scopus ID)
Tilgjengelig fra: 2023-07-13 Laget: 2023-07-13 Sist oppdatert: 2023-11-07bibliografisk kontrollert
Saini, P., Kivioja, V., Naskali, L., Byström, J., Semeraro, C., Gambardella, A. & Zhang, X. (2023). Techno-economic assessment of a novel hybrid system of solar thermal and photovoltaic driven sand storage for sustainable industrial steam production. Energy Conversion and Management, 292, Article ID 117414.
Åpne denne publikasjonen i ny fane eller vindu >>Techno-economic assessment of a novel hybrid system of solar thermal and photovoltaic driven sand storage for sustainable industrial steam production
Vise andre…
2023 (engelsk)Inngår i: Energy Conversion and Management, ISSN 0196-8904, E-ISSN 1879-2227, Vol. 292, artikkel-id 117414Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Decarbonising industrial heat is a significant challenge due to various factors such as the slow transition to renewable technologies and insufficient awareness of their availability. The effectiveness of commercially available renewable heating systems is not well defined in terms of techno-economic boundaries. This study presents a techno-economic assessment of a novel system designed for steam production at a food and beverage plant. The proposed system is combines parabolic trough collectors with pressurized water thermal storage and photovoltaic-driven high-temperature sand storage. The technological components within the hybrid system complements each other both economically and practically, resulting in cost and land area savings. To evaluate the proposed system, simulations were performed using a model developed in TRNSYS and Python. The combined system exhibits better economic and land use performance than when these technologies are used individually. Specifically, the system has a high solar fraction of 90% while remaining competitive with the existing boiler fuel cost. The study emphasizes the importance of multi-technology approaches in developing practical solutions for industrial heat decarbonization. The findings can guide industries in a transition to sustainable heat sources and contribute to global efforts in mitigating climate change.

HSV kategori
Identifikatorer
urn:nbn:se:du-46464 (URN)10.1016/j.enconman.2023.117414 (DOI)001039354600001 ()2-s2.0-85172667530 (Scopus ID)
Tilgjengelig fra: 2023-07-17 Laget: 2023-07-17 Sist oppdatert: 2023-11-07bibliografisk kontrollert
Prosjekter
Agent-GIS-5GDHC: Tekno-ekonomisk prestanda och genomförbarhetsstudie av 5GDHC teknik med agentbaserad modellering och GISPED-Svenskt deltagande i IEA EBC Annex 83 Positive Energy Districts (PED); Publikasjoner
Zhang, X., Penaka, S. R., Giriraj, S., Sánchez, M. N., Civiero, P. & Vandevyvere, H. (2021). Characterizing Positive Energy District (PED) through a Preliminary Review of 60 Existing Projects in Europe. Buildings, 11, Article ID 318.
Autokarakterisering av PED:er för digitala referenser mot iterativ processoptimering (PED-ACT)Integrerad tillgångsförvaltning för belysning i allmänna bibliotek genom Digital Tvilling; Publikasjoner
Lin, J., Shen, J. & Silfvenius, C. (2024). Human-Centric and Integrative Lighting Asset Management in Public Libraries: Insights and Innovations on Its Strategy and Sustainable Development. Sustainability, 16(5), 2096-2096Lin, J., Hedekvist, P. O., Mylly, N., Bollen, M., Shen, J., Xiong, J. & Silfvenius, C. (2024). Human-Centric and Integrative Lighting Asset Management in Public Libraries: Qualitative Insights and Challenges From a Swedish Field Study. IEEE Access, 12, 40905-40921Shen, J. (2023). A Critical Review of Lighting Design and Asset Management Strategies: Illuminating Practices and Lessons Learned for Swedish Public Libraries. In: 13th Nordic Symposium on Building Physics, NSB 2023 proceedings: . Paper presented at 13th Nordic Symposium on Building Physics, Aalborg, Denmark on 12-14 June 2023. Aalborg, Denmark
Gemensam styrning av elproduktion och elbilsladdning i bostadsområden-potential för ökad egenanvändning av solel?Förstudie av ångvärmepumpsystemet för hållbar omställning av industriell uppvärmning i Sverige
Organisasjoner
Identifikatorer
ORCID-id: ORCID iD iconorcid.org/0000-0002-2369-0169