Henrik Kofoed Nielsen

• Jabbari, Shahla Ghaffari; Domínguez, Jose Fermoso; Sufuentes, Sandra Rodríguez; Nyberg, Svein Olav Glesaaen; Vehus, Tore & Nielsen, Henrik Kofoed (2026). A Time-Resolved Analysis of VOCs and VVOCs from Interior Wood Materials in Low-Ventilation Environments. Forests. 17(8). doi: 10.3390/f17080884. Full text in Research Archive Show summary

  Selecting interior wood materials requires balancing functional and aesthetic demands with indoor air quality, as wood can emit volatile organic compounds (VOCs) and very volatile organic compounds (VVOCs) that either peak shortly after installation or persist over time. This study investigated time-resolved VOC and VVOC accumulation concentrations from untreated pine, spruce, aspen, and oak, representing wood species commonly used in Norway. Concentrations of VOCs and VVOCs were monitored for 25–28 days under low-ventilation, worst-case chamber conditions using Proton Transfer Reaction–Time-of-Flight Mass Spectrometry (PTR-TOF-MS). Emission behaviour was assessed using peak concentration, decay rate, half-time, stabilised concentration, cumulative exposure (AUC28), and available health-based thresholds. Clear species-dependent differences were observed. Pine was the dominant VOC source, with the highest peak concentration, stabilised concentration, and AUC28, mainly due to monoterpenes, which remained above the health-based threshold throughout the test period. Oak showed the second-highest VOC burden and a distinct acetate-dominated profile, with acetic acid showing the longest predicted exceedance duration. Aspen and spruce had lower VOC burdens, but their cumulative VVOC exposure exceeded VOC exposure. VVOCs generally peaked earlier than VOCs, although persistence varied by species. Overall, the concentration of VOCs and VVOCs was controlled by species, compound chemistry, volatility, and internal transport, supporting species- and compound-specific ventilation and material-selection strategies.

• Putra, Jouvan Chandra Pratama; Suárez, Silvia; Mateos, Maria Jose; Lao-Zea, Angela; Akhtar, Naureen & Nielsen, Henrik Kofoed [Show all 7 contributors for this article] (2026). TiO<inf>2</inf>/activated-biochar hybrid materials: Weight ratio effects on formaldehyde adsorption and photodegradation. Results in Engineering (RINENG). 30. doi: 10.1016/j.rineng.2026.110337. Full text in Research Archive Show summary

  The performance of Adsorbent-Photocatalyst Hybrids (APHs) based on TiO2 P25 (Evonik) and activated-biochar was investigated for formaldehyde (HCHO) adsorption and photodegradation in the gas phase. Two commercial biochars (birch and Norway spruce) were characterised to identify the most effective adsorbent based on surface area. A microporous wood-based activated charcoal (1374 m2 g-1) served as a reference, with micropore and mesopore volumes of 0.53 and 0.74 cm3 g-1 and pore sizes below 7 nm, for adsorption comparison with the biochars. Subsequently, the selected biochar was activated via wet and dry impregnation methods and then incorporated with TiO2 P25 (Evonik) to form hybrid materials with various weight ratios. The hybrid materials were characterised using BET (surface area), XRF (elemental composition), total carbon analysis, TGA (thermal stability), XRD, and SEM. To evaluate the adsorption and photodegradation performance, a total flow rate of 900 mL min-1 and a HCHO concentration of 15 ppm under UV-A light were applied to the hybrid materials. The results indicated that birch-derived activated biochar with a particle size ≤ 0.5 mm exhibited the highest adsorption performance. When synergised with TiO2 P25 (Evonik) at a 75:25 wt ratio, the hybrid material demonstrated the optimal photodegradation rate and complete mineralisation. The enhanced performance confirms that activated biochar improves photocatalytic efficiency by increasing HCHO availability on the TiO2 P25 (Evonik) surface compared to pure TiO2 P25 (Evonik). These findings provide the optimisation of TiO2-biochar hybrids under high-flow gas-phase conditions and highlight their potential for passive indoor HCHO removal.

• Jabbari, Shahla Ghaffari; Domínguez, Jose Fermoso; Sufuentes, Sandra Rodríguez; Nyberg, Svein Olav Glesaaen; Vehus, Tore & Nielsen, Henrik Kofoed (2025). VOC emissions from commercial wood panels using PTR-MS for indoor air quality evaluation. Frontiers in Built Environment. 11. doi: 10.3389/fbuil.2025.1591669. Full text in Research Archive Show summary

  Introduction: Wood panels, commonly used in cold climates like the Nordic countries for their aesthetic surface and availability, emit volatile organic compounds (VOCs) that can impact indoor air quality and may contribute to health risks, especially with repeated or prolonged exposure. While research has primarily focused on untreated fresh wood, little attention has been given to the VOC emissions from commercial wood panels. This study aims to investigate the VOC emission pattern, intensity, and profile of nine commercially untreated and treated wood panels commonly used in indoor environments, focusing on how wood type and surface treatments influence emission characteristics. Methods: The study utilizes Proton Transfer Reaction Time-of-Flight Mass Spectrometry combined with passive sampling, offering a more comprehensive analysis of volatile organic compounds, including both volatile and very volatile compounds, which traditional gas chromatography cannot capture. Advanced statistical methods, such as Bayesian posterior, principal component analysis, and hierarchical clustering analysis, were employed to identify key emission contributors and classify emission patterns. Results: The findings reveal that emission intensity and profiles are influenced by wood type and surface treatments. Pine and oak emitted higher proportions of VOCs, while spruce primarily emitted VVOCs. Glazing, staining, and painting significantly affect emission intensity, with glazing reducing pine total emissions by 81% and increasing them in spruce by 65%. Staining pine reduced VOC emissions by 74% but increased VVOC emissions by 63%, shifting the emission profile. Despite high emission intensity from untreated pine, painting reduced TVOC emissions by 93%, aligning its profile with lower-emission woods like aspen and spruce, making it more suitable for indoor use. Discussion: The right treatment can transform high-emission woods into materials resembling low-emission species, offering a practical means to mitigate indoor VOC loads.

• Jaiswal, Rajan; Agu, Cornelius Emeka; Nielsen, Henrik Kofoed; Eikeland, Marianne Sørflaten; Moldestad, Britt Margrethe Emilie & Thapa, Rajan Kumar (2023). Investigation of Bubble Properties in a Bubbling Fluidized-Bed Gasification Reactor Using a Computational Particle Fluid Dynamic Model. Industrial & Engineering Chemistry Research. ISSN 0888-5885. 62(21), p. 8500–8514. doi: 10.1021/acs.iecr.3c00626. Full text in Research Archive
• Opalic, Sven Myrdahl; Palumbo, Fabrizio; Goodwin, Morten; Lei, Jiao; Nielsen, Henrik Kofoed & Kolhe, Mohan Lal (2023). COST-WINNERS: COST reduction WIth Neural NEtworks-based augmented Random Search for simultaneous thermal and electrical energy storage control. Journal of Energy Storage. ISSN 2352-152X. 72(B). doi: 10.1016/j.est.2023.108202. Full text in Research Archive Show summary

  The combination of local renewable energy production, dynamic loads, and multiple energy storage systems with different dynamics requires sophisticated control systems to maximize the energy cost efficiency of the combined energy system. Battery and thermal energy storage systems can be combined to increase the local use of on-site renewable energy, reduce peak power demand, and exploit time-of-use energy pricing. In this paper, we focus on how the augmented random search algorithm and artificial neural networks can be used together to solve an energy cost optimization problem involving the control of a battery energy storage system and a thermal energy storage system at the same time in a smart warehouse. As part of this work, a simulated training environment made using the data from the smart warehouse’s operations. In addition to the energy storage systems, the warehouse energy system has integrated a large roof mounted photovoltaic power plant and an industrial-scale cooling system. The developed solution is able to minimize the energy costs by modulating both energy systems, depending on the situation. Additionally, when it is tested against the state-of-the-art solutions, our developed solution at worst matches performance when the alternative algorithm is allowed to increase training time by a factor of nearly three. On average, our presented solution doubles the performance of the benchmark algorithm with much less computational resource expenditure.

• Hosamo, Haidar; Nielsen, Henrik Kofoed; Kraniotis, Dimitrios; Svennevig, Paul Ragnar & Svidt, Kjeld (2023). Improving building occupant comfort through a digital twin approach: A Bayesian network model and predictive maintenance method. Energy and Buildings. ISSN 0378-7788. 288. doi: 10.1016/j.enbuild.2023.112992. Full text in Research Archive Show summary

  This study introduces a Bayesian network model to evaluate the comfort levels of occupants of two non-residential Norwegian buildings based on data collected from satisfaction surveys and building performance parameters. A Digital Twin approach is proposed to integrate building information modeling (BIM) with real-time sensor data, occupant feedback, and a probabilistic model of occupant comfort to detect and predict HVAC issues that may impact comfort. The study also uses 200000 points as historical data of various sensors to understand the previous building systems’ behavior. The study also presents new methods for using BIM as a visualization platform and for predictive maintenance to identify and address problems in the HVAC system. For predictive maintenance, nine machine learning algorithms were evaluated using metrics such as ROC, accuracy, F1-score, precision, and recall, where Extreme Gradient Boosting (XGB) was the best algorithm for prediction. XGB is on average 2.5% more accurate than Multi-Layer Perceptron (MLP), and up to 5% more accurate than the other models. Random Forest is around 96% faster than XGBoost while being relatively easier to implement. The paper introduces a novel method that utilizes several standards to determine the remaining useful life of HVAC, leading to a potential increase in its lifetime by at least 10% and resulting in significant cost savings. The result shows that the most important factors that affect occupant comfort are poor air quality, lack of natural light, and uncomfortable temperature. To address the challenge of applying these methods to a wide range of buildings, the study proposes a framework using ontology graphs to integrate data from different systems, including FM, CMMS, BMS, and BIM. This study’s results provide insight into the factors that influence occupant comfort, help to expedite identifying equipment malfunctions and point towards potential solutions, leading to more sustainable and energy-efficient buildings.

• Hosamo, Haidar; Hosamo, Mohsen; Nielsen, Henrik Kofoed; Svennevig, Paul Ragnar & svidt, kjeld (2022). Digital Twin of HVAC system (HVACDT) for multiobjective optimization of energy consumption and thermal comfort based on BIM framework with ANN-MOGA. Advances in Building Energy Research. ISSN 1751-2549. doi: 10.1080/17512549.2022.2136240. Full text in Research Archive
• Hosamo, Haidar; Svennevig, Paul Ragnar; Svidt, Kjeld; Han, Daguang & Nielsen, Henrik Kofoed (2022). A Digital Twin predictive maintenance framework of air handling units based on automatic fault detection and diagnostics. Energy and Buildings. ISSN 0378-7788. 261(261). doi: 10.1016/j.enbuild.2022.111988. Full text in Research Archive Show summary

  The building industry consumes the most energy globally, making it a priority in energy efficiency initiatives. Heating, ventilation, and air conditioning (HVAC) systems create the heart of buildings. Stable air handling unit (AHU) functioning is vital to ensuring high efficiency and extending the life of HVAC systems. This research proposes a Digital Twin predictive maintenance framework of AHU to overcome the limitations of facility maintenance management (FMM) systems now in use in buildings. Digital Twin technology, which is still at an initial stage in the facility management industry, use Building Information Modeling (BIM), Internet of things (IoT) and semantic technologies to create a better maintenance strategy for building facilities. Three modules are implemented to perform a predictive maintenance framework: operating fault detection in AHU based on the APAR (Air Handling Unit Performance Assessment Rules) method, condition prediction using machine learning techniques, and maintenance planning. Furthermore, the proposed framework was tested in a real-world case study with data between August 2019 and October 2021 for an educational building in Norway to validate that the method was feasible. Inspection information and previous maintenance records are also obtained through the FM system. The results demonstrate that the continually updated data combined with APAR and machine learning algorithms can detect faults and predict the future state of Air Handling Unit (AHU) components, which may assist in maintenance scheduling. Removing the detected operating faults resulted in annual energy savings of several thousand dollars due to eliminating the identified operating faults.

• Opalic, Sven Myrdahl; Goodwin, Morten; Lei, Jiao; Nielsen, Henrik Kofoed & Kolhe, Mohan Lal (2022). Augmented Random Search with Artificial Neural Networks for energy cost optimization with battery control. Journal of Cleaner Production. ISSN 0959-6526. 380(2). doi: 10.1016/j.jclepro.2022.134676. Full text in Research Archive Show summary

  Intermittent renewable energy production and dynamic load must be balanced through appropriate control of integrated energy storage to account for the temporal discrepancy among power supply and demand. Intelligent control systems are required to anticipate and optimize the charging and discharging of energy storage. In recent years, reinforcement learning based techniques have been applied to a multitude of problems, including building integrated energy storage solutions. In this work, the focus is on the application of reinforcement learning based techniques to the specific energy optimization problem of controlling a battery energy storage system in a smart warehouse. This paper adopts data from a real operational battery energy storage system installed in a smart warehouse, integrated with photovoltaic, for food distribution on the west coast of Norway. In the smart warehouse, an intelligent energy management system controls the on-site battery energy storage using machine learning predictions of load and photovoltaic production, and an optimization algorithm is presented to generate a schedule for effective utilization of battery energy storage in coordination with a thermal storage system. This paper presents the combination of the augmented random search reinforcement algorithm with artificial neural networks as a basis to design an intelligent energy management system for controlling energy flows of battery energy storage systems to minimize the energy cost. The developed algorithm finds very promising solutions in the considered case-study of a smart house for energy cost minimization through a battery energy storage system, achieving an average of 99.2% accuracy across 10 seeded trials.

• Hosamo, Haidar; Imran, Aksa; Cardenas, Juan Diego; Svennevig, Paul Ragnar; svidt, kjeld & Nielsen, Henrik Kofoed (2022). A Review of the Digital Twin Technology in the AEC-FM Industry. Advances in Civil Engineering. ISSN 1687-8086. 2022. doi: 10.1155/2022/2185170. Full text in Research Archive Show summary

  The Architecture, Engineering, Construction, and Facility Management (AEC-FM) industry is increasingly affected by digital technologies that monitor sensor network data and control automation systems. Advances in digital technologies like Digital Twin offer a high-level representation of buildings and their assets by integrating the physical and digital world. This paper examines patterns, gaps, and trends in the AEC-FM sector and contributes to digitalization and automation solutions for building management. This work covers a broad range of research topics, from intelligent information management of complex models to building information management and the interaction of building systems, where researchers are increasingly interested in using the Digital Twin to manage their information and in developing new research lines focused on data interchange and the interoperability of building information modeling (BIM) and facility management (FM). After a complete bibliometric search of several databases and following selection criteria, 77 academic publications about the Digital Twin application in the AEC-FM industry were labeled and clustered accordingly. This study analyzed in detail the concept of key technologies, including “Digital Twin in Facility Lifecycle Management,” “Digital Twin-Information Integration Standards,” “Digital Twin-Based Occupants Centric Building Design,” “Digital Twin-Based Predictive Maintenance,” “Semantic Digital Twin for Facility Maintenance,” and “Digital Twin-Based Human Knowledge.” The findings show that information standardization is the first major hurdle that must be overcome before the actual use of Digital Twin can be realized in the AEC-FM industry. Based on that, this paper provides a conceptual framework of Digital Twin for building management as a starting point for future research.

• Hosamo, Haidar; Tingstveit, Merethe Solvang; Nielsen, Henrik Kofoed; Svennevig, Paul Ragnar & svidt, kjeld (2022). Multiobjective optimization of building energy consumption and thermal comfort based on integrated BIM framework with machine learning-NSGA II. Energy and Buildings. ISSN 0378-7788. 277. doi: 10.1016/j.enbuild.2022.112479. Full text in Research Archive
• Hosamo, Haidar; Nielsen, Henrik Kofoed; Alnmr, Ammar; Svennevig, Paul Ragnar & Svidt, Kjeld (2022). A review of the Digital Twin technology for fault detection in buildings. Frontiers in Built Environment. 8. doi: 10.3389/fbuil.2022.1013196. Full text in Research Archive Show summary

  This study aims to evaluate the utilization of technology known as Digital Twin for fault detection in buildings. The strategy consisted of studying existing applications, difficulties, and possibilities that come with it. The Digital Twin technology is one of the most intriguing newly discovered technologies rapidly evolving; however, some problems still need to be addressed. First, using Digital Twins to detect building faults to prevent future failures and cutting overall costs by improving building maintenance is still ambiguous. Second, how Digital Twin technology may be applied to discover inefficiencies inside the building to optimize energy usage is not well defined. To address these issues, we reviewed 326 documents related to Digital Twin, BIM, and fault detection in civil engineering. Then out of the 326 documents, we reviewed 115 documents related to Digital Twin for fault detection in detail. This study used a qualitative assessment to uncover Digital Twin technology’s full fault detection capabilities. Our research concludes that Digital Twins need more development in areas such as scanner hardware and software, detection and prediction algorithms, modeling, and twinning programs before they will be convincing enough for fault detection and prediction. In addition, more building owners, architects, and engineers need substantial financial incentives to invest in condition monitoring before many of the strategies discussed in the reviewed papers will be used in the construction industry. For future investigation, more research needs to be devoted to exploring how machine learning may be integrated with other Digital Twin components to develop new fault detection methods.

• Nielsen, Henrik Kofoed; Vehus, Tore; Rudra, Souman & Kristiansen, Nils Randulf (2022). Chapter 9 - Biomass production, storage, and pretreatment for the production of solid biofuels. In Castro, Fernando Gomez & Gutierrez-Antonio, Claudia (Ed.), Biofuels and Biorefining Volume 1: Current Technologies for Biomass Conversion. Elsevier. ISSN 9780128241165. p. 339–380. doi: 10.1016/B978-0-12-824116-5.00003-9. Full text in Research Archive
• Jaiswal, Rajan; Moldestad, Britt Margrethe Emilie; Eikeland, Marianne Sørflaten; Nielsen, Henrik Kofoed & Thapa, Rajan Kumar (2022). Image Processing and Measurement of the Bubble Properties in a Bubbling Fluidized Bed Reactor. Energies. 15(21). doi: 10.3390/en15217828. Full text in Research Archive Show summary

  The efficiency of a fluidized bed reactor depends on the bed fluid dynamic behavior, which is significantly influenced by the bubble properties. This work investigates the bubble properties of a bubbling fluidized bed reactor using computational particle fluid dynamic (CPFD) simulations and electrical capacitance tomography (ECT) measurements. The two-dimensional images (along the reactor horizontal and vertical planes) of the fluidized bed are obtained from the CPFD simulations at different operating conditions. The CPFD model was developed in a commercial CPFD software Barracuda Virtual Reactor 20.0.1. The bubble behavior and bed fluidization behavior are characterized form the bubble properties: average bubble diameter, bubble rise velocity, and bubble frequency. The bubble properties were determined by processing the extracted images with script developed in MATLAB. The CPFD simulation results are compared with experimental data (obtained from the ECT sensors) and correlations in the literature. The results from the CPFD model and experimental measurement depicted that the average bubble diameter increased with an increase in superficial gas velocities up to 4.2 Umf and decreased with a further increase in gas velocities due to the onset of large bubbles (potential slugging regime). The bubble rise velocity increased as it moved from the lower region to the bed surface. The Fourier transform of the transient solid volume fraction illustrated that multiple bubbles pass the plane with varying amplitude and frequency in the range of 1–6 Hz. Further, the bubble frequency increased with an increase in superficial gas velocity up to 2.5Umf and decreased with a further increase in gas velocity. The CPFD model and method employed in this work can be useful for studying the influence of bubble properties on conversion efficiency of a gasification reactor operating at high temperatures.

• Hosamo, Haidar; Nielsen, Henrik Kofoed; Kraniotis, Dimitrios; Svennevig, Paul Ragnar & Svidt, Kjeld (2022). Digital Twin framework for automated fault source detection and prediction for comfort performance evaluation of existing non-residential Norwegian buildings. Energy and Buildings. ISSN 0378-7788. 281. doi: 10.1016/j.enbuild.2022.112732. Full text in Research Archive Show summary

  Numerous buildings fall short of expectations regarding occupant satisfaction, sustainability, or energy efficiency. In this paper, the performance of buildings in terms of occupant comfort is evaluated using a probabilistic model based on Bayesian networks (BNs). The BN model is founded on an in-depth anal- ysis of satisfaction survey responses and a thorough study of building performance parameters. This study also presents a user-friendly visualization compatible with BIM to simplify data collecting in two case studies from Norway with data from 2019 to 2022. This paper proposes a novel Digital Twin approach for incorporating building information modeling (BIM) with real-time sensor data, occupants’ feedback, a probabilistic model of occupants’ comfort, and HVAC faults detection and prediction that may affect occupants’ comfort. New methods for using BIM as a visualization platform, as well as a pre- dictive maintenance method to detect and anticipate problems in the HVAC system, are also presented. These methods will help decision-makers improve the occupants’ comfort conditions in buildings. However, due to the intricate interaction between numerous equipment and the absence of data integra- tion among FM systems, CMMS, BMS, and BIM data are integrated in this paper into a framework utilizing ontology graphs to generalize the Digital Twin framework so it can be applied to many buildings. The results of this study can aid decision-makers in the facility management sector by offering insight into the aspects that influence occupant comfort, speeding up the process of identifying equipment malfunc- tions, and pointing toward possible solutions.

• Riva, Lorenzo; Wang, Liang; Ravenni, Giulia; Bartocci, Pietro; Buø, Therese Videm & Skreiberg, Øyvind [Show all 8 contributors for this article] (2021). Considerations on factors affecting biocarbon densification behavior based on a multiparameter model. Energy. ISSN 0360-5442. 221. doi: 10.1016/j.energy.2021.119893. Full text in Research Archive Show summary

  The optimization of upscaled biochar pelleting is limited by lack of knowledge regarding the effects of process parameters. A multiparameter model, coupled to a single pellet press unit, was for the first time applied to biochar production to predict the upscaled biochar pelleting process behavior. The model permits to estimate in a time and cost-effective way how the die friction forces, quantified through the pellet exiting pressure, are affected by the key process parameters. It was observed that to achieve acceptably low exiting pressures (in the order of 100 MPa), it was critical to produce biochar at high temperatures (e.g. 600 °C). Addition of water as a binder is also beneficial, while pelletization temperature does not significantly affect the exiting pressure. Furthermore, when pyrolysis oil was used as a binder, lower exiting pressures were measured. Biochar returned higher exiting pressure values compared with untreated wood, but lower compared with torrefied wood. Moreover, the correlation between density and compressive strength was also examined. It was found that the exiting pressure trend is a good indicator to estimate the mechanical quality of the pellets.

• Bandara, Janitha; Jaiswal, Rajan; Nielsen, Henrik K.; Moldestad, Britt Margrethe Emilie & Eikeland, Marianne Sørflaten (2021). Air gasification of wood chips, wood pellets and grass pellets in a bubbling fluidized bed reactor. Energy. ISSN 0360-5442. 233. doi: 10.1016/j.energy.2021.121149. Full text in Research Archive Show summary

  Gasification is an attractive method for biomass-to-energy conversion and fluidized bed design is one of the best options for large scale operation. A bubbling fluidized bed reactor was used to analyze the effects of biomass type, equivalence ratio (ER) and temperature for product gas compositions. Wood chips, wood pellets and grass pellets were gasified between 650 °C and 800 °C temperature. The ER was varied between 0.08 and 0.16. Gasification of grass pellets was difficult at 800 °C due to agglomeration and the gas composition was poor compared to wood. The reactor performances improved over the temperature and 650 °C was not sufficient to achieve a reasonable carbon conversion. Nitrogen dilution at higher ERs was counter weighted by improved carbon conversion at higher temperatures. The highest carbon conversion was achieved at 800 °C which were 75.8% and 70.6% for wood chips and wood pellets at 0.15 and 0.16 ERs respectively.

• Gul, Eid; Riva, Lorenzo; Nielsen, Henrik Kofoed; Yang, Haiping; Zhou, Hewen & Yang, Qing [Show all 12 contributors for this article] (2021). Substitution of coke with pelletized biocarbon in the European and Chinese steel industries: An LCA analysis. Applied Energy. ISSN 0306-2619. 304, p. 1–12. doi: 10.1016/j.apenergy.2021.117644. Full text in Research Archive Show summary

  According to the Financial Times the steel industry emissions accounted for 7–9% of total greenhouse gases emissions worldwide in 2019. The main contribution to those emissions is directly related to the use of fossil coke and coal as fuels and reducing agents. Four solutions can be adopted to address such issue: direct reduction with hydrogen or syngas, electric arc furnaces, carbon capture and storage and use of biofuels (for example the so called “biocarbon”). These solutions can be also integrated. We propose applying innovative methods to produce biocarbon by pelletizing charcoal with pyrolysis oils and reheating it at high temperatures, to obtain materials with sufficient hardness, reduced porosity and proper reactivity. Once upgraded biocarbon can comply with the requirements usually needed for metallurgical coke. We present in this paper the results of a technical and economic analysis plus an environmental analysis on the expected final use of biocarbon in the silicon and steel industry.

• Riva, Lorenzo; Cardarelli, Alessandro; Andersen, Geir Johan; Buø, Therese Videm; Barbanera, Marco & Bartocci, Pietro [Show all 8 contributors for this article] (2020). On the self-heating behavior of upgraded biochar pellets blended with pyrolysis oil: Effects of process parameters. Fuel. ISSN 0016-2361. 278. doi: 10.1016/j.fuel.2020.118395. Full text in Research Archive
• Wang, Liang; Riva, Lorenzo; Skreiberg, Øyvind; Khalil, Roger Antoine; Bartocci, Pietro & Yang, Qing [Show all 11 contributors for this article] (2020). Effect of torrefaction on properties of pellets produced from woody biomass. Energy & Fuels. ISSN 0887-0624. 34(12), p. 15343–15354. doi: 10.1021/acs.energyfuels.0c02671. Full text in Research Archive Show summary

  Torrefaction has been recognized as a promising strategy to improve handling and storage properties of wood-based pellets, thus producing a uniform-quality commodity with high energy density and hydrophobicity. In this work, pellets produced from spruce stem wood, bark, and forest residues were torrefied in a bench-scale tubular reactor at 225 and 275 °C with two residence times (30 and 60 min). The effects of torrefaction on general properties, grindability, mechanical properties, hydrophobicity, and microstructure of the studied pellets were investigated. The increase of torrefaction severity reduced mass yields, but the heating values and the fixed carbon content of the torrefied pellets considerably increased. The grindability of raw pellets was substantially improved after torrefaction treatment. The energy required for grinding torrefied pellets is less than 50% of the energy needed for grinding the untreated pellets. In comparison to untreated pellets, the particles from ground torrefied pellets have clearly smaller sizes in a narrower size range. The increase of torrefaction severity improved hydrophobicity of the pellets, which have high resistance to water uptake and maintain their integrity after immersion testing. Upon torrefaction treatment, the durability and tensile strength of the pellets slightly decreased. Scanning electron microscopy analysis results show that particles from wood pellets torrefied at 275 °C lost their fibrous structure with an evident decrease of length/diameter ratios compared to untreated wood pellets. The particles from ground torrefied pellets are more uniform in terms of shape and size. Torrefaction can considerably improve grindability and uniformity of wood-based pellets and make them more acceptable in pulverized fuel applications. Wood,Biomass,Energy,Durability,Materials

• Surup, Gerrit Ralf; Nielsen, Henrik Kofoed; Großarth, Marius; Deike, Rüdiger; Bulcke, Jan Van den & Kibleur, Pierre [Show all 12 contributors for this article] (2020). Effect of operating conditions and feedstock composition on the properties of manganese oxide or quartz charcoal pellets for the use in ferroalloy industries. Energy. ISSN 0360-5442. 193, p. 1–13. doi: 10.1016/j.energy.2019.116736. Full text in Research Archive
• Opalic, Sven Myrdahl; Goodwin, Morten; Lei, Jiao; Nielsen, Henrik Kofoed; Pardiñas, Ángel Á. & Hafner, Armin [Show all 7 contributors for this article] (2020). ANN modelling of CO2 refrigerant cooling system COP in a smart warehouse. Journal of Cleaner Production. ISSN 0959-6526. 260, p. 1–10. doi: 10.1016/j.jclepro.2020.120887. Full text in Research Archive Show summary

  Industrial cooling systems consume large quantities of energy with highly variable power demand. To reduce environmental impact and overall energy consumption, and to stabilize the power requirements, it is recommended to recover surplus heat, store energy, and integrate renewable energy production. To control these operations continuously in a complex energy system, an intelligent energy management system can be employed using operational data and machine learning. In this work, we have developed an artificial neural network based technique for modelling operational CO2 refrigerant based industrial cooling systems for embedding in an overall energy management system. The operating temperature and pressure measurements, as well as the operating frequency of compressors, are used in developing operational model of the cooling system, which outputs electrical consumption and refrigerant mass flow without the need for additional physical measurements. The presented model is superior to a generalized theoretical model, as it learns from data that includes individual compressor type characteristics. The results show that the presented approach is relatively precise with a Mean Average Percentage Error (MAPE) as low as 5%, using low resolution and asynchronous data from a case study system. The developed model is also tested in a laboratory setting, where MAPE is shown to be as low as 1.8%.

• Bartocci, Pietro; Yang, Haiping; Gul, Eid; Riva, Lorenzo; Skreiberg, Øyvind & Barbanera, Marco [Show all 11 contributors for this article] (2020). How to Produce Green Coke? Proceedings of Applied Energy Symposium: MIT A+B, United States, 2020. Scanditale. ISSN 9789198563474. Full text in Research Archive Show summary

  According to the Financial Times the steel industry emissions accounted for 7-9% of total GHG emissions worldwide in 2019. The main share is directly related to the use of fossil coke and coal as fuels and reducing agents. About four solutions can be adopted to address such issue: direct reduction with hydrogen or syngas, electric arc furnaces, carbon capture and storage and use of biofuels (so-called “biocarbon”). These solutions can also be integrated. We propose applying innovative methods to produce biocarbon by pelletizing biocarbon with pyrolysis oil and reheating it at high temperatures to obtain materials with sufficient hardness, reduced porosity and reduced reactivity. The upgrade takes biocarbon closer to the requirements usually applied to metallurgical coke. We present also the results of technical and economic analysis plus environmental analysis on the expected final use of biocarbon in steel industry.

• Opalic, Sven Myrdahl; Goodwin, Morten; Lei, Jiao; Nielsen, Henrik Kofoed & Kolhe, Mohan Lal (2020). A Deep Reinforcement Learning scheme for Battery Energy Management. In Solic, P (Eds.), 2020 5th International Conference on Smart and Sustainable Technologies (SpliTech). IEEE Press. ISSN 9789532901054. p. 1–6. doi: 10.23919/SpliTech49282.2020.9243797. Full text in Research Archive
• Bandara, Janitha; Jayarathna, Chameera; Thapa, Rajan Kumar; Nielsen, Henrik Kofoed; Moldestad, Britt Margrethe Emilie & Eikeland, Marianne Sørflaten (2020). Loop seals in circulating fluidized beds – Review and parametric studies using CPFD simulation. Chemical Engineering Science (CES). ISSN 0009-2509. 227. doi: 10.1016/j.ces.2020.115917. Full text in Research Archive Show summary

  Loop seal is a robust particle recycling technique used in circulating fluidized bed (CFB) reactors. The rate and the location of the loop seal aeration exert a significant impact on the rate of particle circulation (GS). The standpipe balances the cumulative pressure drop across the rest of the CFB by adjusting its particle height or gas-particle slip velocity. Higher fraction of the loop seal aeration naturally flows down to riser. Increased pressure drop in the standpipe results in high rate of particle circulation. Computational-particle-fluid-dynamic (CPFD) code is customized for multiphase flow modelling. The inbuilt tool of “BC connectors” was incorporated to downsize a CFB into a loop seal. The simulation results of GS and system pressures for loop seal showed a perfect match with experimentally validated CFB model. A parametric study for the effects of aeration rate, aeration position and length of the horizontal section was performed using the developed CPFD model of the loop seal. GS increased proportionally with the loop seal aeration, reaching an approximate threshold at 0.9 Nm3/h and beyond that GS did not improve significantly. Uniform aeration from the loop seal bottom realized the highest particle circulation with a 71% increment. The length of the horizontal section of the loop seal exhibited an inverse relationship on the particle circulation.

• Tingstveit, Merethe Solvang; Nielsen, Henrik Kofoed & Risholt, Birgit Dagrun (2020). Hygrothermal conditions in Cross Laminated Timber (CLT) dwellings. E3S Web of Conferences. 172. doi: 10.1051/e3sconf/202017210009. Full text in Research Archive Show summary

  The use of CLT has been increasing the last decade, and a subsequently focus on documentation of the accompanying indoor climate and exposed wooden surfaces on human well-being. This study presents the results of a measurement campaign conducted over one year of a CLT apartment building in Grimstad, Norway. The apartment building consists of three floors with 35 apartments and comply with the Norwegian passive house standard and energy grade A. Measurements of the relative humidity (RH), indoor air temperature and wood moisture content (MC) were performed in the exposed CLT spruce panels in three apartments in two different floors. The results from the three apartments show a relatively small variation in the MC values regardless the residents behavior measured as RH variation through a complete year. Selected periods from a cold period (winter) and a warm period (summer) show the variation in relative humidity (RH) and moisture content in the CLT element. However, results from control measurements showed higher MC values. The gap between the measurements and methods are discussed.

• Surup, Gerrit Ralf; Nielsen, Henrik Kofoed; Heidelmann, Markus & Trubetskaya, Anna (2019). Characterization and reactivity of charcoal from high temperature pyrolysis (800–1600 °C). Fuel. ISSN 0016-2361. 235, p. 1544–1554. doi: 10.1016/j.fuel.2018.08.092. Full text in Research Archive Show summary

  This study presents the effect of wood origin and heat treatment temperature on the CO2 reactivity, nanostructure and carbon chemistry of chars prepared at 800, 1200, and 1600 °C in slow pyrolysis reactors. The structure of charcoal was characterized by transmission electron microscopy, Raman spectroscopy, mercury intrusion porosimetry and N2 adsorption. The CO2 reactivity of char was investigated by thermogravimetric analysis. Results showed that spruce and oak chars have similar reactivity at all heat treatment temperatures. The oak char prepared at 1600 °C contained long and flat graphene layers and interplanar distance that is similar to graphite and thus, was more ordered than the spruce char. The TEM analysis showed that charcoal had structural characteristics of non-graphitizing carbon. Thus, increasing heat treatment temperature increases the graphitization of char structure, leading to the reactivity that is nearly similar to that of low reactive metallurgical coke. The wood origin, heat treatment temperature, nanostructure, differences in porosity and pore size of char influenced the CO2 reactivity less than the differences in CO2 concentrations.

• Riva, Lorenzo; Nielsen, Henrik Kofoed; Skreiberg, Øyvind; Wang, Liang; Bartocci, Pietro & Barbanera, Marco [Show all 8 contributors for this article] (2019). Analysis of optimal temperature, pressure and binder quantity for the production of biocarbon pellet to be used as a substitute for coke. Applied Energy. ISSN 0306-2619. 256, p. 1–16. doi: 10.1016/j.apenergy.2019.113933. Full text in Research Archive Show summary

  In order to contribute to the decarbonization of the economy, efficient alternatives to coal and coke should be found not only in the power sector but also in the industrial sectors (like steel, silicon and manganese production) in which coal and coke are used as a reductant and for steel production also as a fuel. To this aim many research works have been focused on the development of a coke substitute based on woody biomass and known as “biocarbon”. There are still barriers to overcome, among them: the biocarbon low density, poor mechanical strength and high reactivity. In this paper a new biocarbon production methodology is proposed, based on: pyrolysis at 600 °C, densification (using pyrolysis oil as binder), reheating of the obtained pellet. Response surface methodology with a Box-Behnken experimental design was utilized to evaluate the effects of the process conditions on the pellet's quality. Responses showed that densification was mainly affected by oil content and pelleting temperature, while pelleting pressure had a minor influence. The pelleting process has been finally optimized using Derringer's desired function methodology. Optimal pelletizing conditions are: temperature equal to 60 °C, pressure equal to 116.7 MPa, oil content concentration of 33.9 wt%. These results are relevant for metal production industries at a global level. The identified optimal parameters of the new biocarbon production process can contribute to replace coke with sustainable fuels and probably reduce great part of the related greenhouse gases emissions. © The Authors

• Opalic, Sven Myrdahl; Goodwin, Morten; Lei, Jiao; Nielsen, Henrik Kofoed & Kolhe, Mohan Lal (2019). Modelling of Compressors in an Industrial CO 2-Based Operational Cooling System Using ANN for Energy Management Purposes, Engineering Applications of Neural Networks. EANN 2019.. Springer. ISSN 9783030202569. doi: 10.1007/978-3-030-20257-6_4. Full text in Research Archive Show summary

  Large scale cooling installations usually have high energy consumption and fluctuating power demands. There are several ways to control energy consumption and power requirements through intelligent energy and power management, such as utilizing excess heat, thermal energy storage and local renewable energy sources. Intelligent energy and power management in an operational setting is only possible if the time-varying performance of the individual components of the energy system is known. This paper presents an approach to model the compressors in an industrial, operational two-stage cooling system, with CO 2 as the working fluid, located in an advanced food distribution warehouse in Norway. An artificial neural network is adopted to model the compressors using the operational data. The model is trained with cooling medium evaporation and condensation temperature, suction gas temperature and compressor operating frequency, and outputs electrical power load and cooling load. The best results are found by using a single hidden layer with 45 hidden neurons and a hyperbolic tangent activation function trained with the Adam optimizer, with a resulting mean squared error as low as 0.08% for both the training and validation data sets. The trained model will be part of a system implemented in a real-world setting to determine the cooling load, compressor power load, and coefficient of performance. An intelligent energy management system will utilize the model for energy and power optimization of the cooling system by storing energy in a thermal energy storage, using predictions of energy demand and cooling system performance.

• Surup, Gerrit Ralf; Vehus, Tore; Eidem, Per Anders; Trubetskaya, Anna & Nielsen, Henrik Kofoed (2019). Characterization of renewable reductants and charcoal-based pellets for the use in ferroalloy industries. Energy. ISSN 0360-5442. 167, p. 337–345. doi: 10.1016/j.energy.2018.10.193. Full text in Research Archive
• Bandara, Janitha; Thapa, Rajan Kumar; Nielsen, Henrik Kofoed; Moldestad, Britt Margrethe Emilie & Eikeland, Marianne Sørflaten (2019). Circulating fluidized bed reactors – part 01: analyzing the effect of particle modelling parameters in computational particle fluid dynamic (CPFD) simulation with experimental validation. Particulate Science and Technology. ISSN 0272-6351. doi: 10.1080/02726351.2019.1697773. Full text in Research Archive Show summary

  A CPFD hydrodynamic model was developed for a circulating fluidized bed system and the simulation results were validated against experimental data based on particle circulation rate. Sensitivity of the computational mesh was primarily tested and extended grid refinement was needed at the loopseal to match the particle circulation rate with experimental data. The particle circulation rate was independent of the range of number of computational particles used in this study. A 10% reduction of the particle circulation rate was observed as the particle-wall interaction parameter was changed from 0.85 to 0.55 and 17% increment when the close-packed volume fraction was changed from 0.56 to 0.62. The pressure constant in the particle stress model showed the greatest impact for the circulation rate with 57% increment as the constant was changed from 2.5 to 5. The highest absolute variation in the pressure was observed at the loop seal and pressure values were under predicted in all sections.

• Riva, Lorenzo; Nielsen, Henrik Kofoed; Buø, Therese Videm; Zhuo, Hewen; Yang, Qing & Yang, Haiping [Show all 11 contributors for this article] (2019). LCA Analysis of Biocarbon Pellet Production to Substitute Coke. DEStech Transactions on Environment, Energy and Earth Sciences. ISSN 2475-8833. doi: 10.12783/dteees/iceee2019/31754. Full text in Research Archive Show summary

  Biocarbon is a promising alternative to fossil reductants for decreasing greenhouse gas emissions and increasing sustainability of the metallurgical industry. In comparison to conventional reductants (i.e., coke and coal), biocarbon has low density, poor mechanical strength and high reactivity. Densification is an efficient way to upgrade biocarbon and improve its undesirable properties. In this study, woody biocarbon is compressed into pellets using pyrolysis oils as a binder. In fact both pyrolysis oils and charcoal can be produced through the slow pyrolysis process and represent respectively the liquid product and the solid product. Pyrolysis gases can be used to sustain the process. Mass and energy balance of the biocarbon pelletization process are calculated and used to implement a LCA analysis. Final use of the produced biocarbon will be in the silicon industry in Norway.

• Riva, Lorenzo; Surup, Gerrit Ralf; Buø, Therese Videm & Nielsen, Henrik Kofoed (2019). A study of densified biochar as carbon source in the silicon and ferrosilicon production. Energy. ISSN 0360-5442. 181, p. 985–996. doi: 10.1016/j.energy.2019.06.013. Full text in Research Archive
• Bandara, Janitha; Nielsen, Henrik Kofoed; Moldestad, Britt Margrethe Emilie & Eikeland, Marianne Sørflaten (2018). Sensitivity Analysis and Effect of Simulation parameters of CPFD Simulation in Fluidized Beds. Linköping Electronic Conference Proceedings. ISSN 1650-3686. p. 334–341. doi: 10.3384/ecp18153334. Full text in Research Archive Show summary

  Fluidized bed technology is broadly applied in industry due to its distinct advantages. CFD simulation of fluidized beds is still challenging compared to single-phase systems and needs extensive validation. Multiphase particle-in-cell is a recently developed lagrangian modeling technique and this work is devoted to analyze the sensitivity of grid size, time step, and model parameters, which are the essences of accurate results. Barracuda VR 17.1.0 commercial CFD package was used in this study. 500µm sand particles and air was used as the bed material and fluidization gas respectively. Five different grids, having 27378, 22176, 16819, 9000 and 6656 computational cells were analysed, where five different time steps of 0.05, 0.01, 0.005, 0.001 and 0.0005 were used for each grid. One velocity step was maintained for 8 seconds. The bed pressure drop at packed bed operation was high for simulations with reduced time steps while equal pressure drops were observed during fluidization for all time steps. Time steps of 0.0005s and 0.001s and 0.005s produced equal result of 0.15 m/s for minimum fluidization velocity, irrespective of the grid size. The results from time steps of 0.05 and 0.01 are converged to the results from time steps of 0.005 and 0.001 by increasing simulation time per one velocity step.

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• Nielsen, Henrik Kofoed & Vehus, Tore (2025). Focusing on the use of wood as a building material in relation to IAQ and human health. [Internet]. https://www.youtube.com/watch?v=NoaBkOFqflk&t=1s. Full text in Research Archive
• Nielsen, Henrik Kofoed (2025). Brænderiets hemmeligheder. Full text in Research Archive
• Nielsen, Henrik Kofoed (2025). ENERGI: Energiparken og energiforsyning før og nå. Full text in Research Archive
• Nielsen, Henrik Kofoed (2024). Biomass production, storage, and pretreatment for the production of solid biofuels. Full text in Research Archive
• Nielsen, Henrik Kofoed (2024). Bioeconomy. Full text in Research Archive
• Nielsen, Henrik Kofoed (2024). The many faces of Bioenergy and Bioeconomy. Full text in Research Archive
• Nielsen, Henrik Kofoed (2024). Tre og inneklima: FoU på Universitetet i Agder. Full text in Research Archive
• Nielsen, Henrik Kofoed (2024). Bioenergi: Hvad skal vi bruge biomassen til? Full text in Research Archive
• Nielsen, Henrik Kofoed (2024). Indeklima og sundhed: K-Health in Air og målinger på Fagskolen i Agder. Full text in Research Archive
• Nielsen, Henrik Kofoed (2024). Bioenergi og bioøkonomi. Full text in Research Archive
• Nielsen, Henrik Kofoed (2024). K-Health in Air and VOC. Full text in Research Archive
• Nielsen, Henrik Kofoed (2024). VOC prosjektet til UiA. Full text in Research Archive
• Jabbari, Shahla Ghaffari; Nielsen, Henrik Kofoed & Vehus, Tore (2024). EXPLORING THE EFFECTIVENESS OF DIFFERENT AIR CLEANER TECHNOLOGIES IN REMOVING AIR POLLUTANTS WITH FOCUSING ON ENERGY SAVING and COSTS - AN OVERVIEW. Full text in Research Archive
• Putra, Jouvan Chandra Pratama; Vehus, Tore & Nielsen, Henrik Kofoed (2023). A Review on Electron-Hole Pairs Mechanism in Dark Photocatalysis. Full text in Research Archive
• Nielsen, Henrik Kofoed (2023). Biomass & bioenergy: Waste and residues to energy. Full text in Research Archive
• Nielsen, Henrik Kofoed (2023). Sustainable agriculture. Full text in Research Archive
• Larsen, Baard; Tømte, Thomas; Olsen, Susann Haga; Nielsen, Henrik Kofoed; Imenes, Anne Gerd & Paul, Alexander (2023). Kan ha stor betydning for framtiden. [Journal]. Grimstad Adressetidende. Full text in Research Archive Show summary

  Aldri tidligere har energibruk og energioptimalisering av kirker blitt kartlagt på denne måten. Nå jobber to studenter ved UiA med å se på mulighetene som finnes.

• Sellevold, Terje; Stiansen, Yngve & Nielsen, Henrik Kofoed (2022). Energisparing i egen bolig og Energidagen. [Radio]. NRK Sørlandet Sørlandssendinga. Full text in Research Archive
• Nielsen, Henrik Kofoed & Øymoen, Pål (2022). Dette er professorens tips til huset ditt. [Journal]. Grimstad Adressetidende. Full text in Research Archive
• Hosamo, Haidar; Nielsen, Henrik Kofoed; Svennevig, Paul Ragnar & svidt, kjeld (2022). Digital Twin technology toward more sustainable buildings. Full text in Research Archive
• Nielsen, Henrik Kofoed & Tambjerg, Ellen Holm (2022). HENRIK KOFOED NIELSEN - GUEST RESEARCHER AT AAU ENERGY. [Internet]. www.energy.aau.dk. Full text in Research Archive Show summary

  WHO ARE YOU, AND WHAT IS YOUR BACKGROUND? I have worked at the University of Agder in Kristiansand, Norway, for 30 years, primarily in the field of bioenergy which is a big interest of mine. I guess it can be related to my childhood on Bornholm growing up on a farm. WHAT DO YOU DO AT AAU ENERGY? I have been at AAU Energy since August 1st last year. My field of research is quite broad, and I have worked on different projects while being here. My main project is in continuation of my previous work on energy crops and regards the melting temperature of ash, but I have also spent some of my time as a PhD-supervisor while still fulfilling my different roles from back home at the Department of Engineering Sciences at the University of Agder. WHAT HAS THE PURPOSE BEEN? The main purpose of my stay in Aalborg has been to prune down the many tasks and different meetings I must attend to in Norway. At the same time, it has been beneficial and interesting to be part of a scientific environment with colleagues available for professional discussions whenever we meet during lunch break or at the coffee machine. HOW WAS IT ARRANGED? It began 20 years ago when I needed an external examiner and I got in touch with Lasse Rosendahl at AAU. We have been in contact with one another for different purposes ever since, and so I asked him and head of section Henrik Sørensen if I could stay and conduct research for a year. This was possible I was granted a sabbatical research leave. I have always been part of different exchange programs and have visited AAU several times in this regard, but it has always been for a maximum of two consecutive weeks. HOW HAS THE EXPERIENCE BEEN? It has been a great experience scientifically and regarding research. For me personally it has also been nice to live in Aalborg after living in Norway for many years. I have family here in Jutland and Aalborg is in proximity to Kristiansand and the University of Agder, which is a plus. AAU was also the obvious choice because of the long-standing cooperation between the universities. WHICH EXPERIENCES, BOTH SCIENTIFIC AND PERSONAL, DID YOU GAIN? When I first came to Denmark, I visited AAU in Esbjerg for the first time. I participated in a PhD course in which I taught sustainable forestry and learned very much from their fascinating equipment and skills. I have gained insight into different ways of conducting research and managing a department from the way it is done here, and I have attended as many meetings and seen as many different parts of the university as possible to experience and learn. For instance, I have been very interested in seeing the laboratories and how the students use them both at ENERGY and BUILD. I have also had various good social experiences, such as Unirun and DHL-run, which were a lot of fun to partake in while being another opportunity of getting to know colleagues. IS IT SOMETHING YOU WOULD RECOMMEND TO OTHERS? Absolutely. It has been very beneficial for me to be close to different relevant researchers at other departments as well as developing relationships and establishing contacts. It has been a pleasure to focus on my research and I bring various realizations and new knowledge with me home. I have always travelled a lot to other university and colleges, and this was yet another way for me to learn.

• Sund, Steinar Steinkopf & Nielsen, Henrik Kofoed (2022). Gir treverk i bygg bedre helse? [Journal]. Teknisk Ukeblad. Full text in Research Archive
• Nielsen, Henrik Kofoed (2022). Climate-resilient agriculture: Bioenergy. Full text in Research Archive
• Nielsen, Henrik Kofoed (2022). K-HEALTHinAIR: Gir tre i bygg bedre luftkvalitet og helse? Full text in Research Archive
• Nielsen, Henrik Kofoed (2022). Energisparing i egen bolig: Hvordan redusere strømregninga og samtidig bidra med gode klimatiltak? Full text in Research Archive
• Nielsen, Henrik Kofoed (2022). Bioenergi: Muligheder og begrænsninger & Forskning ved UiA. Full text in Research Archive
• Nielsen, Henrik Kofoed (2022). Bruk begrepene energiomstilling, energisparing og effektivitet for å taksere energiøkonomi i bygninger. Full text in Research Archive
• Wang, Liang; Riva, Lorenzo; Skreiberg, Øyvind; Czégény, Zsuzsanna; Bartocci, Pietro & Nielsen, Henrik Kofoed (2021). Study on Densification of Biocarbon for Metal Production Application. Full text in Research Archive
• Wang, Liang; Riva, Lorenzo; Bartocci, Pietro; Skreiberg, Øyvind; Czégény, Zsuzsanna & Nielsen, Henrik Kofoed (2021). Study on densification of biocarbon for metal production application. Full text in Research Archive
• Nielsen, Henrik Kofoed (2021). Hva gjør vi med de vanskelige sektorene? Kan biokull erstatte kull i smelteverkene? Hva kreves for å få dette til og hva er den reelle klimaeffekten? Full text in Research Archive
• Bartocci, Pietro; Riva, Lorenzo; Nielsen, Henrik Kofoed; Yang, Qing; Yang, Haiping & Skreiberg, Øyvind [Show all 10 contributors for this article] (2021). Two alternative fuels for the reduction of GHG emissions in the steel industry: biocarbon and hydrogen. Full text in Research Archive
• Bartocci, Pietro; Riva, Lorenzo; Nielsen, Henrik Kofoed; Yang, Qing; Yang, Haiping & Skreiberg, Øyvind [Show all 11 contributors for this article] (2020). How to produce green coke? Full text in Research Archive
• Wang, Liang; Riva, Lorenzo; Skreiberg, Øyvind; Bartocci, Pietro; Nielsen, Henrik Kofoed & Fantozzi, Francesco (2020). Effect of Pyrolysis Conditions and Use of Condensates as Binder on Densification of Biocarbon. Full text in Research Archive
• Opalic, Sven Myrdahl; Goodwin, Morten; Lei, Jiao; Nielsen, Henrik Kofoed & Kolhe, Mohan Lal (2020). A Deep Reinforcement Learning scheme for Battery Energy Management. Full text in Research Archive
• Nielsen, Henrik Kofoed (2020). Bioøkonomi - den nye olie. Full text in Research Archive
• Nielsen, Henrik Kofoed (2019). Hva er bioøkonomi - den nye oljen? Full text in Research Archive
• Nielsen, Henrik Kofoed (2019). Biochar in residual ash from gasifier cookstoves. Full text in Research Archive
• Nielsen, Henrik Kofoed (2019). Bioenergiens mange ansikter og muligheter. Full text in Research Archive
• Nielsen, Henrik Kofoed (2019). Hvad er bioøkonomi - den nye olie? Full text in Research Archive
• Nielsen, Henrik Kofoed (2019). Bioenergiens mange ansikter og muligheter. Full text in Research Archive
• Nielsen, Henrik Kofoed (2019). Bioenergi og u-landsovne. Full text in Research Archive
• Nielsen, Henrik Kofoed (2019). BIOMASS SYSTEMS: Extraction and Biochemical conversion; biogas and bioethanol;. Full text in Research Archive
• Nielsen, Henrik Kofoed (2019). Renewable energy at University of Agder. Full text in Research Archive
• Nielsen, Henrik Kofoed (2019). BIOMASS: Resources and production. Full text in Research Archive
• Nielsen, Henrik Kofoed (2019). BIOMASS SYSTEMS: BIOMASS PRE-TREATMENT. Full text in Research Archive
• Riva, Lorenzo; Buø, Therese Videm & Nielsen, Henrik Kofoed (2019). Validation and application of a multiparameter model for the densification of biochar. Full text in Research Archive
• Riva, Lorenzo; Buø, Therese Videm & Nielsen, Henrik Kofoed (2019). Biochar for metallurgical applications. Full text in Research Archive
• Nielsen, Henrik Kofoed (2019). Bioeconomy - the new oil? Full text in Research Archive
• Nielsen, Henrik Kofoed (2019). Biochar for metallurgical applications. Full text in Research Archive
• Riva, Lorenzo; Nielsen, Henrik Kofoed; Buø, Therese Videm; Zhuo, Hewen; Yang, Qing & Yang, Haiping [Show all 11 contributors for this article] (2019). LCA analysis of biocarbon pellet production to substitute coke. Full text in Research Archive
• Nielsen, Henrik Kofoed (2018). Bioenergy solutions in a fluctuating grid with wind and solar power. Full text in Research Archive
• Nielsen, Henrik Kofoed (2018). Future of bio fuels and their production. Full text in Research Archive
• Nielsen, Henrik Kofoed (2018). Bioenergi og u-landsovne. Full text in Research Archive
• Nielsen, Henrik Kofoed (2018). Biomass supply - Sources, pre-treatment, storage and handling. Full text in Research Archive
• Nielsen, Henrik Kofoed (2018). BIOMASS SUPPLY - Sources, pre-treatment, storage and handling. Full text in Research Archive
• Nielsen, Henrik Kofoed (2018). Bioenergy research at University of Agder. Full text in Research Archive
• Nielsen, Henrik Kofoed (2018). Biomass supply - Sources, pre-treatment, storage and handling. Full text in Research Archive
• Nielsen, Henrik Kofoed (2018). Bioenergiens mange ansikter og muligheter. Full text in Research Archive
• Nielsen, Henrik Kofoed (2018). Biobrændstoffer - Fordele og ulemper. Full text in Research Archive
• Skjevrak, Geir; Wang, Liang; Filbakk, Tore; Skreiberg, Øyvind; Nielsen, Henrik Kofoed & Hustad, Johan Einar (2018). Effects of Fuel Additives on Quality of Agricultural Wastes Pellets. Full text in Research Archive
• Nielsen, Henrik Kofoed (2018). Biokull- og drivstoff-forskning ved Universitetet i Agder. Full text in Research Archive
• Nielsen, Henrik Kofoed (2018). Bioøkonomi - den nye olie. Full text in Research Archive
• Riva, Lorenzo; Essmann, Uwe; Surup, Gerrit Ralf; Buø, Therese Videm & Nielsen, Henrik Kofoed (2018). Biochar Pelletization for Metallurgical Applications. Full text in Research Archive
• Hosamo, Haidar; Nielsen, Henrik Kofoed; Svennevig, Paul Ragnar & Svidt, Kjeld (2023). Digital Twin technology toward more sustainable buildings. Universitetet i Agder. ISSN 9788284271576. Full text in Research Archive Show summary

  The integration of digital technologies in the form of sensor networks and automation systems has a significant impact on the Architecture, Engineering, and Construction- Facility Management (AEC-FM) industry in terms of data monitoring and manage- ment. By combining the real and digital worlds, developments in digital technologies like Digital Twin provide a high-level depiction of buildings and their assets. This thesis covers a wide range of topics, including building information management and the interaction of building systems, where the Digital Twin technology becomes a solution to organizing data and generating new study lines on data interchange and BIM (Building Information Modeling)-FM interoperability. In order to contribute to digitalization and automation solutions for building management, the initial step in this thesis was to prepare a review of research on study patterns, gaps, and trends in the AEC-FM industry. After a complete bibliometric search of Google Scholar, Web of Science, and Scopus and following selection criteria, 77 academic publica- tions about the Digital Twin application in the AEC-FM industry were labeled and clustered accordingly. The results demonstrate that information standardization, predictive maintenance, users’ comfort, and optimizations are the marked fields where the Digital Twin in the AEC-FM industry should be implemented to reach Zero Emission Buildings (ZEB). This work suggests several novel frameworks for Digital Twin for building management as a place to start a further investigation.

• Kolhe, Mohan Lal; Goodwin, Morten; Lei, Jiao; Nielsen, Henrik Kofoed & Opalic, Sven Myrdahl (2023). Advanced Warehouse Energy Storage System Control Using Deep Supervised- and Reinforcement Learning. Universitetet i Agder. ISSN 9788284271521. Full text in Research Archive
• Tømte, Thomas; Nielsen, Henrik Kofoed & Imenes, Anne Gerd (2023). Preserving the Past, Powering the Future: Energy Efficiency and Renewables in Norway's Wooden Churches. Universitetet i Agder. Full text in Research Archive Show summary

  This master’s thesis explores the potential for energy efficiency in three wooden churches built in the 19th century in the southern part of Norway. Specifically, the thesis focuses on the three churches Eide, Landvik, and Grimstad, all owned and operated by the Grimstad Church Council. Each church presents its own unique set of challenges related to heating and overall energy efficiency, largely due to their varying sizes. The thesis examines the impact of various energy efficiency measures and explores the possibilities of implementing renewable energy systems such as solar panels and geothermal energy. At Eide church, three different configurations of solar panel systems have been studied, and the thesis also considers how the implementation of a battery can increase self-consumption of the church’s electricity production. PVsyst has been used to simulate these alternatives. The thesis highlights potential energy savings in the range of 30-50% by lowering the temper- ature, making simple structural upgrades, and upgrading the heating control system in an annex adjacent to the church. A combination of solar panels and energy efficiency measures could make the church energy positive. In Landvik church, the energy calculation program Simien has been used to assess the effects of various energy efficiency measures. Among the measures mentioned are retrofitting of roof, wall, and floor insulation, window replacement, lighting system upgrades, and temperature reduction. The results show that the church can achieve annual energy savings of up to 40% of the current energy consumption by combining multiple measures. Furthermore, this master’s thesis suggests that implementing a 25.5 kW liquid-to-water heat pump in Grimstad church, supplied from two energy wells, could cover 90% of the church’s energy consumption and thus save an equivalent proportion of biofuel oil, over 13 000 liters annually. The thesis identifies a significant need to educate and inform the church’s staff about energy efficiency and points out that too much responsibility is placed on those working for the church’s daily operations. Based on the large number of churches in Norway, the results of this study have significant transferability, and the potential for energy savings at a national and Nordic level is consid- erable. In conclusion, the thesis emphasizes that the approach requires a balance between advanced technologies, awareness, and basic practices.

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