This parametric study aims to predict the performance of confluent jets ventilation (CJV) with variable air volume (VAV) from four CJV design parameters. A combination of computational fluid dynamics (CFD), and response surface method (RSM) has been used to predict the energy efficiency, thermal comfort and IAQ for the four expected vital design variables, i.e., heat load (X-H), number of nozzles (X-N), airflow rate (X-Q) and supply temperature (X-TS). The RSM was used to generate a quadratic equation for the response variables exhaust temperature (T-E), supply temperature (T-P), PMV, DR, epsilon(T) and ACE. The RSM shows that the T-E, T-P and PMV were independent of the number of nozzles. The proposed equations were used to generate setpoints optimized for thermal comfort (PMV) for summer, spring and winter cases with different CLO factors and different T-S under a scenario where the heat load varied between 10-30 W/m(2). T-E was used as setpoint to regulate the airflow rate to keep the PMV values close to zero. The results show that by adapting the T-S to the CLO factor both thermal comfort and the energy efficiency can be improved. Further energy reduction can be gained by downregulating the airflow rate to keep the T-P at a fixed setpoint when the heat load is decreased. This means that a CJV can effectively be combined with VAV to improve environmental performance with good thermal comfort (-0.5 < PMV < 0.5, DR < 20%), above average IAQ (ACE approximate to 106%) and with a higher heat removal efficiency (epsilon(T) approximate to 110%) than conventional mixing ventilation. Highlights center dot Parametric study of Confluent jet ventilation with VAV center dot Optimization of set points for VAV scheme with confluent jet ventilation center dot Increased ventilation performance with optimized VAV set points center dot Reduced energy cost with VAV set points optimized for thermal comfort and IAQ

In our digitalized world, Data Centers (DCs) serve as crucial infrastructure. Within the DC sector, data processing operations, including processes such as process cooling, hold special significance when investigated from an energy efficiency perspective, as they account for a substantial portion of total energy end-use. Therefore, it is important to prioritize data processing operations in energy management. The objective of this research is to explore the application of AI-powered clustering techniques to identify cooling operational statuses. Additionally, this research offers valuable perspectives on using AI for visualizing and identifying cooling patterns that deviate, which can provide valuable insights into DC energy management. The study object consists of a DC room equipped with Liquid Cooling Packages (LCPs). The findings show that the cooling power density on average is 9.1 kW/m 2 . Through analysis of the elbow curve, the optimal number of clusters is identified to be three. One of the identified clusters, i.e., Cluster 3, is characterized by large time periods with no supplied cooling from the LCPs. When comparing Clusters 1 and 2, Cluster 1 has a higher temperature difference between the chilled water supply and return, but a lower LCP return temperature compared to Cluster 2. Moreover, the quantified cooling characteristics contribute to the understanding of the LCPs’ operational statuses and cooling performance, which is useful for implementing targeted improvements, e.g., adjusting PID parameters, in the cooling infrastructure.

Direct Air Capture (DAC) technologies have emerged as a promising solution to address climate change and meet global climate goals. However, despite the importance of DAC in designing carbon-negative buildings, there is a lack of research focusing on the energy and cost aspects in building ventilation systems. The objective of this research is to investigate the CO2 capture potential and economic viability of integrating small-scale DAC into a building ventilation system integrated within a gym space. A gym space located in the city of Linköping, Sweden, is used as the research object. Furthermore, the study investigates the CO2 capture potential across a portfolio of gym spaces corresponding to an area of 24,760 m2. The results show that the CO2 capture potential varies between 54 kg/day and 83 kg/day for the investigated gym space. Moreover, the total CO2 capture potential is between 588 ton CO2/year and 750 ton CO2/year for the portfolio of gym spaces. The results also demonstrate that regenerating the sorbent during non-operating hours is more energy-efficient and economically advantageous compared to performing four complete regeneration cycles during operating hours. Based on a sorbent capture potential of 0.2 mmol/g and 2.0 mmol/g, and a CO2 price of 1,000 SEK, the break-even price for energy is 0.25–0.53 SEK/kWh. Lastly, the research shows that, among the investigated cases, the only economically viable solution corresponds to sorbent capture potential 2.0 mmol/g and utilizing low-grade heat for the generation process, resulting in a total cost of 663 SEK/ton CO2.

Information Communication Technology (ICT) centers play a vital role as essential facilities within our digitalized society. Energy efficiency holds great significance in the ICT sector, driven by the rising energy costs and to reduce the environmental impact. Simultaneously, it is essential to ensure a sufficient cooling supply for servers. Artificial Intelligence (AI) can be used to analyze patterns in large datasets, facilitating valuable insights that are difficult for humans to analyze alone because of the complexity and size of the datasets. The aim of this research is to characterize cooling patterns and explore how AI-driven clustering algorithms can be used to identify cooling operational statuses. The research object is an ICT room situated in Linköping, Sweden, and operated by the global telecommunications company Ericsson AB. The ICT room has Liquid Cooling Packages (LCPs) for water-based cooling.The results show that the average cooling power density in the ICT room is 6.98 kW/m2, and the interquartile range is 8.26 kW/m2. The results also demonstrate the potentialities in using AI-based clustering algorithms, K-means in the presented research, to uncover insights related to cooling operational statuses. Furthermore, the results show that it is suitable to divide the data points into four clusters, providing a detailed description of the characteristics of the dataset. The identified clusters differ with regards to variables, among other, such as LCP return air temperature and temperature difference between chilled water supply and return. This is beneficial in identifying undesired operational statuses of LCPs, e.g., low temperature difference between chilled water supply and return, which is an indicator of a poor cooling performance.

The demand for steel components with tailored properties is constantly growing. To obtain a specific variation of microstructures and mechanical properties along the component it must undergo a controllable cooling. One way to control the cooling rates along the component is by using different simultaneous water jet impingements on a hot austenitized surface. This can be done by a newly developed test rig for water Impinging Jet Quenching Technique (IJQT). This work discusses the effect of IJQT on mechanical properties and fracture behavior of 15 mm steel plates containing 0.27 and 0.38 mass-% carbon. The samples were cooled in a specifically designed setup of the technique to obtain simultaneous water and air cooling resulting in diverse microstructures. The mechanical property gradients of both steels were analyzed through hardness measurements and tensile tests. The fracture surfaces and the near fracture regions were observed using scanning electron microscope and light optical microscope respectively. The results from tensile tests showed that the larger part of the sample with higher carbon content was fully hardened, however smoothly transitioning to a more ductile region. The sample with lower carbon content combined various degrees of hardening and transitioned from higher to lower ultimate tensile strength values. Fracture behavior of higher carbon steel was predominantly brittle transitioning to a ductile, while the lower carbon steel had a small region showing brittle fracture transitioning to a larger region of predominant ductile fracture behavior.

The building and service sector accounts for nearly 40% of total energy use in Sweden. The existing, historic building stock accounts for large part of this energy use and comprises an important part of the national pursuit to increase energy efficiency. One main problem for decreasing energy use in the existing building stock is the lack of data describing thermal performance characteristics. This paper presents a novel development of the change-point model for predicting the thermal performance of buildings using selected time periods based on time-dependent variations in climate and user behavior. The predicted thermal power characteristics include total specific heat losses (Q(total)), energy use for hot water circulation (HWC) and hot tap water (HTW), and balance temperature. A residential district with 73 historic buildings in Linkoping, Sweden, has been used as the study object. The developed model is shown to be effective and robust for describing building thermal performance. The average R-2 was 0.70 for predictions of specific heat losses. The sensitivity analyses conclude that the selected time steps and months correspond to the highest R-2 value. The average variation width for prediction of the balance temperature is 0.9 degrees C for buildings in the interquartile range based on a three-year comparison of hourly heating power supply data. Moreover, from a property owner perspective, the model is shown to be useful for identifying deviating thermal power characteristics and can easily be used to get an overview of a district. (C) 2020 Elsevier B.V. All rights reserved.

Ändamålslokaler utgör en speciell byggnadstyp med stora krav på verksamhetsanpassning. Skolor och vårdlokaler utgör den största uppvärmda ytan i byggnader av icke-bostadstyp. Energianvändningen per kvadratmeter är betydligt högre i äldre lokaler jämfört med nyare, och 60% av den uppvärmda ytan finns i lokaler som är byggda före 1980. Att en så stor andel av våra ändamålslokaler är äldre innebär att de idag är i behov av att renoveras, energieffektiviseras och anpassas efter dagens krav på lokalerna. Många förvaltare av ändamålslokaler ställer sig därför frågan om det är bättre att riva gamla och slitna ändamålslokaler och bygga nya ändamålsenliga lokaler, istället för att renovera. Detta projekt syftar till ett ge ett underlag för beslutsfattare som ställs inför detta val och utgår till stor del från perspektivet livscykelkostnad (LCC).

Projektet har bestått av tre delar:

1. LCC-optimering för att identifiera kostnadsoptimala energieffektiviseringsåtgärder av befintliga byggnader i samband med renovering 
2. Jämförelse mellan kostnadsoptimal renovering och nybyggnation från ett LCC-perspektiv 
3. Identifiering av nyttor och fördelar under en byggnads livscykel, så kallade livscykelnyttor, i samband med renovering kontra rivning och nybyggnation 

Valet mellan att energirenovera och att riva och bygga nytt innebär att aspekter som inte ser likadana ut vid de olika ansatserna måste jämföras. Detta forskningsprojekt har angripit detta genom att studera livscykelkostnader för delar av byggnaden som påverkar dess energibalans med hjälp av livscykelkostnadsoptimering. Utöver detta har värden som upplevs uppnås vid renovering kontra rivning och nybyggnation studerats med hjälp av kvalitativa djupintervjuer och enkäter med förvaltare av skolor och förskolor i svenska kommuner. 

Investering samt LCC är lägre för att renovera än att riva och bygga nytt, så länge stommen inte är skadad. Samtidigt upplevds rivning och nybyggnation som en kostnadseffektiv ansats. Detta alternativ innebär viktiga indirekta nyttor, såsom effektiv drift, god verksamhetsanpassning, god inomhusmiljö och god ändamålsenlighet. Till viss del kan dock dessa värden uppnås även vid en renovering. Inomhusmiljöproblem och kapacitetsbrist är viktiga driftkrafter för att åtgärda skolor och förskolor. Dessa aspekter kan i vissa fall vara svåra att hantera vid renovering.  Renovering är dock den vanligaste ansatsen i svenska skolor och förskolor som behöver åtgärdas, och rivning och nybyggnation ses endast som ett alternativ om byggnaden är i så pass dåligt skick att den inte kan åtgärdas med renovering. Renovering har en kortare ledtid och kan i vissa fall innebära att evakueringen är lättare, jämfört med rivning och nybyggnation. 

Till viss del beror valet på kontexten i kommunen. Olika kommuner har olika förutsättningar och olika problematik i sitt byggnadsbestånd. Studien presenterar en matris med värden som kan uppnås vid renovering kontra rivning och nybyggnation, för att ge en grund för att bedöma vilket val som är lämpligt. Mer forskning kring bedömning av byggnadens skick samt vilka värden som efterfrågas, för att ge bättre underlag till valet mellan renovering och rivning och nybyggnation.

Public buildings require extensive adaptation to the activities in the building. The largest proportion of Swedish public buildings were built before 1980 and need maintenance or adaptation to today's needs and expectations. The energy performance is generally low and improving energy efficiency is central. Many Swedish managers of public buildings therefore ask themselves the question of whether it is better to renovate or to demolish these buildings and build new ones instead. The choice between energy renovation and demolition and new construction means that aspects that differ in the two approaches must be compared. This research project has addressed this by studying life cycle costs for parts of buildings that affect the energy balance using life cycle cost optimization. In addition to this, the values that are perceived to be achieved from renovation versus demolition and new construction have been studied with the help of qualitative in-depth interviews and surveys with managers of schools and preschools in Swedish municipalities. 

Investment costs and life cycle costs are lower for energy renovation compared to demolition and new building construction if the building body is not damaged. However, demolition and new construction is perceived as a cost-effective approach. This alternative entails important indirect benefits, such as efficient operation, good adaptation to operation, good indoor environment, and suitability for the building's purpose. To some extent these values can also be achieved during a renovation. Indoor environmental problems and lack of capacity are important drivers for addressing schools and preschools. These aspects can in some cases be difficult to handle with renovation. Renovation is, however, the most common approach in Swedish schools and preschools that needs to be addressed, and demolition and new construction is only seen as an alternative if the building is in such poor condition that it cannot be fixed with renovation. Renovation has a shorter lead time and can in some cases mean that the evacuation of operation is less complicated, compared to demolition and new construction.

To some extent, the choice depends on the context in the municipality. Different municipalities have different conditions and different problems regarding their building stock. The study presents a matrix with values that can be achieved during renovation versus demolition and new construction, to provide a basis for assessing which choice is appropriate. More research on the assessment of the building's condition and what values are missing in the existing building is urged, to provide a better basis for the choice between renovation and demolition and new construction.

Building energy simulation (BES) models rely on a variety of different input data, and the more accurate the input data are, the more accurate the model will be in predicting energy use. The objective of this paper is to show a method for obtaining higher accuracy in building energy simulations of existing buildings by combining time diaries with data from logged measurements, and also to show that more variety is needed in template values of user input data in different kinds of buildings. The case studied in this article is a retirement home in Linköping, Sweden. Results from time diaries and interviews were combined with logged measurements of electricity, temperature, and CO2 levels to create detailed occupant behavior schedules for use in BES models. Two BES models were compared, one with highly detailed schedules of occupancy, electricity use, and airing, and one using standardized input data of occupant behavior. The largest differences between the models could be seen in energy losses due to airing and in household electricity use, where the one with standardized user input data had a higher amount of electricity use and less losses due to airing of 39% and 99%, respectively. Time diaries and interviews, together with logged measurements, can be great tools to detect behavior that affects energy use in buildings. They can also be used to create detailed schedules and behavioral models, and to help develop standardized user input data for more types of buildings. This will help improve the accuracy of BES models so the energy efficiency gap can be reduced.

People spend a significant part of their time in an indoor environment, whether at home, school or workplace. The aim of this paper is to experimentally study the ventilation effectiveness (mean age of air, MAA) and thermal comfort (PMV and PPD) of three different ventilation supply devices, i.e., mixing supply device (MSD), displacement supply device (DSD) and wall confluent jet supply device (WCJSD) in an office room.

This paper is based on analysis from full-scale measurements performed in a laboratory at University of Gävle. The size of the room corresponds to a typical office module for one person. The test room has dimensions of 4.2 x 3.0 x 2.4 m with a volume of 31.24 m³, with the size of the room corresponding to a typical office. Different heat sources are used to simulate the office environment, which corresponds to 31.75 W/m².

The PMV and PPD are comparable to MSD, WCJSD and DSD as it turns out that MSD has poorer comfort than DSD and WCJSD. DSD and WCJSD have more or less the same thermal comfort performance. When comparing the local mean age of air (MAA) for the studied supply devices, the air is significantly much younger for the DSD and WCJSD than for MSD.