This study experimentally evaluated the performance of a wall confluent jet (WCJ) cooling system in a greenhouse under real summer and autumn weather conditions. It examined the effects of indoor air temperature setpoint (Tspt), number of nozzle rows (n) on the WCJ diffuser, and external wall shading on WCJ’s cooling performance. Thermocouples and constant-current anemometers measured air and surface temperatures and air velocity, while pyranometers measured solar radiation. The WCJ system dynamically regulated inlet air temperature between 14 °C and 25 °C to counter solar and conductive heat gains, maintaining indoor air temperature within ±1.5 °C of the setpoint. Increasing Tspt by 4 °C reduced inlet cooling demand by 25% but increased indoor air temperature by 20–25% and raised ceiling, wall, and floor surface temperatures by 17%, 20%, and 16%, respectively. Increasing n reduced surface temperatures by up to 8% and indoor air temperature by 6%. External wall shading reduced solar heat gain, lowering interior surface temperatures by 10–30%, peak and mean indoor air temperatures by up to 35% and 15%, and net power peaks by 40%. Autumn conditions reduced cooling loads by 50% relative to summer. Overall, WCJ cooling demonstrates strong potential as an alternative or complementary system for greenhouse thermal regulation without increasing primary energy demand.

Differential cooling is successfully used in automobile industry to obtain tailored mechanical properties along the thin-walled beams using tool or spray quenching. Thicker steel plates used for soil-working tools in agriculture require high hardness, and therefore, are hardened in water. However, differential cooling of such tools can improve their durability by creating hardness gradients suitable for the spatial variation of loadings that they are subject to. Therefore, the focus of this study is, using Impinging jet Quenching Technique (IJQT), to perform differential cooling of 15 mm steel plate with different water and air flow rates, thus generating a temporal and spatial temperature evolution data. This data is used for further simulations of phase transformations and final hardness gradient predictions in application to other steels using their chemical composition as an input parameter. The experiments resulted in a wide range of cooling rates of 1–43°Cs−1 along the steel plate, generated by different cooling strategies. The simulations showed different combinations of hardness levels along the sample of three simulated steels with different hardenability levels, demonstrating the potential of implementing the same approach for further studies of other steels in terms of their capability of providing necessary hardness gradients using IJQT.

Super duplex stainless steel (SDSS), known for its high corrosion resistance and mechanical properties, is widely used in applications in aggressive environments, such as marine and petrochemical industries. However, intermetallic precipitates may form during cooling from high temperatures, detrimentally affecting the steel's properties, especially its impact toughness. Since cooling after solution annealing is a key step in production to obtain a precipitation-free component, it is important to understand to what extent the cooling process can be optimized and adjusted in terms of cooling rates and their effect on the quality of steel. The aim of this study is to study the effect of cooling rate on the quality of SDSS. For this purpose, the Impinging Jet Quenching Technique (IJQT) was employed to perform continuous and controlled cooling of 80 mm diameter SDSS 2507 solid bars with water and air jets of different flow rates to cover a wide range of cooling rates. The bars were analyzed through microstructure analysis using a scanning electron microscope, hardness tests, impact toughness tests, and fracture surface observations using a stereo light microscope. The results showed a consistent decrease in impact toughness throughout the tests with decreasing cooling capacity, which facilitated the σ-phase precipitation. 

Differential cooling is widely used in the automotive industry to tailor the microstructure and the mechanical properties in thin-walled beams through tool or spray quenching. However, thicker steel plates, such as those used in soil-working agricultural tools, typically require high hardness and are conventionally quenched by immersion in water. While this ensures strength, it does not account for the spatial variation of mechanical loads that these tools experience in service. By implementing differential cooling, it is possible to engineer hardness gradients that optimize both wear resistance and structural integrity.

This study explores the use of Impinging Jet Quenching Technique (IJQT) to achieve differential cooling of 15 mm-thick carbon steel plates by employing different water and air jet flow rates. The cooling process was monitored using embedded thermocouples, generating spatial and temporal temperature evolution data, which was then utilized in finite element simulations to predict phase transformations and final hardness gradients. The simulation framework enables extrapolation to other steel grades, using their chemical composition as an input parameter to a machine learning tool for phase transformation data generation, making the methodology adaptable for various industrial applications.

The experimental trials produced a wide range of cooling rates (0–43 °C/s) along the steel plate, depending on the quenching strategy and cooling medium. The simulated phase transformations revealed distinct hardness distributions across three steel grades with different hardenability levels (0.26, 0.27, and 0.38 mass-% C). The results showed that higher-hardenability steels retained a greater proportion of martensite, whereas lower-hardenability steels exhibited increased bainite, ferrite, and pearlite fractions, particularly in the slower cooling regions. The results clearly show how different steels react on different cooling medium and flow rates in terms of hardness profile variations along a potential component. Furthermore, it was found that differential air cooling could, in some cases, replicate the effects of slower water quenching, providing an alternative method for controlled microstructure tailoring.

These findings highlight the potential of IJQT as a flexible and scalable approach for achieving site-specific material properties in thick steel components. The demonstrated simulative and experimental approach opens new possibilities for enhancing the durability of steel components exposed to variable mechanical loads, offering an efficient means to optimize hardness distributions through controlled cooling strategies.

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 (XH),  number of  nozzles (XN),  airflow rate  (XQ) and  supply temperature (XTS).  The  RSM was  used to  generate a  quad-ratic  equation for  the  response variables exhaust temperature (TE),  sup-ply  temperature (TP),  PMV, DR, eT and  ACE. The  RSM  shows that  the  TE, TP and PMV were independent of the number of nozzles. The proposed equations were used to  generate setpoints optimized for  thermal com-fort  (PMV) for  summer, spring and  winter cases with different CLO  fac-tors  and  different TS under a  scenario where the  heat load varied between 10-30W/m2.  TE was  used as  setpoint to  regulate the  airflow rate  to  keep the  PMV values close to  zero. The  results show that  by adapting the TS 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 TP 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 = 106%) and  with a  higher heat removal efficiency (eT = 110%) than conventional mixing ventilation

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.

Soil-working tools in agriculture are made of boron-containing steels with high wear resistance and hardenability. Nevertheless, these tools are subject to high impacts, abrasive wear, and fatigue and are therefore prone to failure. To combine varying levels of properties within one component in as-quenched condition can be beneficial for such products. To obtain this property variation, a component must undergo a complex and controllable cooling. Therefore, the aim of this work is to obtain a microstructure gradient along two 15 mm-thick steel plates in a newly developed test rig by water jet impingement technique to confirm its controllability and flexibility. Furthermore, a quenching simulation model is created for hardness prediction using phase transformation data from a machine learning tool. Microstructure variation is observed using light optical microscopy and the electron backscatter diffraction technique. Mechanical properties are studied through tensile tests and hardness measurements and are also compared with simulation results. The 0.27 mass% C steel sample is obtained in almost fully martensitic state transitioning to a softer ferritic/bainitic condition, while the 0.38 mass% C steel sample results predominantly into a fully hardened martensitic state and slightly shows ferritic and bainitic features along the sample. The quenching simulation model shows promising hardness prediction for both steels.

Insulating building envelopes is crucial for maintaining indoor thermal comfort, particularlyin large-space enclosures like greenhouses having transparent envelopes. Transparent envelopesallow natural light but challenge temperature regulation due to their low thermal mass and highU-values, which enable significant heat transfer between indoor and outdoor environments. This fieldstudy aims to experimentally investigate whether warm wall confluent jets (WCJs) can maintain therequired indoor climate conditions in a greenhouse exposed to dynamic meteorological conditions inwinter. It analyzed the impact of the airflow rate, number of nozzle rows, and room air temperaturesetpoint on WCJ heating performance on the ceiling, external wall, and room air. Measurementswere performed with thermocouples and constant current anemometers, and the response surfacemethodology evaluated the effect of design variables on WCJ flow, thermal behavior, and the indoorenvironment. The results show that WCJs provided recommended air velocities and temperaturesindoors, with the airflow rate having the strongest effect on flow and thermal behavior, while thenumber of nozzle rows had a moderate effect. This study developed response surface models relatedto room air temperature, ceiling surface temperature, external wall temperature, and supply airtemperature. Supply temperatures between 27 ◦C and 40 ◦C suggest using low-exergy heat sources,like industrial waste heat, to sustain greenhouse operations during winter.

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.

Hardening of carbon steel products by austenitization and immersion in a quenching medium is a widely used heat treatment to obtain a hard and strong martensitic structure. To avoid the undesired consequences, such as residual stresses or insufficient hardening depth, the cooling rates must be accurately measured and controlled. This can be achieved using the impinging water jet quenching technique. The aim of this work is to perform hardening of four low-alloyed 70 mm cylindrical carbon steel bars, using impinging water jet quenching technique with different jet flow rates, and to analyze its effect on thermal evolution and residual stresses. The temperature evolution during quenching experiments is recorded and used as input to a comprehensive quenching model to predict phase transformations, final hardness, and residual stresses of cylindrical bars. All four quenching experiments result in a fully hardened martensitic state. Furthermore, a decrease in jets’ flow rate, within a certain interval, results in different thermal histories and in lower compressive residual stresses on the surface. The results from quenching simulations show promising hardness, microstructure, and residual stress predictions that are validated by hardness measurements, optical microscopy, and residual stress analysis using X-Ray diffraction method.