Temperature Set Point Research Articles

Real‐Time Model Predictive Control of Air‐Conditioners Through IoT—Results From an Experimental Setup in a Tropical Climate

ABSTRACTThere is an increasing demand for air‐conditioners (ACs) to maintain a comfortable indoor environment for all types and sizes of buildings including commercial, industrial, and office spaces. Such ACs are mostly operated by traditional ON–OFF controllers to maintain a temperature setpoint. Extensive control engineering knowledge resulting from experiments on actual buildings is needed before the wide application of an advanced control methods, such as model predictive control (MPC), which are more effective and energy‐efficient than the traditional controllers. Simulation studies on the application of control may provide promising results, but the corresponding experimental validations may prove otherwise. User‐friendly experimental setups to investigate the performance of real‐time advanced control on an actual building and its HVAC system is scarce. This paper details the design, implementation and testing of a user‐friendly, remote and autonomous test bed to acquire measured data through an IoT platform, and to control ACs in real time through MATLAB Thingspeak. Measurement and data acquisition equipment are installed in a two‐zone concrete building in Mauritius. MPC of the indoor air temperature achieved an AC temperature setpoint tracking RMSE which was 0.7°C lower than that achieved by the built‐in ON/OFF AC control. The test bed also revealed that portable air‐conditioners are not very efficient, given that the maximum cooling efficiency achieved in this work was only 60%. It also provided valuable insights based on the experiments carried out, in terms of improvements to sensing and data acquisition. Control engineers can implement such a test bed for the development and application of advanced controllers as per their needs and applications.

Experimental and computational assessment of an energy-saving innovation in a customised testing cabin

The aim of this paper is to assess the performance of an energy-saving device, called ‘Thermocill’ in a customised test cabin, located in a controlled environment. With the UK domestic energy sector responsible for nearly 27 % of the total energy mix in 2022, and massive increases in the cost of energy on homeowners and tenants, simple and low-cost retrofit measures could potentially be of great value, if they prove to be effective at saving energy. The paper describes the experimental and computational methods in detail with the goal of setting an important example/standard for the assessment of similar energy-saving innovations under the UK Standard Assessment Procedure (SAP). This, in turn, would enable the performance of such innovations to be captured in the Energy Performance Certificates (EPCs) for Building Regulation compliance. On that basis, a test cabin was constructed at Salford Energy house 2.0 to investigate Thermocill’s impacts on energy consumption and loss within the cabin. The experimental procedure is subsequently compared against a series of Computational Fluid Dynamics (CFD) simulations conducted for a larger number of scenarios. The performance of Thermocill was explored at different room temperature setpoints (16, 21, and 24 °C), window types (air and argon-filled double-glazed), and with/without blinds. The results were presented for four main scenarios including ‘cabin without Thermocill/blind’, ‘cabin with blind’, ‘cabin with Thermocill’, and ‘cabin with blind/Thermocill’. The results were presented in the form of U-values and heat losses for the windows, while additional results were provided from CFD simulations. A good correlation between the experiments and the CFD was found, showing confidence in both methods. Findings demonstrated that, when Thermocill is in operation, it reduces the average U-value by around 3–4 %, which is considered a significant payback for a passive and economical measure. The methodology presented in this paper is expected to set an important example/standard for the assessment of similar energy-saving innovations under UK SAP. This, in turn, would enable the performance of such innovations to be captured in the EPCs for Building Regulation compliance.

Warm, moderate, or cool-liker? A benchmarking framework to characterize occupant overall thermal preferences based on large-scale thermostat data

Humans could exhibit distinct overall thermal preferences when exposed to identical indoor thermal environments, leading to preference groups such as "warm-likers" or "cool-likers", who consistently prefer warmer or cooler conditions than the average population, respectively. Currently, most thermal comfort modelling studies focus on capturing the instantaneous comfort states/preferences of occupants, while overlooking their overall thermal preferences. This paper proposes a benchmarking framework to identify and characterize overall thermal preferences based on the relationship between preferred setpoints and outdoor air temperatures, derived from the ECOBEE Donate Your Data program. Using descriptive statistics, we establish three temporally consistent overall preference groups, including warm-liker, moderate and cool-liker, along with a temporally chaotic preference group termed random. Our results demonstrate that warm-likers prefer temperature setpoints above 21.5 °C on heating days and 24–25 °C on cooling days, while cool-likers prefer setpoints below 19.6 °C on heating days and 22 °C on cooling days, indicating a significant impact of the seasonal transitions. We observed that around 50 % of users exhibit secondary overall preferences, implying that overall thermal preference could change over time. On average, overall thermal preference can be established in 10–16 setpoint adjustments. The study reveals varied responses to outdoor temperature changes among users: many maintain constant indoor temperature preferences, while a significant number adjust their indoor temperatures upwards by 0.1 °C–0.4 °C for each 1 °C rise in outdoor temperature. A smaller group prefers cooler indoor temperatures as it gets warmer outside, showing a unique negative adjustment trend of −0.1. We also found that climate interacts with the overall preference group, with warmer climates having more warm-likers and vice versa.

Flexible emulation of the climate warming cooling feedback to globally assess the maladaptation implications of future air conditioning use

Abstract Rising affluence and a warming climate mean that the demand for air conditioning (AC) is rising rapidly, as society adapts to climate extremes. Here we present findings from a new methodological framework to flexibly couple and emulate these growing demands into a global integrated assessment model (IAM), subsequently representing the positive feedbacks between rising temperatures, growth in cooling demand, and carbon emissions. In assessing global and regional climate change impacts on cooling energy demand, the emulator incorporates climate model uncertainties and can explore behavioural and adaptation-related assumptions on setpoint temperature and access to cooling. It is also agnostic to the emissions and climate warming trajectory, enabling the IAM to run new policy-relevant scenarios (Current Policies, 2 °C and 1.5 °C) with climate impacts that do not follow Representative Concentration Pathways. We find that climate model uncertainty has a significant effect, more than doubling the increase in electricity demand, when comparing the 95th percentile cases to the median of the climate model ensemble. Residential AC cooling energy demands are expected to increase by 150% by 2050 whilst providing universal access to AC would result in the order of a 400% increase. Depending on the region, under current policies and limited mitigation, climate change could bring in the order of 10%–20% higher cooling-related electricity demands by 2050, and approximately 50% by 2100. Set point temperature has an important moderating role—increasing internal set-point from 23 °C to 26 °C, approximately halves the growth in electricity demand, for the majority of scenarios and regions. This effect is so strong that the change in set point temperature to both residential and commercial sectors outweighs the growth in demand that would occur by providing universal access to AC by 2050 to the 40% of the global population who would otherwise not afford it.

Steady-state and dynamic simulation of gas phase polyethylene process

Gas-phase polyethylene (PE) processes are among the most important methods for PE production. A deeper understanding of the process characteristics and dynamic behavior, such as properties of PE and reactor stability, holds substantial interest for both academic researchers and industries. In this study, both steady-state and dynamic models for a gas-phase polyethylene process are established as a simulation platform, which can be used to study a variety of operation tasks for commercial solution polyethylene processes, such as new product development, process control and real-time optimization. The copolymerization kinetic parameters are fitted by industrial data. Additionally, a multi-reactor series model is developed to characterize the temperature distribution within the fluidized bed reactor. The accuracy in predicting melt index and density of the polymer, and the dynamic behavior of the developed models are verified by real plant data. Moreover, the dynamic simulation platform is applied to compare four practical control schemes for reactor temperature by a series of simulation experiments, since temperature control is important in industrial production. The results reveal that all four schemes effectively track the setpoint temperature. However, only the demineralized water temperature cascade control demonstrates excellent performance in handling disturbances from both the recycle gas subsystem and the heat exchange subsystem.

Investigating the influence of uncertainty on office building energy simulation through occupant-centric control and thermal comfort integration

Buildings with occupant-centric control (OCC) systems can adjust heating, ventilation, and air conditioning (HVAC) operations based on occupant status to minimize unnecessary energy use. However, because occupant behavior is stochastic rather than constant, and preferred setpoints can vary across occupant groups, this randomness significantly impacts energy use in buildings with OCC systems.This study used a stochastic simulation approach to model the uncertainty inherent in occupancy patterns and evaluate its impact on the energy consumption of an office building with OCC. In this case, the setpoint temperature was determined based on the Predicted Mean Vote (PMV) method so that each zone could be controlled to the preferred temperature according to the occupant group.The results showed that the uncertainty of the annualized sum of electricity consumption for heating and cooling was 4.3 % and 1.8 %, respectively, with 95 % confidence intervals. Notably, a negative correlation was observed between the number of occupants and the uncertainty of energy consumption. Thus, as the uncertainty in the setpoint temperature increased during periods of low occupancy, the uncertainty in the energy consumption of the HVAC system also tended to increase. These insights underscore the significant influence of occupancy-related factors on building energy utilization.

An experimental study on the effect of room setpoint temperature, and evaporator/condenser fouling on performance of a ductless split type air conditioner

Ductless splits can have several advantages over conventional systems including energy saving, improved thermal comfort, and performance. A deep understanding of the effect of changes in operating conditions of the unit is required to estimate the energy saving in the field. In this paper, a reference guide is created to classify the effects of different parameters on the performance of the ductless split unit. The experiments are categorized into three main topics: 1- The effect of setpoint temperature on the performance and energy consumption, 2- The effect of evaporator fouling on energy consumption, and 3- The effect of condenser fouling on energy consumption of a ductless split unit. Results show that one degree Celsius increment in room setpoint temperature reduces power consumption approximately 57 W and in annually energy consumption about 279 kWh. Furthermore, covering 30 % of the evaporator coil surface area and comparing with the normal case (evaporator coil with no coverage), parameters of Energy Efficiency Ratio, energy consumption, and cooling capacity drops 13.5 %, 6.4 % and 19.1 %, respectively. Likewise, by covering 1/3 of the condenser coil surface area and comparing with the normal case, Energy Efficiency Ratio, and cooling capacity drops 9.8 % and 2.4 %, respectively. The mentioned data indicate that the effect of the evaporator dirtiness on reducing the cooling load of the device is much higher than that of condenser.

Polyurethane/Carbon Nanotube-Based ThermoSense Electronic Skin: Perception to Decision Making Aided by Internet of Things Brain.

Human skin has several receptors collaborating with the brain to provide appropriate "decisions" when applying stimuli. Several research articles state that biomimetic electronic skin (e-skin) is reportedly used for sensor-related applications and performs similarly to natural skin. However, research reporting the capability of the e-skin to make decisions and therefore react upon exposure to adverse conditions is still in its nascent stage. Herein, we report the development of an e-skin, ThermoSense, that can thermoregulate by making appropriate decisions. Thermoplastic polyurethane and multiwalled carbon nanotubes were used as the model composite. The heating and sensing capabilities of the optimized e-skin were studied in detail. In the study window, the e-skin demonstrated excellent electrothermal conversion efficiency by generating a temperature of 192 °C, consuming a power of 2.23 W. A finite element modeling (FEM) was adopted to determine the distribution of the filler in the case of the optimized e-skin and thus was used to probe the reason for the heating across the e-skin via mapping of the internal energy across the sample. FEM results and experimental findings are in strong agreement. Additionally, the e-skin demonstrated its capability to act as a thermal sensor with a 0.947% °C-1 sensitivity. To integrate the decision-making capabilities of the e-skin, an Internet of Things (IoT) brain console was made using the e-skin and electronic chips by leveraging More than Moore's concept. The IoT brain was automated with decision-making programming that was controllable via an in-house-developed mobile application. The console worked exclusively under simulated conditions. When there was a shift from the set point temperature, it started to heat. Postusage, the e-skin matrix was recycled, and the recycled e-skin demonstrated a marginal decrement in performance attributes. This study opens new avenues for developing decision-making e-skins for next-generation human-machine interphases.

PCM as an energy flexibility asset: How design and operation can be optimized for heating in residential buildings?

In cold climates, residential buildings are often well-insulated to reduce heating costs but may lead to overheating. Incorporating Phase Change Material (PCM) into building envelope can serve as an effective measure to mitigate overheating and reduce cooling costs. However, the inappropriate incorporation of PCM in well-insulated building envelope might negatively affect the heating energy flexibility. Therefore, this paper explores the effectiveness of PCM in reducing heating costs by optimizing the PCM design and heating operation. The main objectives are to (i) quantify the performance of PCM in terms of overheating and cost savings, aligned with the recently introduced Time-of-Use (ToU) tariff and Spot pricing, (ii) identify the optimal design of PCM-incorporated building envelope, and (iii) apply a smart control with resetting temperature setpoints in-line with EN-ISO 52120-1 Standard. A multi-stage optimization process has been designed. It first identifies the optimal properties (i.e., melting temperature), position, and thickness of PCM. Secondly, it optimizes the profile of temperature setpoints, considering the seasonal thermal behavior of PCM. Co-simulation platform between IDA ICE 5.0 and Python 3.8 optimization engine is created for the heating control optimization. Results showed that PCM is more effective when incorporated into the interiors of external walls rather than in roofs. The optimal PCM design for Nordic buildings, featuring 75 mm-thick PCM with a melting temperature of 21 °C positioned within walls’ interior, has a varied impact on monthly energy savings across seasons, with a negative effect in spring and a significant positive effect in autumn. After the multi-stage optimization, the optimal scenario enables to achieve a maximum annual cost savings of 6.5 % with ToU tariff and 21.0 % with Spot pricing, while also eliminating overheating.

Competition between insulation and phase change material to intensify the resilience of envelope against heat exchange to reduce overall energy consumption in buildings

ABSTRACT In this study, the effectiveness of two techniques was investigated to reduce annual building energy demand (ABED) located in hot and desert climates. In the first technique, thermal insulation was used to boost the thermal resistance of the envelopes, and in the second one, bio-based phase change material ( BioPC M R M 27 ) was used. Using numerical methods for five hot and desert regions, the effect of some parameters such as setpoint temperature, installation location, and thermal properties of insulation/PCM on the effectiveness of both techniques were investigated. By installing PCM in the middle layer of the walls, it was found that in 90% of the cases, the first technique had better effectiveness than the second technique in reducing ABED. To enhance PCM efficiency relative to insulation, three approaches were explored: increasing thickness, altering thermal properties, and optimizing installation location. Based on the results, the first two approaches did not yield substantial enhancements in PCM efficacy compared to insulation. The location of PCM installation is very effective in its effectiveness. By installing PCM in different places, it was observed that the presence of PCM in the outermost layer maximizes its effectiveness. In this case, the second technique is more efficient than the first one by 23.63% to 40.4% depending on the climate zone weather.

Comparative analysis of proportional, proportional–integral, and proportional–integral–derivative controllers for thermal regulation in a cylindrical cooling system with multiple O-Ring heat sources

This study is intended to determine the thermal management capability of different closed-loop controllers inside a cylindrical three-dimensional cooling system with multiple O-Ring type heat sources. The motivation for this research stems from the need for efficient thermal regulation in advanced cooling systems, which is critical for applications ranging from electronics cooling to industrial processes. The uniqueness of this study lies in its comprehensive evaluation of different controllers such as proportional (P), proportional–integral (PI), and proportional–integral–derivative within a geometrically complex cooling environment using a novel trial-and-error approach for tuning controller parameters. The observational domain is a hollow cylinder, and the four discrete heat sources are placed at regular intervals along the cylinder's longitudinal axis, with all the remaining walls insulated. At the center of the system is a temperature probe that measures and provides feedback to the control module to continuously compare it to a pre-specified setpoint temperature. The flowing fluid, air, enters through the semi-circular inlet at one end, whose velocity is controlled by a controller response, and is discharged through the semi-circular outlet at the other end at atmospheric conditions. This study uses the Galerkin finite element method, using proper initial and boundary conditions to solve the governing equations, namely, the Navier–Stokes and heat energy equations. We analyze the time-dependent behaviors of the cooling system by measuring controller responses such as overshoot, rise time, oscillation, steady-state error, and settling time. Additionally, the impacts of the Reynolds number (Re), Richardson number (Ri), and Grashof number (Gr) on the overall mean Nusselt number over time are observed to understand the influence of flow regulation due to the controllers' actions. This comprehensive analysis provides insights into the controllers' inlet flow control based on the set temperature at the probe's center location. A unique trial-and-error approach for selecting Kp and Ki values, which is crucial for controller analysis, is also presented. Based on the results, it can be inferred that increasing the Kp value from 0.003 to 0.010 ms−1 K−1 reduces the steady-state error from 40.8% to 13.97%. For a Ki value of 0.006 ms−2 K−1, the PI controller achieves a zero steady-state error with faster settling at 3.29 s, along with an overshoot of approximately 80.51%. Conversely, a lower Kd value of about 0.0001 mK−1 results in a reduction in the settling time and overshoot compared to the PI controller, while a higher Kd value ensures optimum stability with a higher settling time and a stable Nusselt number of 1.93. This trial-and-error approach to parameter tuning provides valuable insights into the design of controlled environments and the effective management of thermal conditions in various thermo-fluidic applications.

Multi-objectives occupant-centric control of thermostats and natural ventilation systems in cold climate conditions using real-time occupant-related information

Recently, Occupant-Centric Controls (OCCs) have attracted great attention. Many studies have applied OCCs to mechanical ventilation systems, while natural ventilation systems have gathered much less attention. The natural ventilation effect, driven by opening windows or vents, can be effective in improving indoor air quality, however, result in a leakage of interior heating energy in winter in cold climates. Therefore, the controls of thermostats and natural ventilation systems shall be designed well so that satisfying levels of thermal comfort, air quality and energy conservation can be simultaneously guaranteed. This study proposes an OCC and applies it to thermostats and natural ventilation systems for indoor thermal comfort, air quality and heating energy management. The strategy comprises three controllers: occupancy-based on-off controller, controller of setpoint of indoor air temperature and window openness controller. First, real-time profiles of heat gains from occupants and window openness were collected by employing vision-based detection. Second, a parametric building simulation study was conducted, and then simulation data were generated to develop predictive shallow artificial neural networks for forecasting the indoor conditions and energy performance of the investigated room. Third, the performance of the proposed strategy was examined. Compared to the baselines, the control could offer a decrease in building heating loads by between 43.4% and 63.8 % and an improvement of predicted mean vote levels by 0.36–0.37. The proposed OCC could also maintain indoor CO2 concentrations below 1000 ppm for about 91 % of the studied time, while 84.2 % of the time with several peaks over 3000 ppm in the baseline cases.

Infrared signal-based implementation of model-based predictive control (MPC) for cost saving in a campus building

Model-based predictive control (MPC) is an advanced control method that is used to achieve energy and cost savings in building energy management. However, there are various challenges to implementing MPC in actual buildings, such as additional engineering costs, physical damage to systems, and security concerns. This study proposes a non-intrusive implementation method for MPC based on a low-cost communication system. Firstly, a grey-box building model was developed along with the heating, ventilation, and air conditioning (HVAC) models based on the actual measurements of the test building. A simulation case study of MPC was performed, along with baseline feedback control, using these constructed models. The MPC outperformed the feedback control in terms of comfort, electricity consumption, and cost. It was implemented in an actual test zone to demonstrate the feasibility of a low-cost and non-intrusive implementation method that was realized using Arduino-based infrared signal communication and to evaluate the cost-saving potential of the MPC when compared with the baseline control. This experiment was conducted under a confined schedule for occupancy and set-point temperature for three days for the MPC and two days for the baseline feedback control in the cooling season. The cost savings of the MPC are as high as 5.8 %. Additional feedback cases were considered with a non-confined occupancy schedule and set-point temperature. The resulting energy consumption and cost savings are 25.2 % and 33.7 %, respectively. In this study, the applicability of the Arduino-based low-cost and non-intrusive implementation method for MPC was demonstrated, and the actual saving percentage of the MPC was compared with the conventional control method in a real building.

Integrated demand response method for heating multiple rooms based on fuzzy logic considering dynamic price

We consider an educational building heated by a combination of district heating (DH) and a local air source heat pump. We have developed an integrated demand response method for multiple rooms, consisting of an optimization layer and a control layer, to maintain thermal comfort and save energy and costs. For the optimization layer, we apply fuzzy logic to adjust indoor temperature setpoints to respond to dynamic heat prices and propose an optimal heat supply method to find optimal heat supply schemes. For the control layer, a multi-objective model predictive control (MPC) has been developed to manage indoor thermal conditions across multiple rooms. To test and verify the integrated demand response method, we build a multi-room simulation model using the CARNOT Toolbox. The results show that adopting different indoor temperature setpoints during working and nonworking hours, combined with the MPC method, has an energy-saving potential of 9.1 % compared to maintaining a constant indoor temperature using DH alone. Adjusting temperature setpoints using fuzzy logic utilizes the building's heat storage capacity to increase energy flexibility, reaching 16.0 % savings in energy and reducing 12.6 % heating costs.

Rancang Bangun Automatic Electric Oil Heater Sebagai Pengganti Thermal Oil Boiler Berbasis IoT Pada Kapal Bulk Carrier

From this study, the automatic electric oil heater can be used to adjust the temperature value and the automatic electric heater will be able to turn off automatically according to the setpoint temperature value determined through a smartphone device or IoT program. Monitoring can also be done with the app, as well as being able to view temperature values directly through the LCD. This tool is in the form of an electric heater that will be used to heat ship fuel automatically and is more practical and efficient. It is also easier to maintain than a boiler on a ship. The design of this tool is based on accurate calculation of temperature values, with which the process of heating up fuel becomes faster. From the results of this study, a heat sensor that can read the temperature value and the buzzer will sound and the device will automatically turn off if the temperature has reached a specified setpoint. This research was carried out when the ship was about to make a departure to find out the temperature in the heating of the fuel on the ship. Testing Design of an automatic electric oil heater as a replacement for IoT-based thermal oil boiler on this bulk carrier ship, it can be known the disadvantages and advantages of this tool, testing can be done by putting oil into the electric heater, then in a short time the oil will heat up quickly, and the tool will be able to turn off automatically and the buzzer will immediately turn on when the heat has reached the specified temperature. In the temperature setting, it can be set in a smartphone or an app that can adjust the temperature and turn off the appliance from a considerable distance. However, the application must use the internet network and cannot be accessed locally, the use of IoT requires devices and smartphones to be connected to the internet.

Definition of a PVT coupled water source heat pump system through optimization of individual components

Exploiting renewable resources considering their discontinuity compared to building needs, necessitates energy system designs that simultaneously maximize generation and storage performance in different seasons. This article presents the optimization of RESHeat European project, concerning a high-performance system which combines water-source heat pump, cooled photovoltaic panels and thermal storage. The research regards the Italian demo site, near Rome, to define a solution for Mediterranean regions which alongside the requirement for heating have notable need for summer cooling. The targets are system's efficiency, with a minimum sCOP of 5, and a minimum 70 % coverage from renewable sources focusing ambient temperature management.A dynamic model of plant and building was used for parametric analysis, which covered separately heating and cooling modes, involving significant parameters: operating temperatures of the heat pump, number of strings comprising the photovoltaic array, volume of the buffer tank connecting PVTs and WSHP and setpoint temperature of a cooler added for tank temperature control in cooling. 184 alternative configurations were evaluated by Multi-Criteria Decision Making (MCDM) method based on energy, economic and logistic criteria, and weighted by five indices. The optimal system includes 15 PVT panels strings for 25 kWp, a 3 m³ storage tank and cooling setpoint temperature of 25 °C.

Calibrating cryogenic temperature of TEM specimens using EELS

Cryogenic Scanning/Transmission Electron Microscopy has been established as a leading method to image sensitive biological samples and is now becoming a powerful tool to understand materials' behavior at low temperatures. However, achieving precise local temperature calibration at low temperatures remains a challenge, which is especially crucial for studying phase transitions and emergent physical properties in quantum materials. In this study, we employ electron energy loss spectroscopy (EELS) to measure local cryogenic specimen temperatures. We use the temperature-dependent characteristics of aluminum's bulk plasmon peak in EEL spectra, which shifts due to changes in electron density caused by thermal expansion and contraction. We successfully demonstrate the versatility of this method by calibrating different liquid nitrogen cooling holders in various microscopes, regardless of whether a monochromated or non-monochromated electron beam is used. Temperature discrepancies between the actual temperature and the setpoint temperatures are identified across a range from room temperature to 100 K. This work demonstrates the importance of temperature calibrations at intermediate temperatures and presents a straightforward, robust method for calibrating local temperatures of cryogenically-cooled specimens in electron microscopes.

NK1 receptor mediates cerebral cellular and extracellular morphological changes during the LPS-induced febrile response

Fever elicited by bacterial lypopolyssacharide (LPS) is mediated by pro-inflammatory cytokines, which activate central mediators and regulate the hypothalamic temperature setpoint. This response is often accompanied by morphological changes involving the extracellular matrix, neurons and glial cells, with significant health impacts. The NK1 receptor is involved in the febrile response induced by LPS but its effects over the extracellular matrix in the context of neuroinflammation remain unknown. The present work aims to clarify the extracellular changes associated with NK1 signaling in LPS-induced fever. Male Wistar rats were exposed to LPS intraperitoneally. Experimental groups were pre-treated intracerebroventricularly with the NK1 selective inhibitor SR140333B or saline. Histological changes involving the brain extracellular matrix were evaluated using hematoxylin and eosin, Mason’s trichrome, picrosirius, alcian blue, periodic acid Schiff’s stains. The expression of matrix metalloproteinase 9 (MMP9) was studied using confocal microscopy. Fever was accompanied by edema, perivascular lymphoplamacytic and neutrophylic infiltration, spongiosis and MMP9 overexpression. SR140333B significantly reduced LPS-induced fever (p < 0.0001), MMP9 overexpression (p < 0.01) and associated histological changes. These results contribute to characterize cerebral extracellular matrix changes associated with LPS-induced fever. Overall, the present work supports a role for NK1 receptor in these neuroinflammatory changes, involving MMP9 overexpression, edema and leukocytic infiltration.

Investigating enhanced thermal comfort and energy efficiency through strategized airflow in Micro-Zonal Occupant-Centric Control (MZOCC)

The potential of Micro-Zonal Occupant Centric Control (MZOCC) to save HVAC energy consumption in medium sized open-plan offices has been established in literature. This is done by virtually dividing a thermal zone into micro-zones and allowing independent diffuser-level control in each micro-zone when the micro-zone is occupied. In continuation, there is a need to ensure that thermal comfort is achieved within micro-zones under such localised control. This is important because several forms of discomfort such as draft, horizontal thermal asymmetry and vertical thermal gradients may arise in MZOCC. Further, the effect of MZOCC airflow control strategies, such as setback flow and setback temperature, which were proposed in previous studies on thermal comfort of occupants needs to be evaluated. In an attempt to address these research gaps, this study explores thermal comfort for different scenarios of diffuser arrangements, airflow control strategies and occupancy conditions and also explores the effect of varying supply velocities used in setback flow and setpoint temperatures used as setback temperatures on air distribution and thermal comfort.Results show that low PMV values, increased draft discomfort and heavy thermal gradients are observed for certain scenarios of MZOCC. Tuning airflow control by choosing appropriate setback flow or setback temperature helps in restoring thermal comfort. As different forms of discomfort are observed in different cases, it is important to plan micro-zones and control airflow, such that, MZOCC does not violate thermal comfort criteria while optimising energy efficiency. This study gives a framework for selecting appropriate airflow control strategies for a selected diffuser arrangement for a given occupancy condition. Comfort-based MZOCC that uses appropriate airflow control strategy saves about 60% energy when the zone is half occupied and about 85% energy when the zone is quarter occupied. Results also show that, improving the diffuser arrangement improves energy savings and increases the options of airflow control strategies that can be used. Also, different airflow control strategies behave differently for each diffuser arrangement and has to be chosen separately for given diffuser setting and occupancy condition.

Numerical simulation of thermal performance of heat sink augmented with phase change material PCM integrated with solid and aluminum metal foam fins

AbstractThis study introduced a novel numerical modeling for the evaluation of a hybrid heat sink design by replacing the solid fins with aluminum foam fins (AFF) for the same thickness of 2 mm within a phase change material (PCM). This innovation is designed to enhance thermal performance in electronic cooling applications. Heat fluxes of 2, 3, and 4 kW/m2 were applied to the base. The performance has been verified at set point temperatures (SPT) of 60°C, 70°C, and 80°C, encompassing a range relevant to various applications. Different AFF thicknesses (4 and 6 mm) and foam porosities (0.85, 0.90, and 0.95) were investigated. The study demonstrated that AFFs improve heat transfer by increasing fin surface area and by effectively raising the thermal conductivity of the PCM. Compared to the SF heat sink, the results show that the AFF design extended the operational time by 5%–8% for the range of heat fluxes. Notably, AFFs with a thickness of 6 mm achieved a significant 41% improvement in the operation time at a lower SPT (60°C). The metal foam porosity of ε = 0.85 exhibited superior thermal performance within the investigated temperature range. This research paves the way for optimizing hybrid heat sink designs using metal foam for efficient thermal management and reduction of weight.