Chilled Temperature Research Articles

Growth of food-borne pathogens Listeria and Salmonella and spore-forming Paenibacillus and Bacillus in commercial plant-based milk alternatives

The objective of the present study was to compare the growth of food-pathogens Listeria monocytogenes, Salmonella enterica, food spoilage Bacillus subtilis, an industrial milk product isolate, and spore-forming Paenibacillus in commercially available ultrahigh temperature processed (UHT) bovine milk and non-dairy, plant-based beverages (coconut, almond, cashew) stored at chilled and ambient temperatures (4 °C, 8 °C or 20 °C). Beverage samples were inoculated with a strain cocktail or individual strains of either Listeria or Salmonella, or Paenibacillus or Bacillus, respectively (approximately 1 × 103 CFU/mL). The findings indicate that the bacterial strains used in the study were capable of proliferating in plant-based beverages at higher rates than in bovine milk at 8 °C and 20 °C for Listeria and 20 °C for Salmonella and Paenibacillus, respectively. Bacillus subtilis grew equally fast in bovine milk and plant-based almond drink at 20 °C. No statistically significant difference (p > 0.05) in growth rates between different types of tested beverages was observed at 4 °C and at 8 °C for Listeria and Salmonella cocktails, respectively. These data suggest that plant-based beverages may present a significant risk for listeriosis and salmonellosis and post-opening recommendations should be carefully considered.

ANALYSING THE BEST QUALITY PARAMETER OF DIE-CASTING PRODUCTS

Die casting has revolutionized manufacturing technology by facilitating mass production while maintaining dimensional accuracy, stability, and strength. It has a broad array of applications in the automotive, lighting, industrial, and domestic sectors. The design parameters have a substantial impact on the quality of die castings. As a response, the aim of this research is set to look into the design characteristics of a hot chamber die-casting. The analysis was carried out using a hot chamber injection molding machine and ZAMAK 5 (Zinc: 96%, Al: 3.5%, and Cu: 0.5%) as the material. To determine the optimal quality parameters for a hot chamber die casting method, the injection speed, chilled water temperature, and cooling time were varied. The injection speeds were set to 4 ms-1, 5 ms-1, and 5 ms-1, respectively, while the chiller temperatures were set at 13°C, and 18°C. In addition, cooling times of 0.8s, 1.2s, 1.6s, and 2s were also recorded. The production analysis was further investigated for casting weights of 40g, 60g, 80g, and 100g. The cooling time was set to 2 seconds, 1.6 seconds, 1.2 seconds, and 0.8 seconds. Following the collection of data, we discovered and examined the most successful and cost-effective parameters for mass production, which offer promises for the industries.

Potential application of the haematology analyser XN-31 prototype for field malaria surveillance in Kenya

BackgroundSimple and accurate diagnosis is a key component of malaria control programmes. Microscopy is the current gold standard, however it requires extensive training and the results largely rely on the skill of the microscopists. Malaria rapid diagnostic tests (RDT) can be performed with minimal training and offer timely diagnosis, but results are not quantitative. Moreover, some Plasmodium falciparum parasites have evolved and can no longer be detected by existing RDT. Developed by the Sysmex Corporation, the XN-31 prototype (XN-31p) is an automated haematology analyser capable of detecting Plasmodium-infected erythrocytes and providing species differentiation and stage specific parasite counts in venous blood samples without any preparation in approximately one minute. However, factors such as stable electricity supply in a temperature-controlled room, cost of the instrument and its initial set-up, and need for proprietary reagents limit the utility of the XN-31p across rural settings. To overcome some of these limitations, a hub and spoke diagnosis model was designed, in which peripheral health facilities were linked to a central hospital where detection of Plasmodium infections by the XN-31p would take place. To explore the feasibility of this concept, the applicability of capillary blood samples with the XN-31p was evaluated with respect to the effect of sample storage time and temperature on the stability of results.MethodsPaired capillary and venous blood samples were collected from 169 malaria-suspected outpatients in Homa Bay County Referral Hospital, Kenya. Malaria infections were diagnosed with the XN-31p, microscopy, RDT, and PCR. Capillary blood samples were remeasured on the XN-31p after 24 h of storage at either room (15–25 °C) or chilled temperatures (2–8 °C).ResultsIdentical results in malaria diagnosis were observed between venous and capillary blood samples processed immediately after collection with the XN-31p. Relative to PCR, the sensitivity and specificity of the XN-31p with capillary blood samples were 0.857 and 1.000, respectively. Short-term storage of capillary blood samples at chilled temperatures had no adverse impact on parasitaemia and complete blood counts (CBC) measured by the XN-31p.ConclusionThese results demonstrate the potential of the XN-31p to improve routine malaria diagnosis across remote settings using a hub and spoke model.

Experimental study and performance analysis on a closed-cycle rotary dehumidification air conditioning system in deep underground spaces

High temperature and high humidity are challenges threatening human health in deep underground spaces. A rotary dehumidifying air conditioning system is an appealing way to solve this problem with free cooling and free heating from different depths of groundwater. A closed-cycle rotary dehumidification air conditioning system in deep underground spaces is proposed. The process and regeneration channels in this proposed system are merged into an optimal channel by recovering heat and harvesting water from the regenerated air. The effects of working conditions, such as the flow configuration of the chilled water, the chilled water supply temperature, the ambient air humidity and the regeneration temperature, on the energy and exergy performance are experimentally investigated. The recommended the flow configuration of the chilled water is 1:5:4. Under typical operating conditions (32 °C, 14 g kg −1 ), the moisture removal of the system driven by 80 °C hot air, reaches 4.9 kW, the thermodynamic coefficient is 1.1, and the exergy efficiency approaches 50.05%. This closed-cycle system with heat and water recovery improves the energy and exergy performance, which is an effective technology option for being applied in deep underground spaces.

Effect of fruit juices in skim milk extender in maintaining Sapudi ram spermatozoa quality at chilled temperature

This study aimed to determine the effect of the addition of cherry tomato, california papaya, and honey melon juice into skim milk extender in maintaining the quality of Sapudi ram semen at chilled temperature (5oC) storage. Five replication of ejaculates were divided equally into four groups. In control group (T0) semen was diluted in skim milk extender, while in T1, T2, and T3 groups semen were diluted in skim milk extender contained 20% of cherry tomato, california papaya, and honey melon juice, respectively. The extended semen was stored at a chilled temperature, and semen quality (based on sperm motility, viability, and plasma membrane integrity) was observed daily for five days. The result showed that semen quality declined day by day during the five days of storage. Based on the minimum standard of post-thawed semen motility (40%), the spermatozoa of the control group only lasted by the second day. Meanwhile, in the groups with the addition of fruit juice motility could last up to the third day, with the highest motility (p <0.05) on the addition of california papaya juice. This study concluded that the addition of 20% (v/v) california papaya juice in skim milk extender could maintain the percentage of spermatozoa motility up to three days at a chilled temperature.

North Eurasian thermal comfort indices dataset (NETCID): new gridded database for the biometeorological studies

Global climate changes give us the important task of obtaining information about the spatial distribution of bioclimatic comfort indicators at the global or continental level. One of the most applicable tools can be based on reanalysis data (meteorological gridded data with global coverage). This issue is fully relevant for the territory of Northern Eurasia with its diverse climates, rapid environmental changes, and often sparse network of in situ observations. In this paper, we present a conceptually new dataset for the most popular thermal comfort indices, namely heat index (HI), humidex (HUM), wind chill temperature, mean radiant temperature, physiologically equivalent temperature (PET) and Universal Thermal Comfort Index (UTCI) derived from ERA-Interim reanalysis hourly data for the territory of Northern Eurasia (the area limited by 40° N–80° N, 10° W–170° W). The dataset has horizontal resolution of 0.75° × 0.75° (up to 79 km), temporal resolution of 3 h, and covers the period from 1979 to 2018 (40 years), which corresponds to the standard of the World Meteorological Organization in determining the parameters of the modern climate. Time series of indices are supplemented with a set of 8092 pre-calculated statistical parameters characterizing climatology of the thermal stress conditions. We further present several examples of the North Eurasian Thermal Comfort Indices Dataset (NETCID) data application, including analysis of the spatial heterogeneity of thermal stress conditions, assessment of their changes and analysis of specific extreme events. Presented examples demonstrate a pronounced difference between considered indices and highlight the need of their accurate selection for applied tasks. In particular, for the whole study areas HI and HUM indices show much smaller thermal stress repeatability and weaker trends of its changes in comparison to PET and UTCI indices. NETCID is available for free download at https://doi.org/10.6084/m9.figshare.12629861.

Dynamic Calibration Method of Sensor Drift Fault in HVAC System Based on Bayesian Inference.

Sensor drift fault calibration is essential to maintain the operation of heating, ventilation and air conditioning systems (HVAC) in buildings. Bayesian inference (BI) is becoming more and more popular as a commonly used sensor fault calibration method. However, this method focused mainly on sensor bias fault, and it could be difficult to calibrate drift fault that changes with time. Therefore, a dynamic calibration method for sensor drift fault of HVAC systems based on BI is developed. Taking the drift fault calibration of the chilled water supply temperature sensor of the chiller as an example, the performance of the proposed dynamic calibration method is evaluated. Results show that the combination of the Exponentially Weighted Moving-Average (EWMA) method with high detection accuracy and the proposed BI dynamic calibration method can effectively improve the calibration accuracy of drift fault, and the Mean Absolute Percentage Error (MAPE) value between the calibrated and normal data is less than 5%.

Dynamics of microbiota in the imported beef primal cuts during storage at different chilled temperatures.

Primal cuts of Australian beef transported by sea were stored under different chilled temperatures (0, 2, and 4 °C) for 6 weeks in different packaging conditions (aerobic or anaerobic packaging). The number of microorganisms and the transition of the microbiota were investigated using culture methods and amplicon sequencing. After 6 weeks of storage, the beef tended to show a high total viable count under aerobic packaging conditions and a high lactic acid bacteria count under anaerobic packaging conditions. The result of amplicon sequencing analysis showed that different beef samples had different predominant bacterial groups. Moreover, at high storage temperatures, Serratia sp. having high putrefactive activity showed increased abundance, while at low storage temperatures, Lactobacillus sp. showed increased abundance. Thus, differences in the packaging conditions and distribution temperatures after import affect the number of bacteria and the type of microorganisms in the Australian beef primal cuts, which may affect their quality.

Deep reinforcement learning optimal control strategy for temperature setpoint real-time reset in multi-zone building HVAC system

Determining a proper trade-off between energy consumption and indoor thermal comfort is important for HVAC system control. Deep Q-learning (DQN) based multi-objective optimal control strategy is designed for temperature setpoint real-time reset to balance the energy consumption and indoor air temperature. In addition, this study develops an EnergyPlus-Python co-simulation testbed to evaluate DQN control strategy in a simulation environment. A case study experiment is conducted to evaluate the performance of DQN control strategy for real-time reset of supply air temperature and chilled supply water temperature setpoint in a multi-zone building VAV system. The developed EnergyPlus-Python co-simulation testbed is used to train and test the DQN control strategy for performance analysis. The applied DQN strategy leans to update control actions (i.e. temperature setpoint) through interaction with the simulation environment. Simulation results show that the DQN control strategy is effective in finding a proper trade-off between the energy consumption of HVAC system and indoor air temperature. Meanwhile, the DQN control strategy can find a proper temperature setpoint reset sequence in smaller training episodes, and the control actions can be stable after ten DQN training episodes. This study provides a preliminary direction of deep reinforcement learning control strategy for temperature setpoint real-time reset in multi-zone building HVAC systems.

Application of artificial intelligence (AI) control system on chiller plant at MTR station

Chillers account for up to 40% of total station energy consumption in the Hong Kong Mass Transit Railway (MTR) system. As part of green railway initiatives, a site trial was conducted to apply a fully automated AI system to control a chiller plant in order to optimise energy performance in real time while maintaining a level of passenger comfort that suits each station’s environment. Through the predictive power of the AI system, the plant power’s consumption and cooling demands can be forecasted based on actual chiller, station, and weather conditions, all of which vary over time. The optimal operational settings can then be determined using an optimisation model for real-time chiller plant control, including staging, sequencing, chilled water supply temperature set-point, etc. This paper presents the formulation of an AI system using data-driven machine learning models and numerical optimisation, and the comparison of the actual energy performance of the proposed system against rule-based control optimisation in a conventional building management system (BMS) through the site trial. The results revealed the proposed AI system achieves better energy efficiency with annual energy savings of approximately 8.7%.

Off-design performance of an organic Rankine-vapor compression cooling cycle using R1234ze(E)

In this study, a 264 kWth organic Rankine-vapor compression cycle (ORVC) was experimentally tested over a range of conditions to quantify the individual impact of off-design external conditions. The ORVC was designed to recover waste heat at 91°C, reject heat to a liquid condenser stream at 30°C, and produce chilled water at 7°C. The condenser heat rejection temperature was varied from 16.6°C to 32.6°C, the chilled water delivery temperature was varied between 2.1°C and 13.1°C, and the heat input temperature was varied from 91°C to 120°C. As the condenser heat rejection temperature decreased, the coefficient of performance (COP) of the ORVC improved from 0.558 at 30°C to 0.682 at 16.6°C, despite a reduction in compressor isentropic efficiency. Although the chilled water temperature variation had almost no impact on the organic Rankine cycle performance, the compressor efficiency decreased when the delivery temperature was below 7°C. At the highest chilled water temperature, 13.1°C, the COP of the ORVC was 0.643. Compressor stall was noted when the condenser heat rejection temperature was greater than 32.6°C and the chilled water delivery temperature was below 2.1°C. Increasing the driving heat source inlet temperature improved the COP of the ORVC and the thermal efficiency of the organic Rankine power cycle, while decreasing the efficiency of the compressor and the COP of vapor compression cycle. In addition, the integrated part load value of the system was determined through experimentation to be 0.682, which provides a realistic estimate of real-world performance.

Chilled Temperature Induced Unidirectional Sliding Characteristics of 2D Woven Carbon Fiber Composites

Chilled Temperature Induced Unidirectional Sliding Characteristics of 2D Woven Carbon Fiber Composites

Field study on cooling performance of a heat recovery ground source heat pump system coupled with thermally activated building systems (TABSs)

Both ground source heat pump and radiant system have attracted more and more attention as the examples of Low-exergy utilization to reduce energy consumption in buildings. This study emphasizes on the cooling performance of a real hybrid recovery ground source heat pump system coupled by thermally activated building systems (TABSs) in a residential district in a hot summer and cold winter region. Based on the recorded data in the building energy management system (BEMS) from 2018 to 2020, comprehensive analysis was carried out in the view of exergy. The COP and the exergy efficiency of the entire system can be up to 5.49 and 16%, respectively. The hybrid ground source system with cooling tower improved the operation performance as the condensate water temperature can be limited to below 40 °C. Nevertheless, the cooling tower was sensitive to the surrounding environment, and which caused more exergy destruction in operation. In addition, as the TABS cooling proportion went up the exergy efficiency of the cooling emission system increased as well as the building cooling load. However, the exergy product of the energy source system did not well match the demands in the end. The TABS and fresh air system simultaneously shared with the energy system whose chilled water temperature was 7–10 °C. The benefit of TABSs in low-exergy utilization cannot be taken. Thus, an energy system with multiple temperatures is recommended. The chilled water with higher temperature can be provided to TABS to improve the system exergy efficiency further; while the water with lower temperature can be supplied to the air handle units for dehumidification.

Effects of chill unit accumulation and temperature on woody plant deacclimation kinetics.

Woody perennials in temperate climates develop cold hardiness in the fall (acclimation) and lose cold hardiness in the spring (deacclimation) to survive freezing winter temperatures. Two main factors known to regulate deacclimation responses are dormancy status and temperature. However, the progression of deacclimation responses throughout the dormant period and across a range of temperatures is not well described. More detailed descriptions of dormancy status and temperature, as factors regulating deacclimation, are necessary to understand the timing and magnitude of freeze injury risks for woody perennials in temperate climates. In this study, we modeled deacclimation responses in cold‐climate interspecific hybrid grapevine cultivars throughout the dormant period by integrating chill accumulation and temperature through the concept of deacclimation potential. We evaluated deacclimation and budbreak under multiple temperature treatments and chill unit accumulation levels using differential thermal analysis (DTA) and bud forcing assays. Deacclimation responses increased continuously following logistic trends for both increasing chill unit accumulation and increasing temperature. There are optimal temperatures where deacclimation rates increased but changes in deacclimation rates diminished below and above these temperatures. The cumulative chill unit range where deacclimation potential increased overlapped with the transition from endo‐ to ecodormancy. Therefore, deacclimation potential could provide a quantitative method for describing dormancy transitions that do not rely on the visual evaluation of budbreak. This information provides a more detailed understanding of when and how deacclimation contributes to increased risks by freezing injury. In addition, our descriptions could inform improvements to models predicting cold hardiness, dormancy transitions, and spring phenology.

Potential application of cascade adsorption-vapor compression refrigeration system powered by photovoltaic/thermal collectors

• Cascade adsorption-compression system is investigated using photovoltaic thermal collectors. • Overall performance enhancement is attained at higher chilled water temperatures. • Annual energy saving proportionally increases with collector numbers up to 29%. • Distinctive payback period is attained compared to the state-of-the-art systems. In the present study, a theoretical assessment of an adsorption-assisted cascade compression refrigeration system powered by photovoltaic/thermal collectors is performed. The proposed system is intended to produce refrigeration and electricity simultaneously. Herein, mathematical modeling of the proposed system is developed using MATLAB/SIMULINK and validated with the open literature. The impact of collector area, compressor displacement volume, cooling water temperature, and brine temperature on the system performance are quantitatively investigated and analyzed. The economic analysis of the proposed system has also been conducted. It is observed that decreasing the compressor displacement volume and cooling water temperature could substantially increase the overall coefficient of performance and energy saving. Furthermore, the results demonstrate that the system performance enhances with the increase of the collector area and the brine temperature. It is found that the proposed system can concurrently attain a daily average cooling capacity and electricity yield of 1.7 kW and 103 kWh at cooling and brine temperatures of 30 °C and −20 °C, respectively. Simulation results indicate that the proposed system can generate annual refrigeration production and electricity production of 34.4 kWh c m −2 and 213 kWh el m −2 , respectively, with an annual average coefficient of performance of 2.38. Moreover, the economic analysis exhibited that the photovoltaic/thermal collectors-assisted cascade adsorption-compression system is economically competitive for refrigeration applications, revealing an annual energy saving of 24.8% and a payback period of ∼3.9 years. In this regard, cascade adsorption-compression systems could significantly extend the potential application and energy savings for cooling systems and heat pumps.

The Implementation of MQTT Protocol using PT-100 for Monitoring the Vaccine Temperature

A vaccine has an essential role for humans because it can reduce the effect of organism infection and activate the body's immune. The limitation of temperature when the vaccine is stored becomes one of the influential factors for its quality. Since the recent technique used for checking the temperature is manual, the process of real-time temperature monitoring cannot be done and becomes the main problem in the process of storing vaccines. This research is aimed to develop a system for measuring temperature on a chiller through a temperature sensor and the internet of things automatically. The methods used in the MQTT protocol are published and subscribed. The quality of service (QoS) to measure network capability and PT-100 is the sensor in this research because it has a high accuracy level, linear signal change, and fast response. This sensor can measure glycol liquid with a temperature range of 2-8°C. Data distribution uses an ESP module to connect the data to Antares through the wifi network. The temperature value measurement using PT-100 toward vaccine chiller temperature obtains an accuracy value of 99,32%. This accuracy value shows that the result is compatible with the logger data measurement tool development used with an error result of 0.58%. Delay parameter testing on the QoS level obtains the average value of 41.91 ms, while the Packet loss parameter obtains the value of 0%.

Effects of climatic factors on the prevalence of influenza virus infection in Cheonan, Korea.

Big data can be used to correlate diseases and climatic factors. The prevalence of influenza (flu) virus, accounting for a large proportion of respiratory infections, suggests that the effect of climate variables according to seasonal dynamics of influenza virus infections should be investigated. Here, trends in flu virus detection were analyzed using data from 9,010 tests performed between January 2012 and December 2018 at Dankook University Hospital, Cheonan, Korea. We compared the detection of the flu virus in Cheonan area and its association with climate change. The flu virus detection rate was 9.9% (894/9,010), and the detection rate was higher for flu virus A (FLUAV; 6.9%) than for flu virus B (FLUBV; 3.0%). Both FLUAV and FLUBV infections are considered an epidemic each year. We identified 43.1% (n = 385) and 35.0% (n = 313) infections in children aged < 10years and adults aged > 60years, respectively. The combination of these age groups encompassed 78.1% (n = 698/894) of the total data. Flu virus infections correlated with air temperature, relative humidity, vapor pressure, atmospheric pressure, particulate matter, and wind chill temperature (P < 0.001). However, the daily temperature range did not significantly correlate with the flu detection results. This is the first study to identify the relationship between long-term flu virus infection with temperature in the temperate region of Cheonan.

Development and performance evaluation of a chiller plant predictive operational control strategy by artificial intelligence

Traditionally, chiller plants are controlled and monitored by a predetermined control strategy to ensure appropriate operation based on the designed system configuration. With the use of new technology of variable speed drive (VSD) for compressors, smart control strategies could be leveraged to enhance the system efficiency in lieu of traditional control strategies. For example, using orderly and straightforward switching procedures without considering various factors in switching the units, including the high-efficiency partial load range benefitted from the VSD, the actual performance of the units as a whole and the variable chilled water flow rate, result in the chiller plant not operating at maximum performance and efficiency. To address these issues, a hybrid predictive operational chiller plant control strategy is proposed to optimize the performance of the chiller plant. Artificial intelligence is employed as the data mining algorithm, with big data analysis based on the actual acquired voluminous operation data by fully considering the characteristics of chiller plants without additional installation of large-sized and high-priced equipment. Artificial neural network (ANN) was employed in the control strategy to predict the future outdoor temperature, building cooling load demand and the corresponding power consumption of the chiller plants. At the same time, particle swarm optimization (PSO) was applied to search for the optimized setpoints, e.g., chilled water supply temperature, operating sequence, chilled water flow rate, for the chiller plants. The developed control strategy has been launched in a chiller plant with a cooling capacity of 7,700 kW installed in a hospital in Hong Kong. The system coefficient of performance (COP) and overall energy consumption of the chiller plants were enhanced by about 8.6% and reduced by about 7.9%, respectively, compared with the traditional control strategy. This real-time, continuous, automatic optimization control strategy can determine the most efficient combination of operating parameters of a chiller plant with different control settings. This ensures that the chiller plant operates in its most efficient mode year-round under various operational conditions.

Chilled water temperature set-point reset based on outdoor air temperature and its cooling energy performance in an office building

In this study, the cooling energy performance of two strategies for controlling ChWT (chilled water temperature) are compared: the conventional control strategy of constantly fixing ChWT and the OAT (outdoor air temperature) compensation control strategy that adjusts ChWT according to the changes in OAT. OAT compensation control strategy was modeled and realized based on Appendix G of ASHRAE Standard 90.1. It was confirmed that applying OAT compensation control strategy can significantly reduce chiller energy consumption, which accounts for the largest portion of total cooling energy consumption. It was found that the difference in total cooling energy consumption between applying the conventional control of constantly fixing ChWT to 6 °C and applying the OAT compensation control was approximately 8 % and 3 % during spring (March to May) and summer (June to August), respectively. Additionally, during the fall (September–November) period, about 7 % of total cooling energy consumption could be saved.

Testing of a Falling-Film Evaporator for Adsorption Chillers

In this work, the performance of an innovative evaporator based on water falling film was investigated. The studied evaporator has been equipped with a recirculation system to maximise the wetted surface. Tests have been carried out in a lab-scale adsorption unit connected to a test bench recently realised at Politecnico di Milano labs for evaluating heat transfer performances under realistic operating conditions. Several ad/desorption cooling cycles were performed, setting different liquid refrigerant initial contents (0.9–1.5 kg), different chilled water inlet temperatures (7–20 °C) and flow rates (200–1000 L/h) and different adsorbent bed temperatures (25–30 °C). Evaporation performance has been determined in delivered cooling capacity. Moreover, the experimental data were used to calculate the overall evaporator heat transfer conductance (UA). Experiments showed how the heat duty peaks are mainly due to the thermal level of the chilled water that enters the evaporator, not the water content inside it because this value only affects the duration of the process. Instead, the UA value does not depend on the evaporator inlet chilled water temperature and initial mass content inside the evaporator. UA is 540–570 W/K for temperatures of chilled water entering the evaporator, equal to 10–20 °C, and mass of refrigerant of 0.9–1.5 kg.