Abrupt Temperature Changes Research Articles

Study on effects of mixing characteristics on the hydrogen-containing micro-mixing combustion using a modified LES-FGM model

Mixing uniformity and combustion performance of a model Micromix burner were studied using the Large eddy simulation (LES) and modified Flamelet Generated Manifold (FGM) model. This model considered hydrogen preferential diffusion and used separate transport equations to compute NO formation, which significantly improved the prediction accuracy of flame structure and NO production for high-hydrogen micro-mixing jet flames. The result shows that, with changes in mixing uniformity, the difference in Damköhler numbers becomes noticeable as the reaction distance increases. It is most pronounced when the mixing quality increases above 90%, which leads to the abrupt change of the overall flame temperature and NO generation. Thus, there is an inflection point in the inhibition of NO production by mixing uniformity. Moreover, while the adiabatic flame temperature changes, the improved mixing quality can mitigate the flame temperature variations caused by changes in the equivalence ratio, further reducing the maximum NO production.

Near-Inertial Oscillations Induced by Winter Monsoon Onset in the Southwest Taiwan Strait

The near-inertial motion in ocean surface currents directly reflects the energy transported by wind towards the surface layer, playing an important role in climate regulation and energy balance. Previous studies have mainly focused on near inertial oscillations (NIOs) induced by tropical cyclones in the Taiwan Strait, with few reports on near inertial oscillations induced by monsoon onset. Using high-frequency radar observations, we detected an amplification of NIOs induced by the winter monsoon onset. While not as strong as NIOs induced by tropical cyclones, the near-inertial current (NIC) induced by winter monsoon onset in the Taiwan Strait has peak speeds reaching up to 5.2 cm/s and explaining up to 0.7% of non-tidal variance. This study presents observational results of NIOs during three monsoon onset events, and analyzes the impact of winds and temperature changes on NIOs. Temporal and spectral analysis reveals that the monsoon onset is the primary driver behind the formation of NIOs. Results indicate that near-inertial kinetic energy is relatively lower in shallower waters, such as the Taiwan Bank, compared to deeper regions. Furthermore, by integrating the air and sea surface temperature from reanalysis products, we have examined the abrupt changes in sea surface temperature (SST) before and after monsoon onset and their correlation with NIOs. The findings suggest that temperature falling favors the intensification of NICs during monsoon onset, and a lack of significant SST changes precludes the triggering of notable NICs. These insights enhance our understanding of the mechanisms driving NIOs and their roles in seawater mixing.

Dynamic heat transfer characteristics of printed circuit precooler in supercritical CO2 Brayton cycle

The dynamic characteristics of heat exchangers are critical in supercritical CO2 Brayton cycle, especially in the precooler where significant thermophysical property variations occur. However, few studies have comprehensively analyzed the dynamic heat transfer characteristics in precooler, particularly with respect to the detailed flow and thermal field evolution. A three-dimensional numerical model was developed to study the dynamic performance of a printed circuit precooler, with an emphasis on the impact of thermophysical properties. The study examines responses to abrupt changes in CO2 and water inlet temperature, as well as mass flux variations. Results show that the precooler exhibits rapid response characteristics with mild fluctuations in heat transfer parameters and flow structure. Notably, the large specific heat near the critical point results in minimal variation in CO2 outlet temperature despite abrupt increases in CO2 inlet temperature, thereby enhancing system stability. Conversely, a decrease in CO2 mass flux causes a transition from forced convection to mixed flow, with strengthened buoyancy effects and decreased entropy production. These variations lead to significant changes in CO2 outlet temperature, posing potential challenges to system stability under CO2 mass flux step change conditions. The heat transfer shows a relatively lower response rate to parameter changes of water compared to CO2. Although variations in water parameters have a negligible effect on CO2 heat transfer, they influence the overall heat transfer coefficient. The dynamic heat transfer characteristics of the precooler presented in this paper address research gaps left by 1D numerical and experimental studies, which have provided limited information on flow and thermal fields during dynamic processes. These insights are essential for understanding the dynamic behavior of the entire system.

Position Feedback-Control of an Electrothermal Microactuator Using Resistivity Self-Sensing Technique.

The self-sensing technology of microactuators utilizes a smart material to concurrently actuate and sense in a closed-loop control system. This work aimed to develop a position feedback-control system of nickel electrothermal microactuators using a resistivity self-sensing technique. The system utilizes the change in heating/sensing elements' resistance, due to the Joule heat, as the control parameter. Using this technique, the heating/sensing elements would concurrently sense and actuate in a closed loop control making the structures of microactuators simple. From a series of experiments, the proposed self-sensing feedback control system was successfully demonstrated. The tip's displacement error was smaller than 3 µm out of the displacement span of 60 µm. In addition, the system was less sensitive to the abrupt temperature change in surroundings as it was able to displace the microactuator's tip back to the desired position within 5 s, which was much faster than a feed-forward control system.

Numerical study on the effect of temperature rise of humeral bone nails in magnetic resonance imaging based on the finite-element method.

Humeral fracture is a common long bone fracture in orthopedic clinical diagnosis and treatment. To investigate the local temperature increase owing to changes in the specific absorption ratio (SAR) of the human body caused by humeral bone nails during magnetic resonance imaging (MRI). A refined geometric model of the upper body was constructed via data segmentation and post-processing using the digital human image dataset. Finally, the geometric model was imported into COMSOL, a 3-T magnetic resonance coil was built, and the operating frequency (128 MHz) was set to analyze the SAR of the bone-nail pair and temperature changes. The analysis of the changes after bone-nail implantation under different tissue conditions revealed that the SAR and temperature after implantation and fixation were three times higher than those before, and the areas with abrupt changes in SAR and temperature were primarily concentrated in the bone-nail area. In MRI, metal implants can cause local elevation of the SAR near the implant in the human body, resulting in a temperature increase around the implant. Consequently, long-term scanning can damage the human body.

Extreme hydrometeorological events induce abrupt and widespread freshwater temperature changes across the Pacific Northwest of North America

AbstractThe Pacific Northwest of North America experienced four extreme hydrometeorological events during 2021 including intense cold waves in mid-February and late December, the record-setting June heat dome, and catastrophic floods caused by two November atmospheric rivers. While the synoptic-scale patterns and terrestrial hydrological responses to these extreme events are well documented, scant information has been published on corresponding freshwater temperature responses. Here, we apply an observational database of hourly freshwater temperatures at 554 sites across the region to characterize their evolution during these four extreme hydrometeorological events. The two cold snaps and summer heat dome induced a general 1 °C decline and 2.7 °C increase, respectively, in water temperatures with subdued changes (+0.4 °C) during the mid-November floods. For 193 sites with long-term records, 478 daily maximum water temperatures were exceeded during the heat dome and 94 were surpassed during the flooding event, suggesting deleterious effects for water quality and aquatic species.

Modeling streamflow responses to land use and land cover change using MIKE SHE model in the upper Omo Gibe catchment of Ethiopia

AbstractThe land use and land cover (LULC) changes in the upper Gibe catchment were studied intricately using the MIKE SHE model and analyzed through statistical tests. The Mann–Kendall test was used to identify potential trends, while the Pettit test was used to detect abrupt changes in rainfall, temperature, and streamflow. A set of three maps of LULC change (1990, 2003, and 2018) was developed to observe how they affect the hydrological pattern of the catchment. Statistical analyses were conducted at mean annual time scales to establish relationships among the anomalies. It has been noted that certain temperature gauges showed statistically significant increases in temperature. Change points in the 1980s and 1990s were identified during the study period. The annual streamflow trends displayed an increasing trend that was not that significant. LULC changes contributed to increased surface runoff, attributed to agricultural, settlement, and water body expansion, as well as reductions in bare land, forest, shrubland, and grassland. The MIKE SHE model performed well during both the calibration and validation periods on the monthly time scale. The alterations in LULC had a noticeable impact on stream flows during both wet and dry seasons, resulting in increased mean monthly stream flows during the wet season and decreased flows during the dry season. The MIKE SHE study and related statistical analysis is quite a different method to perceive the results.

Numerical modelling of the warping behaviour at the first layer-build plate interface in 3D-printed models produced via the fused deposition modelling process

The material structure of 3D-models printed via the fused deposition modelling (FDM) technique is mainly affected in the z-direction of the 3D-print as a result of the layer-by-layer approach which tend to exhibit a deformation behavior corresponding to a type of transversely orthotropic material. Moreover, uncontrolled parameters such as printing temperature and printing speed have been reported to adversely affect 3D-print quality leading to undesired effects such as distortion and warpage. The additive manufacturing process is a relatively new field in advanced manufacturing where further research and innovation are required to overcome the limited strength and structural performance observed in presently 3D-printed components. In line with the above, this study proposes the numerical investigation of the warping behavior in PLA (Polylactic acid) - based 3D printed models by considering the finite element method (FEM) software of LS-DYNA. The warping investigation was specifically centered on the cooling cycle prevailing between the layer-by-layer structures. The findings of this study showed that warpage would most likely occur in the thermal process model corresponding to abrupt change in temperature due to a buildup of strain between the bottom most layers of the 3D model and the build plate. The findings of this study, which shed light on the warping behaviour in 3D-models, has direct implications on the final quality of 3D-printed components.

A Study on the Reliability Evaluation of a 3D Packaging Storage Module under Temperature Cycling Ultimate Stress Conditions.

Based on the theory of reliability enhancement testing technology, this study used a variety of testing combinations and finite element simulations to analyze the stress-strain properties of 3D packaging storage modules and then evaluated its operating and destruction limits during temperature cycling tests (-65 °C~+150 °C) for the purpose of identifying the weak points and failure mechanisms affecting its reliability. As a result of temperature cycling ultimate stress, 3D packaging storage devices can suffer from thermal fatigue failure in the case of abrupt temperature changes. The cracks caused by the accumulation of plastic and creep strains can be considered the main factors. Crack formation is accelerated by the CTE difference between the epoxy resin and solder joints. Moreover, the finite element simulation results were essentially the same as the testing results, with a deviation occurring within 10%.

Variations in Maximum and Minimum Temperature in Mount Qomolangma during 1971–2020

Based on the daily maximum and minimum temperature observational data during 1971–2020, the variabilities of the maximum and minimum temperature of Mount Qomolangma are analyzed. The daily maximum temperature is 25.8 °C and the daily minimum temperature is −31.4 °C during the study period in Mount Qomolangma. Overall, there has been an upward trend with decadal laps for both maximum and minimum temperature. On monthly, seasonal, and annual scales, neither maximum temperature nor minimum temperature time series exhibit an increasing trend from 1971 to 2020. The increasing trends in monthly minimum temperature are even more pronounced than those in maximum temperature. Abrupt changes are noted in both monthly, seasonal, and annual maximum and minimum temperature time series. Specifically, an abrupt change in annual maximum temperature occurred in the 1980s, while an abrupt change in annual minimum temperature occurred in the 1990s. Differences between the north and south slope of Mount Qomolangma are evident, with temperature fluctuations of the north slope being more extreme than those of south slope. The seasonal and annual maximum temperature of the north slope is higher than that of the south slope, except for winter, and the seasonal and annual minimum temperatures of the north slope are all lower than those of the south slope. The tendences of maximum and minimum temperatures in the north slope are more dominant than those in the south slope. The findings are beneficial for understanding the characteristics of local climate change on the Tibetan plateau and to underscore the significant role of Mount Qomolangma in the context of global warming.

Analysis of Thermomechanical Stress of High-Temperature Ignition Surface Caused by Drop–Wall Interaction at Engine Conditions

Abstract Drop–wall interaction is a complex phenomenon encountered in diverse industrial applications. An important example is fuel droplets impinging on a high-temperature ignition plug in a direct-injection compression-ignition engine. The ignition plug, comprised of heat-resistant materials, will experience thermal shock due to abrupt temperature changes. The ensuing temperature fluctuation in the solid wall induces thermal stress, and if this stress surpasses the material's strength in that mode, failure can occur. Therefore, it is imperative to analyze the temperature dynamics on the high-temperature surface to enhance material durability. This study focuses on drop–wall interactions in the engine environment. Utilizing the Smoothed Particle Hydrodynamics (SPH) method, this research simulates fuel droplet impingement on an ignition plug with various materials to characterize heat transfer, thermal penetration, and temperature distributions in the heated wall. The investigation also delves into the behavior of ceramic material, specifically silicon nitride, assessing its thermomechanical stress and durability based on the stress–number of cycles (S-N) curve. Thermal stress is computed by considering temperature gradients and material properties, while mechanical stress is evaluated based on the bending momentum and momentum flux induced by the spray. A parametric study explores diverse materials such as tungsten carbide, iron, stainless steel, carbon steel, and aluminum. Results indicate that thermal stress outweighs bending and spray-induced stress. Moreover, the analysis reveals that silicon nitride exhibits the lowest thermal stress distribution and superior durability, potentially capable of operating for infinite cycles under engine-relevant conditions.

Synthesis and behavior in aqueous solution of carboxymethyl pullulan-graft-poly(N-isopropylacrylamide-co-methacrylamide)

Stimuli-responsive polymers are fascinating materials because they mimic the behavior of living systems. This ability to respond to the action of certain stimuli makes them interesting both from the point of view of the theoretical study of their behavior in solution and of biomedical applications. In this regard, semitelechelic oligomers of N-isopropylacrylamide-co-methacrylamide (thermosensitive) with amine end groups were grafted onto previously synthesized carboxymethyl pullulan (sensitive to pH). The oligomers as well as the graft copolymer were characterized in terms of composition, molecular mass, number of grafts on the pullulan macromolecule, grafting density, and Kuhn segment length. Thermoresponsiveness of the grafted copolymer was studied in wide concentration and pH ranges. The onset temperature of phase separation proved to be independent of concentration and influenced by pH in highly basic solutions.The time of the copolymer response to abrupt change in temperature was analyzed.

A Convolutional Neural Network and Attention-Based Retrieval of Temperature Profile for a Satellite Hyperspectral Microwave Sensor

As numerical weather forecasting advances, there is a growing demand for higher-quality atmospheric data. Hyperspectral instruments can capture more atmospheric information and increase vertical resolution, but there has been limited research into retrieval algorithms for obtaining hyperspectral microwaves in the future. This study proposes an atmospheric temperature profile detection algorithm based on Convolutional Neural Networks (CNN) and Local Attention Mechanisms for local feature extraction, applied to hyperspectral microwave sensors. The study utilizes the method of information entropy to extract more effective channels in the vicinities of 60 GHz, 118 GHz, and 425 GHz. The algorithm uses the brightness temperature as the input of the network. The algorithm addresses common issues encountered in conventional networks, such as overfitting, gradient explosion, and gradient vanishing. Additionally, this method isolates the three oxygen-sensitive frequency bands for modularized local feature extraction training, thereby avoiding abrupt changes in brightness temperature between adjacent frequency bands. More importantly, the algorithm considers the correlation between multiple channels and information redundancy, focusing on variations in local information. This enhances the effectiveness of hyperspectral microwave channel information extraction. We simulated the brightness temperatures of the selected channels through ARTS and divided them into training, validation, and test sets. The retrieval capability of the proposed method is validated on a test dataset, achieving a root mean square error of 1.46 K and a mean absolute error of 1.4 K for temperature profile. Detailed comparisons are also made between this method and other commonly used networks for atmospheric retrieval. The results demonstrate that the proposed method significantly improves the accuracy of temperature profile retrieval, particularly in capturing fine details, and is more adaptable to complex environments. The model also exhibits scalability, extending from one-dimensional (pressure level) to three-dimensional space. The error for each pressure level is controlled within 0.7 K and the average error is within 0.4 K, demonstrating effectiveness across different scales with impressive results. The computational efficiency and accuracy have both been improved when handling a large amount of radiation data.

Navigating Flood Resilience: Challenges, Solutions, and Lessons Learnt from the Dominican Republic

Recent unprecedented events worldwide, such as floods in Dubai, recurring heavy rainfall in Santo Domingo, and abrupt temperature changes in the United Kingdom (UK), underscore the tangible impacts of climate change. In response to escalating threats from natural disasters, global communities prioritise resilience and effective disaster management systems. This paper addresses best practices for managing abnormal floods, laying the foundation for the next generation of preparedness and mitigation plans. Focusing on flood risk in Santo Domingo, the study employs the Community Disaster Resilience Framework, conducting a workshop with over 100 stakeholders from government, private, and academic sectors. The assessment spans physical, economic, environmental, and social aspects, revealing common challenges in infrastructure upkeep, public awareness, urban planning, drainage, and economic disparities. The paper proposes technological solutions like predictive maintenance and smart drainage systems, emphasising the potential for implementation. Recognising the importance of community involvement and preparedness, insights from the United Kingdom guide initial steps in strategy development. The conclusions advocate for collaborative efforts among government, academia, and society to navigate the complexities of disaster management and community resilience, ultimately proposing a framework to address these challenges. Further research is suggested in expanding online platforms for disaster risk reduction education in the Caribbean region.

Ecophysiological responses of Liolaemus arambarensis juveniles to experimental temperature variations

Climate change increasingly influences the loss of biodiversity, especially in ectothermic organisms, which depend on environmental temperatures to obtain heat and regulate their life cycle. Studies that aim to understand the impact of temperature variation are important to better understand the possible impacts generated on the homeostasis of ectothermic organisms. Our objective was to characterize the responses of juvenile Liolaemus arambarensis lizards to abrupt changes in temperature, quantifying markers of body condition, intermediary and hormonal metabolism and oxidative balance. We collected 45 juvenile individuals of L. arambarensis (winter: 20 and summer: 25) in Barra do Ribeiro, Brazil. We transported the animals to the laboratory, where they were acclimatized for five days at a temperature of 20 °C, then divided and exposed to temperatures of 10 °C, 20 °C, 30 °C and 40 °C for 24 h. After exposure, the animals were euthanized and the brain, caudal muscle, thigh, and liver tissues were extracted for quantification of biomarkers of metabolism (glycogen and total proteins) and oxidative balance (acetylcholinesterase, superoxide dismutase, catalase, glutathione-S-transferase and lipoperoxidation) and plasma for corticosterone quantification. The results show that L. arambarensis is susceptible to sudden temperature variations, where higher temperatures caused greater activity of antioxidant enzymes, increased lipoperoxidation and higher plasma levels of corticosterone in animals eliminated in winter. The present study demonstrated that abrupt changes in temperature could significantly modify the homeostatic mechanisms of animals, which could lead to oxidative stress and a potential trade-off between survival and growth/reproduction. In this context, the organism mobilizes energy resources for survival, with possible damage to growth and reproduction. Demonstrate that a change in temperature can be a potential factor in extinction for a species given the profile of global climate change.

Degradation of Carbon/Phenolic Composite Materials for Spacecraft Structure Material

Due to their ability to be tailored in terms of strength, stiffness, and density, composite materials are a valuable commodity in the aerospace sector. But composite materials also deteriorate with time, just like other materials do, particularly in abrasive conditions like space. Thermal degradation brought on by abrupt temperature changes in the aircraft environment, which can result in dimensional changes, cracking, and even decomposition of composite materials, are degradation issues that can influence composite materials in aerospace applications. In this study, thermogravimetric analysis (TGA) of carbon/phenolic composites, as a fiber using carbon fiber (Kyoto carbon) with plain weave type and as a matrix using ARMC-551-RN phenolic resin. Furthermore, the test method refers to the ASTM E1131-08 Standard. Thermogravimetric Compositional Analysis Test Method. Ultimately, engineers hope to improve spacecraft design, reliability, and safety in severe space missions by using TGA analysis to understand the thermal characteristics and stability of carbon/phenolic composite materials utilized in spacecraft components.

Theoretical study of the structural and energetic properties of Ce1-xZrxO2 nanoparticles via molecular dynamics simulations.

The combination of ceria (CeO2) with different metal oxides (MO2), e.g. Ce1-xMxO2, has been strategically used to enhance its intrinsic properties. Moreover, the controlled synthesis of mixed oxide nanoparticles (NPs) opens the opportunity to explore the size dependence and chemical composition of the physical-chemical properties. However, our atomic-level understanding of how the physical-chemical and thermodynamic characteristics change with particle size and composition remains far from satisfactory. Here, we used force-field molecular dynamics simulations to investigate the effects of composition (x) and size on the physical-chemical properties of Ce1-xZrxO2 NPs with diameter from 1 (32 cations) up to 3 nm (256 cations), where x = 0.0, 0.2, 0.4, 0.6, 0.8 and 1.0. We found abrupt changes in potential energy versus temperature for NPs with more than 108 cations, indicating a structural phase transition from disordered to ordered structures, which was confirmed by the radial distribution function. We found a linear relationship between the phase transition temperature (Tpt) and the size and composition of the NPs: the increase in the molar fraction of Zr4+ and the reduction in particle size are related to lower Tpt temperature and less defined decays of potential energy versus temperature. NPs larger than 56 cations show a radial distribution function with several peaks, which is related to the order of cations and anions in these structures. These peaks gradually disappear as the size decreases and the fraction of Zr4+ increases. Similar trends were observed with X-ray diffraction analysis; for example, fluorite-like motifs occur even with 56 cations in the case of ceria, but only for NPs with 108 cations for zirconia. Common neighbor analysis confirmed that NPs with well-defined values of the temperature Tpt have face-centered cubic (fcc)-like domains in the core region. The number of ordered fcc cations increases with increasing NP size and decreasing Zr4+ concentration. Finally, we observed that ceria nucleate first during simulated annealing and occupy highly coordinated sites within the core, while Zr4+ prefers the lowest coordinated sites on the surface.

Development of a multi-stage model for freezing of a suspended binary solution droplet

The importance of developing spray freeze-drying technology for extending the shelf life of biological and pharmaceutical materials has never been greater, given the increasing food shortage and the strong demand for pharma processes. In particular, the optimal thermal design and application of spray freeze-drying technologies now depend on the estimation of nucleation behavior for droplet solidification (especially the droplets of binary mixtures). Although earlier nucleation models could estimate the nucleation rate and temperature of solidifying droplets, few considered extreme environmental factors, such as extremely low ambient temperatures below −60C∘. To ensure the preservation and storage of biological and pharmaceutical products, such as vaccines and protein drugs, these conditions are essential. Hence, developing an accurate and trustworthy mathematical framework for simulating nucleation is paramount. In this study, a multi-stage, hybrid analytical-numerical model for droplet solidification is developed while coupled with a gradient-based optimization algorithm. Specifically, the five-stage solidification of binary mixtures is simulated (including supercooling of liquid, nucleation, recalescence, equilibrium freezing, and subcooling of solid), which captures the dynamic behaviors of temperature and composition or solute concentration during phase change. The heterogeneous nucleation of a binary-mixture droplet in a frigid environment is predicted and validated against a series of experiments on single suspended droplets at a wide range of ambient temperatures between −20 and −160C∘. The freezing curves of different solute concentrations are also validated against experimental data. It is found that significant variations in interfacial tension lead to abrupt changes in nucleation temperature for extremely cold environments. Further, the effects of the concentration, contact angle, droplet size, and heat transfer coefficient are investigated.

Extraction of atmospheric corrosion monitoring sensor signals using MSSA and corrosion progress prediction with an LSTM model

The sensitivity of corrosion signals to temperature fluctuations often presents significant challenges for signals acquired from corrosion sensors. The main objective of this study is to assess these signals collected by the atmospheric corrosion monitoring sensor based on strain measurement through the application of multivariate singular spectrum analysis (MSSA) for extracting corrosion signal data. The study results demonstrate that MSSA has consistently exhibited exceptional performance in isolating corrosion signals, particularly in scenarios where they are affected by inherent noise resulting from abrupt temperature changes, corrosion products and residual stress. Moreover, the corrosion signals extracted via MSSA were harnessed to create a long short-term memory (LSTM) model, with the aim of predicting future corrosion processes. The results of this study emphasize the effectiveness and reliability of the LSTM model in forecasting corrosion processes. This study holds a crucial role in the management of corrosion processes in materials exposed to atmospheric conditions, ensuring both structural integrity and industrial safety.

Effects of One-Step Abrupt Temperature Change on Anaerobic Co-Digestion of Kitchen Waste with Dewatered Sludge

The operating temperature of anaerobic digesters should be adjusted to adapt to seasonal variations in environmental temperature and the composition of organic solid waste. This study investigated the effects of one-step abrupt temperature changes (from mesophilic to thermophilic temperature, M–T, and from thermophilic to mesophilic temperature, T–M) and the inoculation ratio on methane yield and microbial diversity during the anaerobic co-digestion of kitchen waste with dewatered sludge. The results showed that the cumulative methane yield (CMY) level resulting from thermophilic control and the M–T digesters was greater than that resulting from mesophilic control and the T–M digesters. The CMF of M–T digesters increased, whereas the CMY of T–M digesters gradually decreased with an increase in the inoculation ratio. The maximal CMY was 385.1 mL/g-VSSadded, which corresponded to an M–T digester with a 5% inoculation ratio. In the later stage of anaerobic digestion, the bacterial community of T–M was more diverse than that of M–T, but the archaeal community of M–T was more diverse than that of T–M. The one-step temperature change from thermophilic to mesophilic temperature was more stable than that from mesophilic to thermophilic temperature.