Temperature Variance Research Articles

Numerical study of reaction enhancement in hydrogen oxidation reactor with supercritical water medium by twisted oval structure

The oxidation of hydrogen in supercritical water supplies heat for the supercritical water gasification technology and is an essential part of the system. The mild release of heat in a limited space is a significant challenge. In the present study, a twisted oval structure was used to enhance the mixing inside the reactor, avoiding excessive local temperature and promoting heat transfer to the outside. A numerical model was developed to investigate hydrogen oxidation in supercritical H2O / CO2 mixtures. The effects of different inlet and structure parameters, including temperature, velocity, components, twisted pitch length, and aspect ratio, were evaluated. The steady-state simulation found that the circular structure allowed high-temperature fluids to cluster significantly around the nozzle and axis, resulting in excessive local temperatures. In contrast, the twisted oval structure stabilized the axial temperature faster while enabling more uniform temperature distribution in the radial direction. The maximum radial temperature difference and radial temperature variance were reduced by an average of 52.18% and 81.31%, respectively. Furthermore, the unreacted hydrogen escaping from the reactor at high flow rates was also avoided due to the enhanced radial mixing by the secondary flow in the twisted oval structure. The transient-state simulation showed that the twisted oval structure could stabilize the temperature distribution rapidly during reactor start-up, which might support further scale-up for the reactor.

Mixing and Overturning Across the Brazil‐Malvinas Confluence

AbstractThe rates of isopycnal stirring and water mass transport by mesoscale eddies, and of diapycnal mixing by small‐scale turbulence, across the Brazil‐Malvinas Confluence (BMC) are assessed from a set of microstructure and hydrographic measurements in the Argentine Basin. This assessment is founded on a theoretical framework that applies a triple decomposition to the temperature variance equation and assumes eddies to transfer potential vorticity downgradient. The BMC is found to host widespread intense isopycnal stirring at rates of O(103–104 m2 s−1), and generally weak diapycnal mixing at rates of O(10−6–10−5 m2 s−1). Despite such disparity, both diapycnal mixing and isopycnal stirring play roles of comparable importance in determining regional water mass properties within surface and mode waters. In deeper layers, isopycnal stirring prevails. Eddies are further diagnosed to effect an important cross‐BMC transport, at rates of O(1 m2 s−1). When scaled by the along‐stream extent of the BMC, these rates integrate to volume transports that may be as large as O(10 Sverdrups). This suggests that cross‐BMC transfers of waters are substantially effected by eddy‐induced flows.

Effect of mechanical stirring on the tubular heating process of crude oil

Research on thermal behaviors under the synergy of mechanical stirring and tubular heating can reveal the effect mechanism of mechanical stirring, and determine the optimal stirring parameters. In this paper, the physical and mathematical models of heat transfer in crude oil storage tank under the synergy of tubular heating and mechanical stirring are established, the sliding grid technique is used to model the stirring impeller, which are further numerical calculated by the FVM. Our outcomes demonstrate that through the enhancement of convection, mechanical stirring significantly changes the thermal behaviors and enhances the heat exchange. Precisely, for a 1,000 m3 crude oil storage tank, the stirring of 350 rpm can increase the average velocity by 329%, the heating rate by 89%, and rise the average crude oil temperature from 42.311 °C to 42.586 °C during 2 h of heating. However, the higher crude oil temperature will cause a 1,613 W increase in heat loss power. The heating efficiency has also increased by 10%. Furthermore, mechanical stirring can promote a more uniform temperature distribution. Thus, the volume ratio in the low-temperature region decreases by 10% and that in the high-temperature region increases by 26%. The temperature variance decreases from 4.517 °C2 to 0.275 °C2. However, the velocity and temperature fields are almost the same under different stirring rates. With increasing stirring rate from 100 rpm to 700 rpm, the average heating rate can only increase by 0.026 °C/h, and temperature variance decreases from 0.596 °C2 to 0.086 °C2. With increasing stirring rate, the efficiency of the heating tube does not change significantly. The optimal stirring rate is determined as 350 rpm based on the fitting curve of temperature variance stabilization time and the comprehensive effect.

Turbulent structure of the Arctic boundary layer in early summer driven by stability, wind shear and cloud-top radiative cooling: ACLOUD airborne observations

Abstract. Clouds are assumed to play an important role in the Arctic amplification process. This motivated a detailed investigation of cloud processes, including radiative and turbulent fluxes. Data from the aircraft campaign ACLOUD were analyzed with a focus on the mean and turbulent structure of the cloudy boundary layer over the Fram Strait marginal sea ice zone in late spring and early summer 2017. Vertical profiles of turbulence moments are presented from contrasting atmospheric boundary layers (ABLs) from 4 d. They differ by the magnitude of wind speed, boundary-layer height, stability, the strength of the cloud-top radiative cooling and the number of cloud layers. Turbulence statistics up to third-order moments are presented, which were obtained from horizontal-level flights and from slanted profiles. It is shown that both of these flight patterns complement each other and form a data set that resolves the vertical structure of the ABL turbulence well. The comparison of the 4 d shows that especially during weak wind, even in shallow Arctic ABLs with mixing ratios below 3 g kg−1, cloud-top cooling can serve as a main source of turbulent kinetic energy (TKE). Well-mixed ABLs are generated where TKE is increased and vertical velocity variance shows pronounced maxima in the cloud layer. Negative vertical velocity skewness points then to upside-down convection. Turbulent heat fluxes are directed upward in the cloud layer as a result of cold downdrafts. In two cases with single-layer stratocumulus, turbulent transport of heat flux and of temperature variance are both negative in the cloud layer, suggesting an important role of large eddies. In contrast, in a case with weak cloud-top cooling, these quantities are positive in the ABL due to the heating from the surface. Based on observations and results of a mixed-layer model it is shown that the maxima of turbulent fluxes are, however, smaller than the jump of the net terrestrial radiation flux across the upper part of a cloud due to the (i) shallowness of the mixed layer and (ii) the presence of a downward entrainment heat flux. The mixed-layer model also shows that the buoyancy production of TKE is substantially smaller in stratocumulus over the Arctic sea ice compared to subtropics due to a smaller surface moisture flux and smaller decrease in specific humidity (or even humidity inversions) right above the cloud top. In a case of strong wind, wind shear shapes the ABL turbulent structure, especially over rough sea ice, despite the presence of a strong cloud-top cooling. In the presence of mid-level clouds, cloud-top radiative cooling and thus also TKE in the lowermost cloud layer are strongly reduced, and the ABL turbulent structure becomes governed by stability, i.e., by the surface–air temperature difference and wind speed. A comparison of slightly unstable and weakly stable cases shows a strong reduction of TKE due to increased stability even though the absolute value of wind speed was similar. In summary, the presented study documents vertical profiles of the ABL turbulence with a high resolution in a wide range of conditions. It can serve as a basis for turbulence closure evaluation and process studies in Arctic clouds.

A comparative study of data-driven electro-thermal models for reconfigurable lithium-ion batteries in real-time applications

Reconfigurable battery systems can change the cell topology, which allows novel applications that are not possible with conventional battery systems. However, reconfiguration complicates monitoring of the individual cell state since greater variances in temperature and SOC are introduced. Especially critical for a safe operation and adequate performance is the thermal behavior, which needs to be determined for every single cell in real-time. In this work, four different reduced-order lumped models and four artificial neural network models are compared in a surrogate modeling approach for the practical application in a reconfigurable battery system. The comparison includes the representation of serial and serial–parallel topologies. Furthermore, different coupling variants of single cell models are investigated in order to find the best representation of the physical model of a reconfigurable battery systems in an automotive application. While a separate observation of individual cells in switching systems is shown to be no longer sufficient, good results are already evident with simple models and adequate coupling approaches. The data-driven surrogate approaches achieved errors as low as 0.1 K while at the same time reducing the computational effort drastically compared to a physics-based model.

Study on DNA Storage Encoding Based IAOA under Innovation Constraints.

With the informationization of social processes, the amount of related data has greatly increased, making traditional storage media unable to meet the current requirements for data storage. Due to its advantages of a high storage capacity and persistence, deoxyribonucleic acid (DNA) has been considered the most prospective storage media to solve the data storage problem. Synthesis is an important process for DNA storage, and low-quality DNA coding can increase errors during sequencing, which can affect the storage efficiency. To reduce errors caused by the poor stability of DNA sequences during storage, this paper proposes a method that uses the double-matching and error-pairing constraints to improve the quality of the DNA coding set. First, the double-matching and error-pairing constraints are defined to solve problems of sequences with self-complementary reactions in the solution that are prone to mismatch at the 3' end. In addition, two strategies are introduced in the arithmetic optimization algorithm, including a random perturbation of the elementary function and a double adaptive weighting strategy. An improved arithmetic optimization algorithm (IAOA) is proposed to construct DNA coding sets. The experimental results of the IAOA on 13 benchmark functions show a significant improvement in its exploration and development capabilities over the existing algorithms. Moreover, the IAOA is used in the DNA encoding design under both traditional and new constraints. The DNA coding sets are tested to estimate their quality regarding the number of hairpins and melting temperature. The DNA storage coding sets constructed in this study are improved by 77.7% at the lower boundary compared to existing algorithms. The DNA sequences in the storage sets show a reduction of 9.7-84.1% in the melting temperature variance, and the hairpin structure ratio is reduced by 2.1-80%. The results indicate that the stability of the DNA coding sets is improved under the two proposed constraints compared to traditional constraints.

Topology optimized novel additively manufactured heat sink: Experiments and numerical simulations

Topology optimization is an effective method for designing high-performance heat sinks with reduced weight and size. The integration of topology optimization with additive manufacturing technology can effectively leverage the benefits of topology optimization to enhance the design process. In this study, nine types of heat sinks are designed by density-based topology optimization and fabricated via the laser powder bed fusion technology. Three different optimization goals including the minimization of temperature variance, thermal compliance and the temperature difference between the heat source surface and side surfaces are considered in design configurations. We develop a high-fidelity computational fluid dynamics model to investigate the velocity and temperature distributions of the cooling fluid around various fins, and conduct the corresponding experiments to test the thermal performance of the developed heat sinks. The results show that topology optimized fins can significantly enhance heat transfer capability of the heat sink. As the cooling fluid velocity increases from 0.3 m/s to 1.9 m/s, topology optimized heat sinks exhibit superior thermal performance with the highest heat transfer coefficient of 305 W·m−2·K−1 and the highest Nusselt number of 202. This research proves the powerful capability of laser powder bed fusion technology on manufacturing novel peculiar fins and provides a theoretical and experimental guidance for novel compact heat sink in the future designs.

Understanding and Reducing Warm and Dry Summer Biases in the Central United States: Analytical Modeling to Identify the Mechanisms for CMIP Ensemble Error Spread

Abstract Most climate models in phase 6 of the Coupled Model Intercomparison Project (CMIP6) still suffer pronounced warm and dry summer biases in the central United States (CUS), even in high-resolution simulations. We found that the cloud base definition in the cumulus parameterization was the dominant factor determining the spread of the biases among models and those defining cloud base at the lifting condensation level (LCL) performed the best. To identify the underlying mechanisms, we developed a physically based analytical bias model (ABM) to capture the key feedback processes of land–atmosphere coupling. The ABM has significant explanatory power, capturing 80% variance of temperature and precipitation biases among all models. Our ABM analysis via counterfactual experiments indicated that the biases are attributed mostly by surface downwelling longwave radiation errors and second by surface net shortwave radiation errors, with the former 2–5 times larger. The effective radiative forcing from these two errors as weighted by their relative contributions induces runaway temperature and precipitation feedbacks, which collaborate to cause CUS summer warm and dry biases. The LCL cumulus reduces the biases through two key mechanisms: it produces more clouds and less precipitable water, which reduce radiative energy input for both surface heating and evapotranspiration to cause a cooler and wetter soil; it produces more rainfall and wetter soil conditions, which suppress the positive evapotranspiration–precipitation feedback to damp the warm and dry bias coupling. Most models using non-LCL schemes underestimate both precipitation and cloud amounts, which amplify the positive feedback to cause significant biases.

Biotic and abiotic drivers of aquatic plant communities in shallow pools and wallows on the sub-Antarctic Iles Kerguelen

In the sub-Antarctic region, climate change is particularly rapid, while their freshwater ecosystems, such as ponds, host plant species with limited spatial distributions. These particular systems and their plant communities remain however poorly known and the context of their changing habitat calls for deeper insights into these systems. We performed an extensive survey of 45 ponds over three locations of the Iles Kerguelen during the winter and summer seasons of two years, which included the measurement of 12 abiotic parameters and the assessment of the plant community composition. Overall, our results showed that Iles Kerguelen ponds are shallow freshwater ecosystems harbouring species-poor plant communities with high evenness, of which structure did not vary among the sampled locations. Three different habitats were identified among ponds in relation with nutrient supply by marine animals, which ultimately influenced plant community structure and cover. We highlight that these habitats are mostly determined by water depth, nutrients, and temperature (mean and variance). Present plant community composition was more strongly correlated with plant community composition in the previous year than with abiotic conditions. Overall, this study provides new knowledge on the aquatic plant communities and the functioning of Iles Kerguelen freshwater ecosystems, which can serve as a basis for future studies dealing with the impact of climate change in the sub-Antarctic region.

Ocean drifter velocity data assimilation, Part 1: Formulation and diagnostic results

Numerical ocean circulation forecasts diverge from reality due to non-deterministic processes. Through data assimilation, ocean forecasting systems routinely make corrections to scalar ocean variables of temperature and salinity derived from ocean observations. Velocity observations, however, are vector quantities that require different processing. To assimilate existing ocean velocity observations, which generally are depth limited, vertical error covariances are needed to relate the velocity errors throughout the water column. In this paper we show a velocity assimilation approach that relies on historical observations and geostrophy to relate velocity, temperature, and salinity. Geopotential calculations transform temperature and salinity covariances into corresponding geopotential covariances. This paper describes the methods and examines details of the solution process for ocean velocity data assimilation. The approach employs two separate three-dimensional variational (3DVAR) analyses combined to create one set of initial conditions during each daily forecast cycle. The first 3DVAR analysis utilizes temperature, salinity, and sea surface height anomaly data and reduces the background error variance based on these observations. The second 3DVAR analysis uses the reduced error variance and performs velocity data assimilation using surface drifter data, and these observations further reduce the error variance of temperature and salinity for the next cycle. The second 3DVAR analysis for velocity data assimilation utilizes the new full depth error covariances. We show diagnostic results from a Gulf of Mexico simulation during extensive drifter deployments in the summer of 2020. Results reveal that the two-step data assimilation cycle applies vector velocity innovations to create increments that correct the background field towards a geostrophic balance in temperature and salinity.

Artificial-neural-network-based nonlinear algebraic models for large-eddy simulation of compressible wall-bounded turbulence

In this paper, we propose artificial-neural-network-based (ANN-based) nonlinear algebraic models for the large-eddy simulation (LES) of compressible wall-bounded turbulence. An innovative modification is applied to the invariants and the tensor bases of the nonlinear algebraic models through using the local grid widths along each direction to normalise the corresponding gradients of the flow variables. Furthermore, the dimensionless model coefficients are determined by the ANN method. The modified ANN-based nonlinear algebraic model (MANA model) has much higher correlation coefficients and much lower relative errors than the dynamic Smagorinsky model (DSM), Vreman model and wall-adapting local eddy-viscosity model in the a priori test. The significantly more accurate estimations of the mean subgrid-scale (SGS) fluxes of the kinetic energy and temperature variance are also obtained by the MANA models in the a priori test. Furthermore, in the a posteriori test, the MANA model can give much more accurate predictions of the flow statistics and the mean SGS fluxes of the kinetic energy and the temperature variance than other traditional eddy-viscosity models in compressible turbulent channel flows with untrained Reynolds numbers, Mach numbers and grid resolutions. The MANA model has a better performance in predicting the flow statistics in supersonic turbulent boundary layer. The MANA model can well predict both direct and inverse transfer of the kinetic energy and temperature variance, which overcomes the inherent shortcoming that the traditional eddy-viscosity models cannot predict the inverse energy transfer. Moreover, the MANA model is computationally more efficient than the DSM.

Development of high-resolution annual climate surfaces for Turkey using ANUSPLIN and comparison with other methods

Many climate models have been developed due to the importance of the effects of climatic factors on the physical and biological environment, e.g., rock weathering, species distribution, and growth patterns of plants. Accurate, reliable climate surfaces are necessary, especially for countries such as Turkey, which has a complex terrain and limited monitoring stations. The accuracy of these models mainly depends on the spatial modeling methods used. In this study, the Australian National University Spline (ANUSPLIN) model was used to develop climate surfaces and was compared with other methods such as inverse distance weighting, co-kriging, lapse rate, and multilinear regression. The results from the developed climate surfaces were validated using three methods: (1) diagnostic statistics from the surface fitting model, such as signal, mean, root mean square predictive error, root mean square error estimate, root mean square residual of the spline, and estimate of the standard deviation of the noise in the spline; (2) a comparison of error statistics between interpolated surfaces and the withheld climate data from 81 stations; and (3) a comparison with other interpolation methods using model performance metrics, such as mean absolute error, mean error, root mean square error, and R2adj. The most accurate results were obtained by the ANUSPLIN model. It explained 95, 88, 92, and 71% of the variance in annual mean, minimum and maximum temperature, and total precipitation, respectively. The mean absolute error of these models was 0.63, 1.16, and 0.72 ºC, as well as 54.82 mm. The generated climate surfaces, having a spatial resolution of 0.005º × 0.005º could contribute to the fields of forestry, agriculture, and hydrology.

Synthesis, spectroscopic characterization and solid-state electrical behavior of [Ni(L)2] [L = 1,2-di(4-methoxyphenyl)ethene-1,2-dithiolate]: a computational investigation on UV–vis-NIR absorption and electrical transport

A bis(dithiolene)nickel(II) complex, [Ni(L)2] (1) [L = 1,2-di(4-methoxyphenyl)ethene-1,2-dithiolate], has been synthesized and characterized using elemental analysis, UV–vis-NIR, IR, NMR spectroscopies and high resolution mass spectrometry. The geometry of the molecule was optimized using density functional theory (DFT) calculations. The calculated bond angles and distances are in agreement with the literature value. As for other dithiolenes, the present molecule absorbs extensively at 925 nm, in the near-infrared (NIR) region. A time-dependent density functional theory (TD-DFT) predicts the absorption at 1002 nm. The other absorptions are in better parity with the experimental values. In solid-state, 1 conducts electricity. The electrical conductivity of 1 rises on increasing temperature. Upon incremental changes of temperature to 200 °C, the solid-state electrical conductivity of 1 reaches 1.91 × 10−4 S/m. From electrical conductivity versus temperature plot, it is clearly found out that 1 behaves like a semiconductor. The band gap of the molecule was calculated using DFT. The calculated band gap for 1 is 0.0724922 eV which indicates that 1 deviates from metallic to semiconductor-like behavior. The thermal stability of the molecule reveals that the molecule is thermally stable to 200 °C. This is why the temperature variance of the molecular electrical conductivity was measured to this temperature.

Understanding Responses of Summer Continental Daily Temperature Variance to Perturbations in the Land Surface Evaporative Resistance

Abstract Understanding the roles of land surface conditions and atmospheric circulation on continental daily temperature variance is key to improving predictions of temperature extremes. Evaporative resistance (rs, hereafter), a function of the land cover type, reflects the ease with which water can be evaporated or transpired and is a strong control on land–atmosphere interactions. This study explores the effects of rs perturbations on summer daily temperature variance using the Simple Land Interface Model (SLIM) by mimicking, for rs only, a global land cover conversion from forest to crop/grassland. Decreasing rs causes a global cooling. The cooling is larger in wetter areas and weaker in drier areas, and primarily results from perturbations in shortwave radiation (SW) and latent heat flux (LH). Decreasing rs enhances cloud cover due to greater land surface evaporation and thus reduces incoming SW over most land areas. When rs decreases, wetter areas experience strong evaporative cooling, while drier areas become more moisture-limited and thus experience less cooling. Thermal advection further shapes the temperature response by damping the combined impacts of SW and LH. Temperature variance increases in drier areas and decreases in wetter areas as rs decreases. The temperature variance changes can be largely explained from changes in the combined variance of SW and LH, including an important contribution of changes in the covariance of SW and LH. In contrast, the effects of changes in thermal advection variance mainly affect the Northern Hemisphere midlatitudes. Significance Statement This study aims to better understand processes governing daily near-surface air temperature variance over land. We use an idealized modeling framework to explore the effects of land surface evaporative resistance (a parameter that controls how hard it is to evaporate water from the surface) on summer daily temperature variance. We find that a uniform decrease of evaporative resistance across the global land surface causes changes in the temperature variance that can be predicted from changes in the combined variance of shortwave radiation and latent heat flux. The variance of horizontal advection is important in altering the temperature variance in the Northern Hemisphere midlatitudes. Our findings shed light on predicting the characteristics of temperature variability as a function of surface conditions.

Observed Budgets of Turbulence Kinetic Energy, Heat Flux, and Temperature Variance Under Convective and Stable Conditions

Observed Budgets of Turbulence Kinetic Energy, Heat Flux, and Temperature Variance Under Convective and Stable Conditions

Subsurface imbalance stimulated in a mesoscale eddy. Part I: Observations

This study presents observational evidence of a stimulated imbalance below the mixed layer from a fast-tow cruise survey with approximately 4 km resolution that traverses a cyclonic mesoscale eddy in the central South China Sea. The observed physical and biochemical properties reveal both geostrophic and ageostrophic physics in the mesoscale eddy. In addition to the well-known eddy-induced features, banded structures of temperature and chlorophyll anomaly across the section indicate unbalanced motions. These features are notably active near the eddy's edge and show larger amplitudes of variance than those induced by the mesoscale eddy. The results also show remarkable unbalanced variances of temperature and salinity, as well as lateral temperature-salinity compensation on isopycnals, likely due to stirring associated with internal waves. Spectral analysis suggests that there exist significant unbalanced variances of temperature and chlorophyll at ∼13 km. Our further analysis suggests that symmetric instability may have been stimulated due to strong lateral buoyancy gradients and vertical shear of velocity, which may account for the imbalance signature in the pycnocline. The observed imbalances point to the instability due to the interaction between mesoscale, submesoscale, and internal wave dynamics, which may play an important role in catalyzing the forward energy cascade in the ocean.

Martian Gravity Waves Observed by the Thermal Emission Imaging System (THEMIS) During Northern Summer

AbstractMartian gravity waves (GW) greatly impact the atmospheric circulation and formation of clouds, but many GW observations of the lower atmosphere are confined to specific orientations and wavelengths, leaving many gaps in the continuum of waves. To overcome the issue, we analyze eight Mars years of data during the season of Ls = 120°–150° from Band 10 (14.9 µm) of the Thermal Emission Imaging System (THEMIS), sensitive to GWs at ∼25 km altitude. All horizontal orientations at wavelengths below ∼40 km are detectable, with the potential to detect north‐south oriented GWs up to ∼1,000 km in length. Most THEMIS observations have brightness temperature variances compatible with GW disturbances. Intense GW activity concentrates poleward of 60°S, with normalized magnitudes up to 10−4 K2 K−2; activity decreases toward the equator and remains low throughout the northern hemisphere. The interannual intensity of GWs varies by latitude within three regimes of GW length: short (<20 km), medium (20–100 km), and long (>100 km). Gravity wave orientations that are detectable in all directions do not favor a single direction; that is, Martian GWs at 25 km altitude are isotropic. Finally, interannual variability seems to emerge from interactions with dust storms, orography, and planetary waves.

Reibkoeffizientenermittlung in der Zerspanung auf Basis von Hochgeschwindigkeitsaufnahmen

The friction at the cutting wedge has a significant influence on tool wear. Due to the strong local variance of temperatures and stresses at the cutting wedge, the friction conditions differ significantly locally. In this work, a method is presented with which normal stress es, tangential stresses and local friction coefficients at the cutting wedge can be determined based on experimental investigations. For this purpose, high-speed recordings and force measurements are conducted on a planing test rig. In addition to dry cutting processes, investigations are carried out on the test rig using emulsion and oil as metal working fluid. The results show a reduction of the coefficients of friction when oil is used as metal working fluid. However, when emulsion is used as metal working fluid, the coefficient of friction changes only slightly compared to dry machining. This can be attributed to low film-forming ability of the emulsion.

The Effect of Submeso Motions on the Budgets of the Mean Turbulent Kinetic Energy and Temperature Variance in the Stable Atmospheric Surface Layer

By considering turbulence observations in the atmospheric stable surface layer over complex terrain, we study the effect of submeso motions on the budgets of the mean turbulent kinetic energy (TKE) and (half) the temperature variance. Different averaging times are considered (i.e., 100 s and 30 min), to filter out or retain the submeso contributions to second-order moments. Furthermore, results are interpreted by introducing four parameters that express the relative submeso contribution to the TKE, the temperature variance, and the vertical fluxes of heat and momentum. Four regimes are identified according to these four submeso parameters and the budgets are evaluated for these regimes. A balance among production, buoyancy (for the TKE) and dissipation occurs for the two regimes characterized by small submeso contribution to the fluxes, while an unbalance occurs for the other two regimes, where the submeso contribution to the fluxes is large. Instead, the budgets are independent of the magnitude of the submeso contribution to the TKE and the temperature variance.

Improved particle filter remaining life prediction method for switch mode power supply using variance of case temperature

Switch mode power supply plays a crucial role in industrial systems as an energy source. Its remaining life prediction is vital to help in schedule maintenance to avoid the unexpected failures of industrial systems. Due to the high cost of monitoring the degradation characterization parameter and the complexity of the degradation rule, predicting remaining life for the switch mode power supply is challenging. This study used a novel degradation characterization parameter, i.e., the variance of the case temperature, to characterize switch mode power supply degradation. Multi-stage state equations and degradation thresholds of each stage were established based on the change in the variance of the case temperature. Additionally, the state equations and degradation thresholds were introduced into the traditional particle filter method to form an improved particle filter, which is a useful life prediction method. The effect of the proposed method was evaluated and compared with other methods. The results show that over the life of a switch mode power supply, there are three change stages in the variance of the case temperature: the constant tendency stage, linear increase stage, and exponential increase stage. The degradation thresholds of these stages were 20 %, 70 %, and 200 %, respectively. The predicted curve of the variance of the case temperature was in good agreement with the test curve, and the prediction interval at a 90 % confidence level was narrow. Compared with other algorithms, the improved particle filter method could maintain the prediction error within 5 %, and was more suitable for predicting the remaining life of a switch mode power supply with multi-stage degradation characteristics.