Data-driven methods for predicting the representative temperature of bridge cable based on limited measured data

Cable-stayed bridges have been widely used in high-speed railway infrastructure.The accurate determination of cable’s representative temperatures is vital during the intricate processes of design,construction,and maintenance of cable-stayed bridges.However,the representative temperatures of stayed cables are not specified in the existing design codes.To address this issue,this study investigates the distribution of the cable temperature and determinates its representative temperature.First,an experimental investigation,spanning over a period of one year,was carried out near the bridge site to obtain the temperature data.According to the statistical analysis of the measured data,it reveals that the temperature distribution is generally uniform along the cable cross-section without significant temperature gradient.Then,based on the limited data,the Monte Carlo,the gradient boosted regression trees(GBRT),and univariate linear regression(ULR)methods are employed to predict the cable’s representative temperature throughout the service life.These methods effectively overcome the limitations of insufficient monitoring data and accurately predict the representative temperature of the cables.However,each method has its own advantages and limitations in terms of applicability and accuracy.A comprehensive evaluation of the performance of these methods is conducted,and practical recommendations are provided for their application.The proposed methods and representative temperatures provide a good basis for the operation and maintenance of in-service long-span cable-stayed bridges.

Application of Kalman Filter Method in the Forecast of Temperature in Nanchang

A temperature forecasting model was created firstly based on the Kalman filter method,and then used to predict the highest and lowest temperature in Nanchang station from October 27 to November 1,2017.Finally,according to the empirical forecasting method,guidance forecasts were established for the northern,central,and southern parts of Nanchang City.After inspection,it was found that the temperature prediction model established based on the Kalman filter method in Nanchang station had good prediction performance,and especially in the 24-hour forecast,it had advantages over the European Center.The accuracy of low temperature forecast was better than that of high temperature forecast.

Phase-field simulations of the effect of temperature and interface for zirconiumδ-hydrides

Hydride precipitation in zirconium cladding materials can damage their integrity and durability.Service temperature and material defects have a significant effect on the dynamic growth of hydrides.In this study,we have developed a phasefield model based on the assumption of elastic behaviour within a specific temperature range(613 K-653 K).This model allows us to study the influence of temperature and interfacial effects on the morphology,stress,and average growth rate of zirconium hydride.The results suggest that changes in temperature and interfacial energy influence the length-to-thickness ratio and average growth rate of the hydride morphology.The ultimate determinant of hydride orientation is the loss of interfacial coherency,primarily induced by interfacial dislocation defects and quantifiable by the mismatch degree q.An escalation in interfacial coherency loss leads to a transition of hydride growth from horizontal to vertical,accompanied by the onset of redirection behaviour.Interestingly,redirection occurs at a critical mismatch level,denoted as qc,and remains unaffected by variations in temperature and interfacial energy.However,this redirection leads to an increase in the maximum stress,which may influence the direction of hydride crack propagation.This research highlights the importance of interfacial coherency and provides valuable insights into the morphology and growth kinetics of hydrides in zirconium alloys.

Stability analysis of a liquid crystal elastomer self-oscillator under a linear temperature field

Self-oscillating systems abound in the natural world and offer substantial potential for applications in controllers,micro-motors,medical equipments,and so on.Currently,numerical methods have been widely utilized for obtaining the characteristics of self-oscillation including amplitude and frequency.However,numerical methods are burdened by intricate computations and limited precision,hindering comprehensive investigations into self-oscillating systems.In this paper,the stability of a liquid crystal elastomer fiber self-oscillating system under a linear temperature field is studied,and analytical solutions for the amplitude and frequency are determined.Initially,we establish the governing equations of self-oscillation,elucidate two motion regimes,and reveal the underlying mechanism.Subsequently,we conduct a stability analysis and employ a multi-scale method to obtain the analytical solutions for the amplitude and frequency.The results show agreement between the multi-scale and numerical methods.This research contributes to the examination of diverse self-oscillating systems and advances the theoretical analysis of self-oscillating systems rooted in active materials.

RETRACTED: Determination of the Mesalazine Solubility at Biorelevant Temperature

Short Retraction NoticeThis article has been retracted to straighten the academic record. In making this decision the Editorial Board follows COPE's Retraction Guidelines. The aim is to promote the circulation of scientific research by offering an ideal research publication platform with due consideration of internationally accepted standards on publication ethics. The Editorial Board would like to extend its sincere apologies for any inconvenience this retraction may have caused. The full retraction notice in PDF is preceding the original paper, which is marked "RETRACTED".

Magnetohydrodynamic Conjugate Free Convective Heat Transfer Analysis of an Isothermal Horizontal Circular Cylinder with Temperature Dependent Viscosity

Heat transfers due to MHD-conjugate free convection from the isothermal horizontal circular cylinder while viscosity is a function of temperature is investigated. The governing equations of the flow and connected boundary conditions are made dimensionless using a set of non-dimensional parameters. The governing equations are solved numerically using the finite difference method. Numerical results are obtained for various values of viscosity variation parameter, Prandtl number, magnetic parameter, and conjugate conduction parameter for the velocity and the temperature within the boundary layer as well as the skin friction coefficients and heat transfer rate along the surface.

Algorithms for Empirical Equations in Terms of the Cosmic Microwave Background Temperature

Previously, we presented several empirical equations using the cosmic microwave background (CMB) temperature. Next, we propose an empirical equation for the fine-structure constant. Considering the compatibility among these empirical equations, the CMB temperature (Tc) and gravitational constant (G) were calculated to be 2.726312 K and 6.673778 × 10−11 m3∙kg−1∙s−2, respectively. Every equation can be explained numerically in terms of the Compton length of an electron (λe), the Compton length of a proton (λp) and α. Furthermore, every equation can also be explained in terms of the Avogadro number and the number of electrons at 1 C. We show that every equation can be described in terms of the Planck constant. Then, the ratio of the gravitational force to the electric force can be uniquely determined with the assumption of minimum mass. In this report, we describe the algorithms used to explain these equations in detail. Thus, there are no dimension mismatch problems.

Furnace Temperature Curve Optimization Model Based on Differential Evolution Algorithm

When soldering electronic components onto circuit boards,the temperature curves of the reflow ovens across different zones and the conveyor belt speed significantly influence the product quality.This study focuses on optimizing the furnace temperature curve under varying settings of reflow oven zone temperatures and conveyor belt speeds.To address this,the research sequentially develops a heat transfer model for reflow soldering,an optimization model for reflow furnace conditions using the differential evolution algorithm,and an evaluation and decision model combining the differential evolution algorithm with the Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)method.This approach aims to determine the optimal furnace temperature curve,zone temperatures of the reflow oven,and the conveyor belt speed.

Effects of Temperature on Determination of Protein Concentration with Coomassie Brilliant Blue Method

[Objective] This study aimed to investigate the effects of temperature on determination of protein concentration with Coomassie Brilliant Blue method,thus proving advice and guidance for accurate determination of protein concentration.[Method] With Coomassie Brilliant Blue method,the concentrations of different bovine serum albumin samples were determined under different temperatures and incubation time.[Result] According to the standard curve,when the determination range of protein concentration was 0-100 mg/ml,the determined protein concentration was relatively stable after incubation at 20 ℃ for 20-30 min.Furthermore,the determination result of higher protein concentration with Coomassie Brilliant Blue method was less affected by various factors.[Conclusion] In determination of protein concentration with Coomassie Brilliant Blue method,temperature,sample concentration and incubation time were important factors affecting the accuracy of experimental results.

Calculation of effective temperature for pavement rutting using numerical simulation methods

In order to predict the long-term rutting of asphalt pavement, the effective temperature for pavement rutting is calculated using the numerical simulation method. The transient temperature field of asphalt pavement was simulated based on actual meteorological data of Nanjing. 24-hour rutting development under a transient temperature field was calculated in each month. The rutting depth accumulated under the static temperature field was also estimated and the relationship between constant temperature parameters was analyzed. Then the effective temperature for pavement rutting was determined based on the rutting equivalence principle. The results show that the monthly effective temperature is above 40 t in July and August, while in June and September it ranges from 30 to 40 Rutting development can be ignored when the monthly effective temperature is less than 30 t. The yearly effective temperature for rutting in Nanjing is around 38. 5 t. The long-term rutting prediction model based on the effective temperature can reflect the influences of meteorological factors and traffic time distribution.

Various admixtures to mitigate the long-term strength retrogression of Portland cement cured under high pressure and high temperature conditions

In order to investigate the problem of long-term strength retrogression in oil well cement systems exposed to high pressure and high temperature(HPHT)curing conditions,various influencing factors,including cement sources,particle sizes of silica flour,and additions of silica fume,alumina,colloidal iron oxide and nano-graphene,were investigated.To simulate the environment of cementing geothermal wells and deep wells,cement slurries were directly cured at 50 MPa and 200?C.Mineral compositions(as determined by X-ray diffraction Rietveld refinement),water permeability,compressive strength and Young’s modulus were used to evaluate the qualities of the set cement.Short-term curing(2e30 d)test results indicated that the adoption of 6 m m ultrafine crystalline silica played the most important role in stabilizing the mechanical properties of oil well cement systems,while the addition of silica fume had a detrimental effect on strength stability.Long-term curing(2e180 d)test results indicated that nano-graphene could stabilize the Young’s modulus of oil well cement systems.However,none of the ad-mixtures studied here can completely prevent the strength retrogression phenomenon due to their inability to stop the conversion of amorphous to crystalline phases.

The Coordinated Influence of Indian Ocean Sea Surface Temperature and Arctic Sea Ice on Anomalous Northeast China Cold Vortex Activities with Different Paths during Late Summer

The Northeast China cold vortex(NCCV)during late summer(from July to August)is identified and classified into three types in terms of its movement path using machine learning.The relationships of the three types of NCCV intensity with atmospheric circulations in late summer,the sea surface temperature(SST),and Arctic sea ice concentration(SIC)in the preceding months,are analyzed.The sensitivity tests by the Community Atmosphere Model version 5.3(CAM5.3)are used to verify the statistical results.The results show that the coordination pattern of East Asia-Pacific(EAP)and Lake Baikal high pressure forced by SST anomalies in the North Indian Ocean dipole mode(NIOD)during the preceding April and SIC anomalies in the Nansen Basin during the preceding June results in an intensity anomaly for the first type of NCCV.While the pattern of high pressure over the Urals and Okhotsk Sea and low pressure over Lake Baikal during late summer-which is forced by SST anomalies in the South Indian Ocean dipole mode(SIOD)in the preceding June and SIC anomalies in the Barents Sea in the preceding April-causes the intensity anomaly of the second type.The third type is atypical and is not analyzed in detail.Sensitivity tests,jointly forced by the SST and SIC in the preceding period,can well reproduce the observations.In contrast,the results forced separately by the SST and SIC are poor,indicating that the NCCV during late summer is likely influenced by the coordinated effects of both SST and SIC in the preceding months.

High temperature formability of graphene nanoplatelets-AZ31 composites fabricated by stir-casting method

Outstanding mechanical properties of graphene nanoplatelets(GNPs)make them ideal reinforcement for mass production of composites.In this research,the composites were fabricated by stir-casting method.GNPs were added in 1.5 and 3.0 wt.%into Mg–3wt.%Al–1wt.%Zn(AZ31)magnesium alloy.As cast ingots were preheated for one hour and extruded at 350℃ with extrusion ratio of 5.2:1.As extruded AZ31-GNPs composites were micro-structurally characterized with X-ray diffraction,optical microscopy and scanning electron microscopy.Vickers microhardness of synthesized materials was investigated both in parallel and perpendicular to extrusion directions.Room temperature mechanical testing revealed that with increasing GNP’s content,tensile fracture strain was remarkably increased without significant compromise in tensile strength.Furthermore,as extruded AZ31-3GNPs composites were subjected to tensile testing at temperatures ranging from 75℃ to 300℃ with initial strain rate of 2×10^(−3)s^(−1) to evaluate high temperature formability of composite.It was found that like CNTs,GNPs also have the potential to sustain tensile strength at high temperatures.

Influence of preparation methods on the physicochemical properties and catalytic performance of MnO_x-CeO_2 catalysts for NH_3-SCR at low temperature

This work examines the influence of preparation methods on the physicochemical properties and catalytic performance of MnOx‐CeO2 catalysts for selective catalytic reduction of NO by NH3 (NH3‐SCR) at low temperature. Five different methods, namely, mechanical mixing, impregnation,hydrothermal treatment, co‐precipitation, and a sol‐gel technique, were used to synthesizeMnOx‐CeO2 catalysts. The catalysts were characterized in detail, and an NH3‐SCR model reaction waschosen to evaluate the catalytic performance. The results showed that the preparation methodsaffected the catalytic performance in the order: hydrothermal treatment > sol‐gel > co‐precipitation> impregnation > mechanical mixing. This order correlated with the surface Ce3+ and Mn4+ content,oxygen vacancies and surface adsorbed oxygen species concentration, and the amount of acidic sitesand acidic strength. This trend is related to redox interactions between MnOx and CeO2. The catalystformed by a hydrothermal treatment exhibited excellent physicochemical properties, optimal catalyticperformance, and good H2O resistance in NH3‐SCR reaction. This was attributed to incorporationof Mnn+ into the CeO2 lattice to form a uniform ceria‐based solid solution (containing Mn‐O‐Cestructures). Strengthening of the electronic interactions between MnOx and CeO2, driven by thehigh‐temperature and high‐pressure conditions during the hydrothermal treatment also improved the catalyst characteristics. Thus, the hydrothermal treatment method is an efficient and environment‐friendly route to synthesizing low‐temperature denitrification (deNOx) catalysts.

Self-heating Probe Instrument and Method for Measuring High Temperature Melting Volume Change Rate of Material

The castings defects are affected by the melting volume change rate of material. The change rate has an important effect on running safety of the high temperature thermal storage chamber, too. But the characteristics of existing measuring installations are complex structure, troublesome operation and low precision. In order to measure the melting volume change rate of material accurately and conveniently, a self-designed measuring instrument, self-heating probe instrument, and measuring method are described. Temperature in heating cavity is controlled by PID temperature controller; melting volume change rate υ and molten density are calculated based on the melt volume which is measured by the instrument. Positive and negative υ represent expansion and shrinkage of the sample volume after melting, respectively. Taking eutectic LiF＋CaF2 for example, its melting volume change rate and melting density at 1 123 K are -20.6% and 2 651 kg/m–3 measured by this instrument, which is only 0.71% smaller than literature value. Density and melting volume change rate of industry pure aluminum at 973 K and analysis pure NaCl at 1 123 K are detected by the instrument too. The measure results are agreed with report values. Measuring error sources are analyzed and several improving measures are proposed. In theory, the measuring errors of the change rate and molten density which are measured by the self-designed instrument is nearly 1/20-1/50 of that measured by the refitted mandril thermal expansion instrument. The self-designed instrument and method have the advantages of simple structure, being easy to operate, extensive applicability for material, relatively high accuracy, and most importantly, temperature and sample vapor pressure have little effect on the measurement accuracy. The presented instrument and method solve the problems of complicated structure and procedures, and large measuring errors for the samples with high vapor pressure by existing installations.

Temperature and solar radiation utilization of rice for yield formation with different mechanized planting methods in the lower reaches of the Yangtze River,China

Several studies have demonstrated the effect of planting methods on rice yield, but information on the climate resources is limited. This study aims to reveal the effects of planting methods on climate resources associated with rice yield in a rice-wheat rotation system in the lower reaches of the Yangtze River, China. Field experiments were conducted in 2014 and 2015 with two japonica, two indica hybrid, and two japonica-indica hybrid varieties grown under three mechanized planting methods： carpet seedling of mechanical transplanting（CT）, mechanical direct seeding（DS）, and pot-hole seedling of mechanical transplanting（PT）. The rice yield and total dry matter under PT were greater than those under CT and DS methods. Besides, the entire growth duration and daily production showed significant positive relations with rice yield. Compared with CT and DS, the effective accumulated temperature and cumulative solar radiation of rice under PT were higher in phenological phases. In addition, the dry matter/effective accumulated temperature and solar energy utilization of rice under CT and DS were higher during vegetative phase and lower during reproductive and grain filling phases in contrast to PT. The mean daily temperature and mean daily solar radiation in the entire growth duration showed significant positive correlation with rice yield, total dry matter, and harvest index. This study demonstrated that when the mean daily temperature is 〈25.1°C in vegetative phase and 〉20.1°C in grain filling phase, rice yield could be increased by selecting mechanized planting methods. Most varieties under PT method exhibited high yield and climate resources use efficiency compared with CT and DS. In conclusion, the PT method could be a better cultivation measure for high rice yield, accompanied with high temperature and solar radiation use efficiency in a rice-wheat rotation system in the lower reaches of the Yangtze River, China.

Analysis of the Temperature Characteristics of High-speed Train Bearings Based on a Dynamics Model and Thermal Network Method

High-speed trains often use temperature sensors to monitor the motion state of bearings.However,the temperature of bearings can be affected by factors such as weather and faults.Therefore,it is necessary to analyze in detail the relationship between the bearing temperature and influencing factors.In this study,a dynamics model of the axle box bearing of high-speed trains is established.The model can obtain the contact force between the rollers and raceway and its change law when the bearing contains outer-ring,inner-ring,and rolling-element faults.Based on the model,a thermal network method is introduced to study the temperature field distribution of the axle box bearings of high-speed trains.In this model,the heat generation,conduction,and dispersion of the isothermal nodes can be solved.The results show that the temperature of the contact point between the outer-ring raceway and rolling-elements is the highest.The relationships between the node temperature and the speed,fault type,and fault size are analyzed,finding that the higher the speed,the higher the node temperature.Under different fault types,the node temperature first increases and then decreases as the fault size increases.The effectiveness of the model is demonstrated using the actual temperature data of a high-speed train.This study proposes a thermal network model that can predict the temperature of each component of the bearings on a high-speed train under various speed and fault conditions.

Neumann stochastic finite element method for calculating temperature field of frozen soil based on random field theory

To study the effect of uncertain factors on the temperature field of frozen soil, we propose a method to calculate the spatial average variance from just the point variance based on the local average theory of random fields. We model the heat transfer coefficient and specific heat capacity as spatially random fields instead of traditional random variables. An analysis for calculating the random temperature field of seasonal frozen soil is suggested by the Neumann stochastic finite element method, and here we provide the computational formulae of mathematical expectation, variance and variable coefficient. As shown in the calculation flow chart, the stochastic finite element calculation program for solving the random temperature field, as compiled by Matrix Laboratory （MATLAB） sottware, can directly output the statistical results of the temperature field of frozen soil. An example is presented to demonstrate the random effects from random field parameters, and the feasibility of the proposed approach is proven by compar- ing these results with the results derived when the random parameters are only modeled as random variables. The results show that the Neumann stochastic finite element method can efficiently solve the problem of random temperature fields of frozen soil based on random field theory, and it can reduce the variability of calculation results when the random parameters are modeled as spatial- ly random fields.

The Effect of Organ Temperature on Total Yield of Transplanted and Direct-Seeded Rice(Oryza sativa L.)

The canopy temperature of rice is an important index that directly reflects the growth and physiological state of rice,and affects the yield of rice plants to a great extent.The correlation between the temperatures of different rice organs and canopy in different growth stages and the grain yield is complex.The stability and universality of these correlations must be verified.We conducted a pot experiment using two rice varieties and two temperature treatments(high temperature treatment was carried out at the beginning of heading stage for 10 days).We measured rice organ temperature during seven stages of growth using a high-precision infrared thermal imager.Results showed that the optimal observation period for the rice canopy temperature was 13:00.Although the rice variety did not significantly impact the canopy or organ temperature(p>0.05),the different organs and canopy exhibited significantly different temperatures(p<0.05).The correlations between the leaf,stem,panicle,canopy–air temperature differences and seed setting rate,theoretical and actual yields were the strongest during the milk stage.Among them,the correlation coefficient betweenΔT_(s) and theoretical and actual yields was the highest,the relationship between theoretical yield(Y)andΔT_(s)(X)was Y=−5.6965X+27.778,R^(2)=0.9155.Compared withΔT_(l),ΔT_(p) andΔTc,ΔT_(s) was closely related to the main traits of plants.ΔT_(s) could better reflect the growth characteristics of rice thanΔT_(c),such as dry matter accumulation(r=−0.931),SPAD(r=0.699),N concentration(r=0.714),transpiration rate(r=−0.722).In conclusion,stem temperature was more important indicator than canopy temperature.Stem temperature is a better screening index for rice breeding and cultivation management in the future.

Analysis and comparison of spatial interpolation methods for temperature data in Xinjiang Uygur Autonomous Region, China

Spatial interpolation methods are frequently used to estimate values of meteorological data in locations where they are not measured. However, very little research has been investigated the relative performance of different interpolation methods in meteorological data of Xinjiang Uygur Autonomous Region (Xinjiang). Actually, it has importantly practical significance to as far as possibly improve the accuracy of interpolation results for meteorological data, especially in mountainous Xinjiang. There- fore, this paper focuses on the performance of different spatial interpolation methods for monthly temperature data in Xinjiang. The daily observed data of temperature are collected from 38 meteorological stations for the period 1960- 2004. Inverse distance weighting (IDW), ordinary kriging (OK), temperature lapse rate method (TLR) and multiple linear regressions (MLR) are selected as interpolated methods. Two rasterized methods, multiple regression plus space residual error and directly interpolated observed temperature (DIOT) data, are used to analyze and compare the performance of these interpolation methods respectively. Moreover, cross-validation is used to evaluate the performance of different spatial interpolation methods. The results are as follows: 1) The method of DIOT is unsuitable for the study area in this paper. 2) It is important to process the observed data by local regression model before the spatial interpolation. 3) The MLR-IDW is the optimum spatial interpolation method for the monthly mean temperature based on cross-validation. For the authors, the reliability of results and the influence of measurement accuracy, density, distribution and spatial variability on the accuracy of the interpolation methods will be tested and analyzed in the future.