Dynamic thermo-mechanical responses of road-soft ground system under vehicle load and daily temperature variation

A complete road-soft ground model is established in this paper to study the dynamic responses caused by vehicle loads and/or daily temperature variation.A dynamic thermo-elastic model is applied to capturing the behavior of the rigid pavement,the base course,and the subgrade,while the soft ground is characterized using a dynamic thermo-poroelastic model.Solutions to the road-soft ground system are derived in the Laplace-Hankel transform domain.The time domain solutions are obtained using an integration approach.The temperature,thermal stress,pore water pressure,and displacement responses caused by the vehicle load and the daily temperature variation are presented.Results show that obvious temperature change mainly exists within 0.3 m of the road when subjected to the daily temperature variation,whereas the stress responses can still be found in deeper places because of the thermal swelling/shrinkage deformation within the upper road structures.Moreover,it is important to consider the coupling effects of the vehicle load and the daily temperature variation when calculating the dynamic responses inside the road-soft ground system.

April-September minimum temperature reconstruction based on Sabina tibetica ring-width chronology in the central eastern Tibetan Plateau,China

Minimum temperatures have remarkable impacts on tree growth at high-elevation sites on the Tibetan Plateau,but the shortage of long-term and high-resolution paleoclimate records inhibits understanding of recent minimum temperature anomalies.In this study,a warm season(April–September)reconstruction is presented for the past 467 years(1550–2016)based on Sabina tibetica ring-width chronology on the Lianbaoyeze Mountain of the central eastern Tibetan Plateau.Eight warm periods and eight cold periods were identified.Long-term minimum temperature variations revealed a high degree of coherence with nearby reconstructions.Spatial correlations between our reconstruction and global sea surface temperatures suggest that warm season minimum temperature anomalies in the central eastern Tibetan Plateau were strongly influenced by large-scale ocean atmospheric circulations,such as the El Ni?o-Southern Oscillation and the Atlantic Multidecadal Oscillation.

Homogenized Daily Mean/Maximum/Minimum Temperature Series for China from 1960-2008

Inhomogeneities in the daily mean/maximum/ minimum temperature （Tm/Tmax/Tmin） series from 1960- 2008 at 549 National Standard Stations （NSSs） in China were analyzed by using the Multiple Analysis of Series for Homogenization （MASH） software package. Typical biases in the dataset were illustrated via the cases of Beijing （B J）, Wutaishan （WT）, Urumqi （UR） and Henan （HN） stations. The homogenized dataset shows a mean warming trend of 0.261/0.193/0.344℃/decade for the annual series of Tm/Tmax/Tmin, slightly smaller than that of the original dataset by 0.006/0.009/0.007℃/decade. However, considerable differences between the adjusted and original datasets were found at the local scale. The adjusted Tmin series shows a significant warming trend almost everywhere for all seasons, while there are a number of stations with an insignificant trend in the original dataset. The adjusted Tm data exhibit significant warming trends annually as well as for the autumn and winter seasons in northern China, and cooling trends only for the summer in the middle reaches of the Yangtze River and parts of central China and for the spring in southwestern China, while the original data show cooling trends at several stations for the annual and seasonal scales in the Qinghai, Shanxi, Hebei, and Xinjiang provinces. The adjusted Tmax data exhibit cooling trends for summers at a number of stations in the mid-lower reaches of the Yangtze and Yellow Rivers and for springs and winters at a few stations in southwestern China, while the original data show cooling trends at three/four stations for the annual/autumn periods in the Qinghai and Yunnan provinces. In general, the number of stations with a cooling trend was much smaller in the adjusted Tm and Tmax dataset than in the original dataset. The cooling trend for summers is mainly due to cooling in August. The results of homogenization using MASH appear to be robust; in particular, different groups of stations with consideration of elevation led to minor effects in the results.

Homogenised Monthly and Daily Temperature and Precipitation Time Series in China and Greece since 1960

In this paper,we describe and analyze two datasets entitled“Homogenised monthly and daily temperature and precipitation time series in China during 1960–2021”and“Homogenised monthly and daily temperature and precipitation time series in Greece during 1960–2010”.These datasets provide the homogenised monthly and daily mean(TG),minimum(TN),and maximum(TX)temperature and precipitation(RR)records since 1960 at 366 stations in China and 56stations in Greece.The datasets are available at the Science Data Bank repository and can be downloaded from https://doi.org/10.57760/sciencedb.01731 and https://doi.org/10.57760/sciencedb.01720.For China,the regional mean annual TG,TX,TN,and RR series during 1960–2021 showed significant warming or increasing trends of 0.27℃(10 yr)^(-1),0.22℃(10 yr)^(-1),0.35℃(10 yr)^(-1),and 6.81 mm(10 yr)-1,respectively.Most of the seasonal series revealed trends significant at the 0.05level,except for the spring,summer,and autumn RR series.For Greece,there were increasing trends of 0.09℃(10 yr)-1,0.08℃(10 yr)^(-1),and 0.11℃(10 yr)^(-1)for the annual TG,TX,and TN series,respectively,while a decreasing trend of–23.35 mm(10 yr)^(-1)was present for RR.The seasonal trends showed a significant warming rate for summer,but no significant changes were noted for spring(except for TN),autumn,and winter.For RR,only the winter time series displayed a statistically significant and robust trend[–15.82 mm(10 yr)^(-1)].The final homogenised temperature and precipitation time series for both China and Greece provide a better representation of the large-scale pattern of climate change over the past decades and provide a quality information source for climatological analyses.

Application of Machine-Learning-Based Objective Correction Method in the Intelligent Grid Maximum and Minimum Temperature Predictions

Post-processing correction is an effective way to improve the model forecasting result. Especially, the machine learning methods have played increasingly important roles in recent years. Taking the meteorological observational data in a period of two years as the reference, the maximum and minimum temperature predictions of Shenyang station from the European Center for Medium-Range Weather Forecasts (ECMWF) and national intelligent grid forecasts are objectively corrected by using wavelet analysis, sliding training and other technologies. The evaluation results show that the sliding training time window of the maximum temperature is smaller than that of the minimum temperature, and their difference is the largest in August, with a difference of 2.6 days. The objective correction product of maximum temperature shows a good performance in spring, while that of minimum temperature performs well throughout the whole year, with an accuracy improvement of 97% to 186%. The correction effect in the central plains is better than in the regions with complex terrain. As for the national intelligent grid forecasts, the objective correction products have shown positive skills in predicting the maximum temperatures in spring (the skill-score reaches 0.59) and in predicting the minimum temperature at most times of the year (the skill-score reaches 0.68).

Modeling Daily Average Temperatures in a Coastal Site of Central Africa: An Analysis of Seasonal Divisions

The seasonality and day-to-day variation of near-surface temperature patterns can greatly control nearly all physical and biological processes though temperature predictions at such scales remain challenging. This paper implements a simple analytical approach in order to generate daily average temperatures which implicitly accounts for surface heating and drivers through a comprehensive representation of station-based temperature records on a universal standard calendar propagated by the earth’s dynamics features. The modeled and observed pattern of daily temperatures exhibits a close agreement with the level of strength agreement exceeding 0.56. The extreme high and low values of the observed temperature patterns are equally well captured although model underestimates the probability of temperatures around the two modal peaks (~25.6℃ and 27.5℃). Additionally, a theoretical thermal-based division led to the identification of six seasons, including two hot and cold periods along with two pairs of mixed hot-cold. The theoretical division proposed here appears to be a good approximation for the understanding of rainfall seasonality in this area.

Ratio of Gravitational Force to Electric Force from 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 could be explained in terms of the Compton length of an electron (λe), the Compton length of a proton (λp) and a. Furthermore, every equation could also be explained in terms of Avogadro’s number and the number of electrons in 1 C. However, the ratio of the gravitational force to the electric force cannot be uniquely determined when the unit of the Planck constant (Js) is changed. In this study, we showed that every equation can be described in terms of Planck constant. From the assumption of minimum mass, the ratio of gravitational force to electric force could be elucidated.

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.

Application of Multiple Analysis of Series for Homogenization to Beijing Daily Temperature Series (1960-2006)

Homogenization of climate observations remains a challenge to climate change researchers, especially in cases where metadata （e.g., probable dates of break points） are not always available. To examine the inffuence of metadata on homogenizing climate data, the authors applied the recently developed Multiple Analysis of Series for Homogenization （MASH） method to the Beijing （BJ） daily temperature series for 1960- 2006 in three cases with different references： （1） 13M-considering metadata at BJ and 12 nearby stations; （2） 13NOM-considering the same 13 stations without metadata; and （3） 21NOM-considering 20 further stations and BJ without metadata. The estimated mean annual, seasonal, and monthly inhomogeneities are similar between the 13M and 13NOM cases, while those in the 21NOM case are slightly different. The detected biases in the BJ series corresponding to the documented relocation dates are as low as -0.71~0C, -0.79~0C, and -0.5~0C for the annual mean in the 3 cases, respectively. Other biases, including those undocumented in metadata, are minor. The results suggest that any major inhomogeneity could be detected via MASH, albeit with minor differences in estimating inhomogeneities based on the different references. The adjusted annual series showed a warming trend of 0.337, 0.316, and 0.365~0C （10 yr）^（-1） for the three cases, respectively, smaller than the estimate of 0.453~0C （10 yr）^（-1） in the original series, mainly due to the relocation-induced biases. The impact of the MASH-type homogenization on estimates of climate extremes in the daily temperature series is also discussed.

Analysis of Sampling Error Uncertainties and Trends in Maximum and Minimum Temperatures in China

In this paper we report an analysis of sampling error uncertainties in mean maximum and minimum temperatures （Tmax and Tmin） carried out on monthly,seasonal and annual scales,including an examination of homogenized and original data collected at 731 meteorological stations across China for the period 1951-2004.Uncertainties of the gridded data and national average,linear trends and their uncertainties,as well as the homogenization effect on uncertainties are assessed.It is shown that the sampling error variances of homogenized Tmax and Tmin,which are larger in winter than in summer,have a marked northwest-southeast gradient distribution,while the sampling error variances of the original data are found to be larger and irregular.Tmax and Tmin increase in all months of the year in the study period 1951-2004,with the largest warming and uncertainties being 0.400℃ （10 yr）-1 ＋ 0.269℃ （10 yr）-1 and 0.578℃ （10 yr）-1 ＋ 0.211℃ （10 yr）-1 in February,and the least being 0.022℃ （10 yr）-1 ＋ 0.085℃ （10 yr）-1 and 0.104℃ （10 yr）-1 ＋0.070℃ （10 yr）-1 in August.Homogenization can remove large uncertainties in the original records resulting from various non-natural changes in China.

Effect of elevated temperature and silica sand particle size on minimum fluidization velocity in an atmospheric bubbling fluidized bed

The impact of temperature and particle size on minimumfluidizing velocity was studied and analyzed in a small pilot scale of bubbling fluidized bed reactor.This study was devoted to providing some data about fluidization to the literature under high temperature conditions.The experiments were carried out to evaluate the minimum fluidizing velocity over a vast range of temperature levels from 20℃ to 850℃ using silica sand with a particle size of 300-425μm,425-500μm,500-600μm,and 600-710μm.Furthermore,the variation in the minimumfluidized voidage was determined experimentally at the same conditions.The experimental data revealed that the Umf directly varied with particle size and inversely with temperature,whileεmf increases slightly with temperature based on the measurements of height at incipient fluidization.However,for all particle sizes used in this test,temperatures above 700℃ has a marginal effect on Umf.The results were compared with many empirical equations,and it was found that the experimental result is still in an acceptable range of empirical equations used.In which,our findings are not well predicted by the widely accepted correlations reported in the literature.Therefore,a new predicted equation has been developed that also accounts for the affecting of mean particle size in addition to other parameters.A good mean relative deviation of 5.473% between the experimental data and the predicted values was estimated from the correlation of the effective dimensionless group.Furthermore,the experimental work revealed that the minimum fluidizing velocity was not affected by the height of the bed even at high temperature.

Performance evaluation of minimum quantity lubrication by vege-table oil in terms of cutting force,cutting zone temperature,tool wear,job dimension and surface finish in turning AISI-1060 steel

In all machining processes, tool wear is a natural phenomenon and it leads to tool failure. The growing demands for high productivity of machining need use of high cutting velocity and feed rate. Such machining inherently produces high cutting temperature, which not only reduces tool life but also impairs the product quality. Metal cutting fluid changes the performance of machining operations because of their lubrication, cooling and chip flushing functions, but the use of cutting fluid has become more problematic in terms of both employee health and environmental pollution. The minimization of cutting fluid also leads to economical benefits by way of saving lubricant costs and workpiece/tool/machine cleaning cycle time. The concept of minimum quantity lubrication (MQL) has been suggested since a decade ago as a means of addressing the issues of environmental intru- siveness and occupational hazards associated with the airborne cutting fluid particles on factory shop floors. This paper deals with experimental investigation on the role of MQL by vegetable oil on cutting temperature, tool wear, surface roughness and dimen- sional deviation in turning AISI-1060 steel at industrial speed-feed combinations by uncoated carbide insert. The encouraging results include significant reduction in tool wear rate, dimensional inaccuracy and surface roughness by MQL mainly through reduction in the cutting zone temperature and favorable change in the chip-tool and work-tool interaction.

The efficacy of Kriging spatial interpolation for filling temporal gaps in daily air temperature data: A case study in northeast China

Quality-controlled and serially complete daily air temperature data are essential to evaluating and modelling the influences of climate change on the permafrost in cold regions. Due to malfunctions and location changes of observing stations, temporal gaps （i.e., missing data） are common in collected datasets. The objective of this study was to assess the efficacy of Kriging spatial interpolation for estimating missing data to fill the temporal gaps in daily air temperature data in northeast China. A cross-validation experiment was conducted. Daily air temperature series from 1960 to 2012 at each station were estimated by using the universal Kriging （UK） and Kriging with an external drift （KED）, as appropriate, as if all the ob-servations at a given station were completely missing. The temporal and spatial variation patterns of estimation uncertainties were also checked. Results showed that Kriging spatial interpolation was generally desirable for estimating missing data in daily air temperature, and in this study KED performed slightly better than UK. At most stations the correlation coefficients （R2） between the observed and estimated daily series were 〉0.98, and root mean square errors （RMSEs） of the estimated daily mean （Tmean）, maximum （Tmax）, and minimum （Tmin） of air temperature were 〈3 ℃. However, the estimation quality was strongly affected by seasonality and had spatial variation. In general, estimation uncertainties were small in summer and large in winter. On average, the RMSE in winter was approximately 1 ℃ higher than that in summer. In addition, estimation uncertainties in mountainous areas with complex terrain were significantly larger than those in plain areas.

Minimum and Maximum Temperature Trends in Congo-Brazzaville: 1932-2010

Maximum and minimum temperatures time series of Congo-Brazzaville are analyzed for trend and discontinuities over the period 1932 to 2010. Temperatures series show an irregular increase. A total of 8 synoptic stations show positive trends in their annual mean maximum temperature series, and 7 of them are significant, with higher trends for urban stations. Annual mean minimum temperature showed 6 stations having positive trends. This increase is in relation with observations at regional scale. However, the differences are observed between large towns (Brazzaville and Pointe-Noire), and small or rural towns (Dolisie, Sibiti, Impfondo, Djambala). Trends in diurnal temperature range (DTR) are large positive trends in maximum temperature that are mainly observed in cities. The curve of DTR shows a decreasing trend which indicates the increasing of minimum temperatures. The effects of urbanization on temperature trends are investigated. Most stations regarded as urban stations are still useful for trend analysis;being situated on the suburban of the studied cities, they are therefore, not substantially influenced by the urban heat island.

The relation between ambulance transports due to heat stroke and air temperature using daily data in Okayama prefecture, Japan

The aim of this study was to investigate the link between ambulance transports due to heat stroke and air temperature by using daily data of ambulance transports in Okayama prefecture, Japan. Daily observations for ambulance transports due to heat stroke from July to September in 2010 in Okayama prefecture, Japan were obtained from Fire and Disaster Management Agency in Japan. Data of meteorological parameters in Okayama prefecture, Japan were also obtained from Japan Meteorological Agency. Effect of meteorological parameters on ambulance transports due to heat stroke was analyzed. A total of 1133 ambulance transports due to heat stroke were observed in from July to September of 2010 in Okayama prefecture, Japan. Ambulance transports due to heat stroke was significantly correlated with air temperature. In addition, number of subjects with ambulance transports due to heat stroke over 34°C in the highest air temperature was 21.2 ± 9.8 per day. Higher air temperature was closely associated with higher ambulance transports due to heat stroke by using daily data in Okayama, prefecture, Japan.

Study on Refined Forecast Method of Daily Maximum Temperature in Wugang City from July to September

[Objective] The aim was to study the refined forecast method of daily highest temperature in Wugang City from July to September. IM[ethod] By dint of ECMWF mode product and T231 in 2009 and 2010 and daily maximum temperature in the station in corresponding period, multi-factors similar forecast method to select forecast sample, multivariate regression multi-mode integration MOS method, after dynamic corrected mode error and regression error, dynamic forecast equation was concluded to formulate the daily maximum temperature forecast in 24 -120 h in Wugang City from July to September. [ Result] Through selection, error correction, the daily maximum temperature equation in Wugang City from July to September was concluded. Through multiple random sampling, F test was made to pass test with significant test of 0.1. [ Conclusionl The method integrated domestic and foreign forecast mode, made full use of useful information of many modes, absorbed each others advantages, con- sidered local regional environment, lessen mode and regression error, and improved forecast accuracy.

Diurnal Temperature Range and Daily Emergency Room Admissions among the Elderly in Beijing,China

In recent years, more attentions have been paid to the association between climate change and human health. Increasing and more variable global surface temperature is one of the key climatic change factors which have been consistently reported about the effect on human health. So far, more researches have revealed that temperature lead not only to direct deaths and illnesses but also to aggravation of cardiovascular and respiratory diseases. Typically, the relationship between temperature and mortality or morbidity is V-, U-, or J- shaped, with optimum temperature corresponding to the lowest point in the temperature mortality curve.

Asymmetrical Change Characteristics of Maximum and Minimum Temperatures in Shangqiu in Recent 50 Years

[Objective] The research aimed to analyze temporal and spatial variation characteristics of temperature in Shangqiu City during 1961-2010.[Method] Based on temperature data in eight meteorological stations of Shangqiu during 1961-2010,by using trend analysis method,the temporal and spatial evolution characteristics of annual average temperature,annual average maximum and minimum temperatures,annual extreme maximum and minimum temperatures,daily range of annual average temperature in Shangqiu City were analyzed.M-K method was used to determine mutation year of temperature.[Result] The annual average temperature,annual average minimum temperature and annual extreme minimum temperature respectively rose at 0.122,0.255 and 0.488 ℃/10 a.The variation trend of annual average maximum temperature wasn’t obvious.The daily range of annual average temperature and annual extreme maximum temperature respectively declined at-0.217 and-0.292 ℃/10 a.Seen from spatial distribution,the increase amplitudes of annual average temperature,annual average minimum temperature and annual extreme minimum temperature were all large in the east and small in the west.The decrease amplitude of daily range of annual average temperature was large in the east and small in the west.The decrease amplitude of annual extreme maximum temperature was large in the west and small in the east.The annual average maximum temperature had trends of increase and decrease.The annual average temperature,annual average minimum temperature and daily range of annual average temperature all mutated in 1997.The annual average maximum temperature didn’t have obvious mutation point.The annual extreme maximum temperature mutated in 1973.The annual extreme minimum temperature respectively mutated in 1989 and 1999.[Conclusion] The research played important guidance significances in adjustment of agricultural production structure,regional climate planning,reasonably using climate resource and replying climate change in Shangqiu City.

Prediction of Minimum Spouting Velocity at Elevated Pressures and Temperatures

Minimum spouting velocity （Ums） is one of the most important flow characteristics for proper design and operation of spouted bed reactors. Many correlations for Ums have been published since spouted bed technology was initiated in 1955. In this paper, a new correlation is developed for Ums based on 767 published experimental data covering both high pressure and high temperature conditions. The calculated and the measured results of Ums are in better agreement than other published correlations.

Change in summer daily precipitation and its relation with air temperature in Northwest China during 1957–2016

On the basis of the summer daily-precipitation meteorological data collected from weather stations across Northwest China from 1957 to 2016, this study evaluated the trends in 12-daily precipitation indices in the summer season and their relations with air temperature. Precipitation-event intensity, which was averaged over the total study area, increased in recent decades although the total precipitation continuously decreased. In particular, intensity generally decreased in the northern and eastern parts and increased in the southern and western parts of the study area. None of the 12 precipitation indices was significantly correlated with temperature in Xinjiang; R95 N(number of events with precipitation greater than the long-term95 th percentile), RX1 day(greatest 1-day total precipitation), PI(simple daily intensity), and R10(number of heavy-precipitation days) were significantly and positively correlated with temperature in Qinghai–Gansu. However, low correlation coefficients were observed. In the Loess Plateau, P(total precipitation), WS(maximum number of consecutive wet days),R95 N, and WD(number of wet days) were significantly and negatively correlated with temperature, whereas Gini(gini concentration index) and DS(maximum number of consecutive dry days) were significantly and positively correlated with temperature. Results of the study suggested that climate shift was evident in terms of daily precipitation, and the study area faced new challenges involving precipitation-event intensity increasing in the southwestern part and unevenly dispersing in the northwest.