Effect of changes in temperature scales on historical temperature data

2015 ◽  
Vol 36 (2) ◽  
pp. 1005-1010 ◽  
Author(s):  
P. Pavlasek ◽  
A. Merlone ◽  
C. Musacchio ◽  
Å. A. F. Olsen ◽  
R. A. Bergerud ◽  
...  
Keyword(s):  
Temperature Data ◽  
Temperature Scales ◽  
Historical Temperature

Research on Wireless Temperature Measurement System for Electrical Equipment

2014 ◽  
Vol 721 ◽  
pp. 523-526
Author(s):  
Xiang Li Wang ◽  
Yu Gui Nian ◽  
Dong Dong Cai
Keyword(s):  
Energy Efficiency ◽  
Temperature Measurement ◽  
Production Efficiency ◽  
Electrical Equipment ◽  
Temperature Data ◽  
Living Standards ◽  
Measuring Point ◽  
Measurement Software ◽  
Historical Temperature ◽  
Temperature Measurement System

As one of the important parameters for the production process of industry, agriculture and military, temperature can affect the production efficiency, energy efficiency and people’s living standards. The temperature measurement has been widely noted and studied. Firstly, the software can receive the temperature of measuring point, and store the value in the database. Secondly, when the temperature exceeds the specified range, the software will give an alarm. The software can view the historical temperature data and draw the curve of temperature. Finally, the software can query and modify the information of the measuring point, such as number, name, normal temperature range of equipment, etc. Based on the existing research results, this paper describes the design and implement of wireless temperature measurement software for electrical equipment.

scholarly journals FAO-56 Penman-Monteith DailyETofrom Linear Regression Calibrated Hargreaves Equation with Wind Terms in Tropics with Limited Data

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Eric Kra
Keyword(s):  
Linear Regression ◽  
Quadratic Function ◽  
Constant Term ◽  
Calibration Method ◽  
Temperature Data ◽  
Limited Data ◽  
Wide Range ◽  
Hargreaves Equation ◽  
Historical Temperature ◽  
Monteith Equation

Hargreaves equation (HG), which lacks a wind speed (u2) term, was modified, through a linear regression calibration method, into LHGu which hasu2terms. LHGu is effectively a simplified method for approximating FAO-56 Penman-Monteith equation (FPM) daily reference evapotranspiration (ETo) in tropics with only temperature data. In LHGu, the “0.0023” constant term in HG was calibrated as a shifted power function ofu2, and the calibration constant was parametrized as a quadratic function ofu2. LHGu was developed using simulated constantu2data and historical temperature data for four sites in West Africa: Abidjan, Accra, Daloa, and Lome. LHGu matched FPMETobetter than HG over a wide range ofu2: for Accra, foru2range 0.5–6.0 m/s, the modified coefficient of efficiency,E1, varied narrowly (0.83–0.98) for LHGu but widely (0.14–0.95) for HG optimized foru2=2.0 m/s; the corresponding MBE ranges were −0.05–0.01 mm/d for LHGu and 0.02–0.63 mm/d for HG which cannot respond to varying dailyu2. LHGu is useful for quickly computing practically accurate estimates of FPMETofor varying dailyu2where only temperature data are available.

Classification of Surface Temperature for the Flexible Pavement Design

2017 ◽  
Author(s):  
Rita Kleizienė ◽  
Audrius Vaitkus ◽  
Jurgita Židanavičiūtė ◽  
Evaldas Marcinkevičius
Keyword(s):  
Surface Temperature ◽  
Temperature Data ◽  
Pavement Design ◽  
Traffic Loading ◽  
The Road ◽  
Weather Information ◽  
Cause Of Failure ◽  
Pavement Structures ◽  
Historical Temperature ◽  
The Impact

Surface temperature significantly affects the asphalt layers modulus and entire pavement structure response to vehicles traffic loading. Because of the rheological properties of bitumen binders, the asphalt performs similarly to temperature-susceptible visco-elastic materials. The historical temperature data of local regions is necessary to design sustainable pavement structures. Likewise, the layers’ material mechanical properties determined at specific temperatures is essential for proper design too. This paper presents an analysis of pavement surface temperature classification results. Data analysis covers temperature data from the Road Weather Information Stations from the past ten years. An analysis of various temperature profile forecast methods is presented, followed by a review of recent research on the impact of temperature and cause of failure. Particular emphasis is laid on sorting the qualitative temperature data. The complete linkage clustering method had been used for establishing the most similar pairs for classification. Accordingly, the territory of Lithuania was divided into three main regions with different pavement temperature distributions for each temperature interval. Temperature classification along these lines enables pavement responses to be estimated over the pavement design life.

Quality control and homogenization of the Belgian historical temperature data

2018 ◽  
Vol 39 (1) ◽  
pp. 157-171 ◽  
Author(s):  
Charles Delvaux ◽  
Romain Ingels ◽  
Vladimír Vrábeĺ ◽  
Michel Journée ◽  
Cédric Bertrand
Keyword(s):  
Quality Control ◽  
Temperature Data ◽  
Historical Temperature

scholarly journals Stability and Complexity Analysis of Temperature Index Model Considering Stochastic Perturbation

2018 ◽  
Vol 2018 ◽  
pp. 1-18
Author(s):  
Jing Wang
Keyword(s):  
Control Method ◽  
Complexity Analysis ◽  
Stochastic Perturbation ◽  
Periodic Variation ◽  
Stability Control ◽  
Temperature Data ◽  
Anhui Province ◽  
Temperature Index ◽  
Index Model ◽  
Historical Temperature

A temperature index model with delay and stochastic perturbation is constructed in this paper. It explores the influence of parameters and stochastic factors on the stability and complexity of the model. Based on historical temperature data of four cities of Anhui Province in China, the temperature periodic variation trends of approximately sinusoidal curves of four cities are given, respectively. In addition, we analyze the existence conditions of the local stability of the temperature index model without stochastic term and estimate its parameters by using the same historical data of the four cities, respectively. The numerical simulation results of the four cities are basically consistent with the descriptions of their historical temperature data, which proves that the temperature index model constructed has good fitting degree. It also shows that unreasonable delay parameter can make the model lose stability and improve the complexity. Stochastic factors do not usually change the trend in temperature, but they can cause high frequency fluctuations in the process of temperature evolution. Stability control is successfully realized for unstable systems by the variable feedback control method. The trend of temperature changes in Anhui Province is deduced by analyzing four typical cities.

MAPPING NANTUCKET PINE TIP MOTH (LEPIDOPTERA: TORTRICIDAE) PHENOLOGY IN GEORGIA

1989 ◽  
Vol 24 (4) ◽  
pp. 405-412 ◽  
Author(s):  
Darrell W. Ross ◽  
John Pickering ◽  
Jack D. Berg ◽  
C. Wayne Berisford
Keyword(s):  
Temperature Data ◽  
Lower Threshold ◽  
Published Data ◽  
Degree Days ◽  
Thermal Requirements ◽  
Thermal Requirement ◽  
Nantucket Pine Tip Moth ◽  
Rhyacionia Frustrana ◽  
Historical Temperature

Thermal requirements for the Nantucket pine tip moth (NPTM), Rhyacionia frustrana (Comstock), to complete one generation were estimated using published data and new observations representing six unique combinations of location and year. Estimates ranged from 690 degree-days (DD) to 818 DD using a lower threshold of 9.5° C and an upper threshold of 33.5° C. Selected values within the range of estimates were used along with historical temperature data to produce maps of NPTM phenology in Georgia. The map based on the midpoint of the range of estimates (754 DD) was most closely compatible with previous observations of NPTM phenology and major physiographic boundaries. With an estimated mean thermal requirement of 754 DD, the NPTM will complete two to four generations per year in Georgia. This study demonstrates a technique that could be applied to map the phenology of any multivoltine insect for which data on thermal requirements for development are available.

An integrated simulation-based construction crew allocation and trade-off with energy and carbon footprint

2019 ◽  
Author(s):  
Hadia Awad ◽  
Mustafa Gül ◽  
Osama Mohsen ◽  
Simaan AbouRizk
Keyword(s):  
Carbon Emissions ◽  
Temperature Data ◽  
Construction Process ◽  
Simulation Methodology ◽  
Integrated Simulation ◽  
Event Simulation ◽  
House Construction ◽  
Simulation Based ◽  
Reducing Activity ◽  
Historical Temperature

On-site construction in winter consumes a considerable amount of energy and emits a significant volume of greenhouse gases, especially in cold regions. It has been reported that on-site winter heating accounts for 34% of carbon emissions of the framing phase for panelized house construction. In this paper, in order to quantify and analyze carbon emissions from on-site construction, the on-site panelized construction process is simulated in a combined discrete and continuous event simulation model based on which the possibility of reducing activity durations are investigated for the aim of reducing emissions. The integrated simulation methodology is demonstrated using case studies in Edmonton, Canada. Carbon emission which includes propane consumption for winter heating and diesel consumption for on-site mobile equipment and vehicles is calculated. Historical temperature data is analyzed to simulate weather behavior. Results show that on-site heating is the largest contributor to carbon emissions in panelized construction.

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