Hourly Values Research Articles

Importance of solar radiation and the need for improved respect to Sun by Agrometeorologists

Solar radiation refers to energy produced by the Sun, some of which reaches the Earth. This is the primary energy source for most processes in the atmosphere, hydrosphere, and biosphere. Solar radiation is of crucial importance inproviding the energy source for photosynthesis. During 1973 to 1977, when I did my Ph.D. in Agroclimatology in the Iowa State University, USA, I conducted the field experiments during 1975 and 1976 on soil-plant-water relations, growth and nutrient uptake patterns of field grown soybeans under water stress at the Western Iowa Experimental Farm, Castana. During these experiments, the solar radiation was measured with a pyranometer sensor mounted on an anodized aluminimum base. Daily solar radiation values were obtained from an LI-500 integrator attached to the pyranometer sensor. The attenuation of photosynthetically active radiation (PAR) and net radiation (NRAD) in the soybean canopy was determined during the growing season by using vertical profiles of radiation and leaf-area-index values. Once I received my Ph.D., I worked at the Headquarters of the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) in Hyderabad from 1977 to 1983 and at the ICRISAT Sahelian Center, Niamey, Niger from 1984 to 1996. In several field experiments in ICRISAT, the hourly values of net radiation were obtained through net radiometers mounted above the crop canopies. The growth and interception of PAR in a maize/pigeonpea intercrop and sole maize and sole pigeonpea crops grown in large plots were compared. The productivity of maize, sorghum, pigeonpea and a maize/pigeonpea intercrop in the operational research watersheds was measured in relation to the interception of PAR. In another study, it was shown that different shading ability of the crop canopies was one of the factors which determined the crop/weed competition balance and thus contributed to differential crop productivity observed in different cropping systems. Afterwards, when I worked at the World Meteorological Organization from 1996 to 2016 as the Chief of the Agricultural Meteorology Department, as the Director of the Climate Prediction and Adaptation Branch and as the Acting Secretary of the Intergovernmental Panel on Climate Change, a lot of work was done on Solar Radiation. Given all the above work on Solar Radiation, I emphasized the need for improved respect to Sun Bhagawan by Agrometeorologists at the end of this article.

Sedation protocols in non-traumatic SAH (SPRINT-SAH): A cross-sectional survey among German-speaking neurointensivists.

In subarachnoid hemorrhage (SAH), titrating sedation to find a balance between wakefulness with the ability to perform valid clinical examinations on the one hand, and deep sedation to minimize secondary brain damage, on the other hand, is challenging. However, data on this topic are scarce, and current guidelines do not provide recommendations for sedation protocols in SAH. We designed a web-based, cross-sectional survey for German-speaking neurointensivists to map current standards for the indication and monitoring of sedation, duration of prolonged sedation, and biomarkers for the withdrawal of sedation. Overall, 17.4% (37/213) of neurointensivists answered the questionnaire. Most of the participants were neurologists (54.1%, 20/37) and exhibited a long-standing experience in intensive care medicine (14.9 years, SD 8.3). Among indications for prolonged sedation in SAH, the control of intracranial pressure (ICP) (94.6%) and status epilepticus (91.9%) were most significant. With regard to further complications in the course of the disease, therapy refractory ICP (45.9%, 17/37) and radiographic surrogates of elevated ICP, such as parenchymal swelling (35.1%, 13/37), were the most relevant topics for experts. Regular awakening trials were performed by 62.2% of neurointensivists (23/37). All participants used clinical examination for the therapeutic monitoring of sedation depth. A total of 83.8% of neurointensivists (31/37) used methods based on electroencephalography. As a mean duration of sedation before attempting an awakening trial in patients with unfavorable biomarkers, neurointensivists suggested 4.5 days (SD 1.8) for good-grade SAH and 5.6 days (SD 2.8) for poor-grade SAH, respectively. Many experts performed cranial imaging before the definite withdrawal of sedation [84.6% (22/26)], and 63.6% (14/22) of the participants required an absence of herniation, space-occupying lesions, or global cerebral edema. The values of ICP tolerated for definite withdrawal were smaller compared to that of awakening trials (17.3 mmHg vs. 22.1 mmHg), and patients were required to stay below the threshold value for several hours (21.3 h, SD 10.7). Despite the paucity of clear recommendations for sedation management in SAH in the pre-existing literature, we found some level of agreement indicating clinical efficacy for certain clinical practices. By mapping the current standard, this survey may help to identify controversial aspects in the clinical care of SAH and thereby streamline future research.

Performance investigation and estimation of the 1 kWp photovoltaic array for an isolated hilly area in India

AbstractThis paper presents the assessment of solar resources, investigation of performance, and estimation of normalized performance indices of a 1 kWp Solar PV system in India's climatology of an isolated hilly area. The monthly and yearly mean normalized performance indices are estimated. The annual mean values of the daylight hours, cell temperature, and ambient temperature are 12.7 h/d, 10.89°C, and 1.25°C, respectively. The yearly mean values and corresponding ranges of monthly mean values of capacity factor, performance ratio, array yield, reference yield, final yield, array capture loss and system loss are obtained as 23.60%, 59.82%, 2.83 h/d, 4.63 h/d, 2.69 h/d, 1.8 h/d, 0.14 h/d and (17.56–29.07)%, (47.93–75.55)%, (2.24–3.42) h/d, (2.85–6.1) h/d, (2.13–3.25) h/d, (0.60–2.99) h/d and (0.11–0.17) h/d, respectively. The Levelized Cost of energy is reduced to 85% and 68.22% by using the proposed solar PV/ battery system compared to DG and DG/Battery systems. A saving of 14.8 kl of diesel and the corresponding reduction of emissions of carbon monoxide (244.22 kilograms), unburned hydrocarbons (10.66 kg), particulates (1.48 kg), and nitrogen Oxides (229.42 kg) have also been achieved per year. These findings effectively provide optimal power solution strategies for policymakers in the concerned area.

Can synoptic drivers explain rotor‐area wind conditions and predict energy output?

AbstractSynoptic‐scale weather patterns are an important driver of wind speed at turbine hub height, but wind energy generation is also affected by the wind profile across the rotor. In this research, we use a 6‐year record of hourly profile measurements at the Eolos Wind Research Station in Minnesota, USA, to investigate whether synoptic weather patterns can provide information about rotor‐area characteristics in addition to hub‐height wind speed. We use sea level pressure data from the MERRA‐2 reanalysis to classify synoptic patterns at the Eolos site into 15 synoptic types and use the Eolos wind profile data to create mean hourly and mean monthly values of wind speed and turbulence intensity at hub height (80 m), and wind speed shear, wind direction shear, and the potential temperature gradient across the rotor (30–129 m), for each synoptic type. Using a simple linear regression model, we find that, at monthly time scales, wind speed, turbulence intensity, and wind speed shear across the rotor are the most important variables for predicting monthly wind energy output from the Eolos turbine. Regression models using the original Eolos data and the derived synoptic types capture about 64% and 55% of the variance in monthly energy output, respectively. When fewer than the full 6 years of observations are used to fit the regression model, however, predictions using the synoptic types slightly outperform predictions using the Eolos observations. These results suggest that seasonal energy projections may be enhanced by incorporating wind profile measurements with synoptic‐scale drivers.

Activity and composition of the hyperactive comet 46P/Wirtanen during its close approach in 2018

Context. Hyperactive comets are a small group of comets whose activity is higher than expected. They seem to emit more water than would normally be expected given the size of their nucleus. Comet 46P/Wirtanen (hereafter, 46P) is among these objects of interest. Investigating its activity and composition evolution could provide clues about its origins and its formation region in the Solar nebulae. Aims. Given the exceptional close approach of comet 46P to the Earth in 2018, we aim to study the evolution of its activity and composition as a function of heliocentric distances before and after perihelion. Methods. We used both TRAPPIST telescopes to monitor the comet for almost a year with broad and narrow-band filters. We derived the production rates of five gaseous species (OH, NH, CN, C3, and C2) using a Haser model as well as the A(θ)fρ dust proxy parameter. The comet was also observed with the two optical high-resolution spectrographs UVES and ESPRESSO, mounted on the 8-m ESO VLT, to measure the isotopic ratios of C and N, along with the oxygen forbidden-line ratios and the NH2 ortho-to-para ratios. Results. Over nearly a year, we followed the rise and decline of the production rates of different species as well as the dust activity of 46P on both pre- and post-perihelion. Relative abundances with respect to CN and OH along the orbit of the comet show constant and symmetric abundance ratios and a typical coma composition. We determined the rotation period of the nucleus using high-cadence observations and long series of CN images on several nights. We obtained a value of (9.18±0.05) hours at perihelion. Using the high-resolution spectra of 46P coma, we derived C and N isotopic ratios of 100±20 and 150±30 as well as a green-to-red forbidden oxygen [OI] line ratio of 0.23±0.02. We measured a NH2 ortho-to-para ratio of 3.31 ±0.03 and derived an ammonia ratio of 1.19±0.03, corresponding to a spin temperature of 27±1 K. Conclusions. Narrow-band observations show that comet 46P is a hyperactive comet for which 40% of its nucleus surface is active. It has a typical composition, similar to other normal comets; however, an asymmetric behavior with respect to perihelion has been seen in its activity, which is typical of seasonal effects. Photometric measurements show no evidence for a change in the rotation period of the nucleus during this apparition. High-resolution spectra show that 46P has typical NH2 ortho-to-para, [OI] lines ratios, and C and N isotopic ratios.

MONITORING SUMMER SOLAR ULTRAVIOLET (UV) RADIATION ON THE GROUND LEVEL OVER ARDABIL-SAREIN, NW IRAN

Abstract. The UV radiation level at the Earth’s surface is generally affected by several factors such as time, geographic location, and climate. The first observations of solar UV radiation ever made in NW Iran, obtained in June 2019 are reported in this work. The analysis of hourly values of UV irradiances measured in the study area reveals significant diurnal variation during daylight hours, with lower values in the morning and afternoon and higher around noon. Mean hourly UV (A+B) ranged from 2755 to 10434 µW/cm2 with an average value being about 7960 µW/cm2. Mean hourly UV (C) ranged from 40 to 91 µW/cm2 with an average value being about 76 µW/cm2. The results of a short but intense measurement campaign in Ardabil-Sarein indicate the trends for geographical latitude, longitude, and altitude from surface UV measurements. The UV intensity is associated with geographical longitude (r2= 0.15 for UV (A+B); r2= 0.13 for UV (C)). Furthermore, UV intensity varies with the local latitude in the study area. There is a strong linear relationship between average UV and altitude and a trend of rising UV with increasing altitude is obtained. A decrease in UV radiation with increasing solar zenith (°) was observed. However, the correlation between UV radiation and solar azimuth (°) was not significant. Understanding the factors influencing near-surface UV radiation through systematic ground-based UV will help determine whether long-term changes occur as a result of changes in cloud cover or climate change, and how specific it means to identifying the causes.

Estimating the Monetary Value of Hours Lost to the Nigerian Public Healthcare System When Full-Time Government Employee Doctors Engage in Dual Practice

Background: Dual Practice (DP) allows full-time public sector doctors to concurrently offer the same clinical services in the private sector. The debate against this practice seems to be largely influenced by its potential to reduce the contracted hours in the public sector and shift attention to private work. Purpose: The purpose of this secondary research is to estimate the monetary value of hours lost to the Nigerian public healthcare system when full-time government employee doctors are engaged in private practice. It attempts to quantify the amount of resource outflow from the public system due to absences and lateness arising from competition for time between the public system’s contracted hours and private practice. Methods: Sensitivity analysis in Excel 2010 was used to calculate doctors’ hourly pay in the public sector using the 2015 Consolidated Medical Salary Structure for medical and dental officers in Nigeria’s federal public service. The parameters used for the calculation were the official 40-hour working week and the average monthly gross pay of doctors on different grade levels. Hypothetical scenarios of hours lost due to absences associated with DP were created. The value of different hypothetical hour losses by the percentage of doctors assumed to engage in dual practice across all doctor grade levels was then computed. Results: The estimated annual value of hours lost from dual practice to a single public tertiary care hospital was N4,851,754 or 15,855 USD (best case scenario) and N19,407,017 or 63,422 USD (worst case scenario) for the normal routine work and N1,800,133 or 5883 USD (best case scenario) and N3,600,266 or 11,766 USD (worst case scenario) for the on-call duty. Conclusion: The government may have been paying salaries for large volumes of work not rendered in the public sector. The overall financial impact of dual practice in the Nigerian public system might be negative.

The impact of crisis phenomena on economic security in the automotive industry and the quality of life of employees

The quality of life of people inter alia depends on their economic well-being. The direct source of their well-being is their wage paid by employers. Any economic crisis that impacts the biggest industrial employers in a region directly translates into the deteriorated quality of life of people. This article describes several transmission channels of the two major global crises which have been following covid pandemic and military conflict in Ukraine. Transmission of crisis phenomena into the well-being of people is provided by explaining the importance of the automotive industry for the Slovak Republic and the values of employment and hours worked indices are provided as supporting evidence. The mechanism of increased scarcity is described in the case of increased raw material prices on the global market which resulted in the decreased production in the automotive industry.

Computerized insulin protocol for intrapartum and postpartum glucose management in gravidas with Type 1 diabetes

Computerized insulin infusion calculators (IICC) improve glucose control in non-pregnant populations. Our IICC is an insulin sensitivity coefficient-based algorithm relying on point of care (POC) glucose values and the rate of change which allows for dynamic changes in insulin resistance. We evaluated the effectiveness of an IICC in achieving intrapartum and postpartum euglycemia in gravidas with Type 1 diabetes mellitus (T1DM). This retrospective study included gravidas with T1DM managed intrapartum and postpartum with IICC between 2016-2020. Patients were excluded if insulin infusion or POC glucose values were not available. Insulin infusion rate, POC glucose and neonatal data were obtained from the electronic medical record. Our primary outcome was the percentage of hourly glucose values within goal in the intrapartum period (80-119 mg/dL), and postpartum period (80-179 mg/dL). Secondary outcomes included intrapartum mild hyperglycemia (120-179 mg/dL) and hypoglycemia (< 60 mg/dL), hyperglycemia (≥ 180 mg/dL) for both time periods, and select neonatal outcomes. 39 patients (47 pregnancies) were included for analysis. Mean maternal age was 29.5 ± 5.3 years and first trimester HbA1c was 7.2 ± 1.4%. 39.3% (n=471) of the intrapartum glucose values and 68.7% (n=929) of the postpartum glucose values were in target (p< .0001)(Figure 1). The incidence of intrapartum mild hyperglycemia was 545 (46.3%). The incidence of hypoglycemia was 2.7% for both time periods while the incidence of hyperglycemia was 9.3% and 18.6% intrapartum and postpartum, respectively. Figure 2 shows the mean POC glucose values. Twenty-four (51.1%) neonates were admitted to the neonatal intensive care unit and 22 (46.8%) had hypoglycemia requiring dextrose infusion. To our knowledge, this is the first descriptive study of IICC use intrapartum and postpartum. The IICC performed better at achieving postpartum versus intrapartum glucose control, while having low rates of hyperglycemia and hypoglycemia. Development of a pregnancy specific IICC may improve peripartum glycemic control.View Large Image Figure ViewerDownload Hi-res image Download (PPT)

Analysis of temporary variability of the total intensity of solar radiation when assessing energy resources

The results of the analysis of temporary variability of average monthly and annual amounts of solar radiation in Ukraine for the period 2011-2020 are presented. Measurement data were compared with earlier periods and the standard period of 1961-1990. The statistical characteristics of the series of changes in solar radiation have been determined. Comparison of the characteristics of solar radiation with the normative data of SSU NBV .1.1-27-2010 was made. It has been shown that in recent years the annual amounts of direct radiation have increased by 18-23%. The total annual radiation in 2020 increased by 6% according to the period 1961-1990. The analysis of the calculated results of determining hourly values and daily sums of direct and scattered radiation obtained using empirical dependencies of engineering methods is carried out. The efficiency of using the sustainable potential of solar energy depends on the climatic characteristics of this area or region. Inconsistencies in regulations can therefore create a problem where the best places for energy production lack public interest, infrastructure and cost-effective consumption. Depending on the regional climatic conditions of Ukraine, the solar energy potential varies from 1400 MJ/m2 in the western regions to 1950 MJ/m2 in the eastern regions. An important characteristic of solar energy resources is the duration of sunshine. For the conditions of Kyiv, the average monthly value of the actual duration varies from 180 hours in March to 120 hours in November. The possible annual duration of sunshine varies accordingly from 4452 hours (2011) to 4481 hours (2020). The maximum values are observed in June (331 hours) and August (334 hours). In the southern regions of Ukraine, the actual annual duration of sunshine for Odesa conditions varies from 2387 hours (2011) to 2709 hours (2020). The criterion for the expediency of using solar energy is the annual number of clear days of more than 200. The number of clear days is not given in SSU.

Relationship between running performance and weather in elite marathoners competing in the New York City Marathon

It is well known that weather and pacing have an influence on elite marathon performance. However, there is limited knowledge about the effect of weather on running speed in elite marathoners. The aim of the present cross-sectional study was to investigate potential associations between running speed and weather variables in elite runners competing in the 'New York City Marathon' between 1999 and 2019. Data from all official female and male finishers with name, sex, age, calendar year, split times at 5km, 10km, 15km, 20km, 25km, 30km, 35km, 40km and finish and hourly values for temperature (°Celsius), barometric pressure (hPa), humidity (%) and sunshine duration (min) between 09:00 a.m. and 04:00 p.m. were obtained from official websites. A total of 560,731 marathon runners' records were available for analysis (342,799 men and 217,932 women). Pearson and Spearman correlation analyses were performed between the average running speed and the weather variables (temperature, pressure, humidity and sunshine). Ordinary Least Squares (OLS) regressions were also performed. The runner´s records were classified into four performance groups (all runners, top 100, top 10 and top 3) for comparison. Differences in running speed between the four performance groups were statistically significant (p < 0.05) for both men and women. Pearson (linear) correlation indicated a weak and positive association with humidity in the top 10 (r = 0.16) and top 3 (r = 0.13) performance groups that the running speed of the elite runners was positively correlated with humidity. Regarding sunshine duration, there was a weak and positive correlation with the running speed of the elite groups (r = 0.16 in the top 10 and r = 0.2 in the top 3). Spearman correlation (non-linear) identified a weak but negative correlation coefficient with temperature in all runners' groups. Also, non-linear positive correlation coefficients with humidity and sunshine can be observed in the Spearman matrixes. A Multivariate Ordinary Least Squares (OLS) regression analysis showed no predictive power of weather factors. For elite runners competing in the 'New York City Marathon' between 1999 and 2019, the main findings were that elite runners became faster with increasing humidity and sunshine duration while overall runners became slower with increasing temperature, increasing humidity and sunshine duration. Weather factors affected running speed and results but did not provide a significant predictive influence on performance.

The Effect of European Climate Change on Indoor Thermal Comfort and Overheating in a Public Building Designed with a Passive Approach

Dynamic building energy performance modeling is becoming increasingly important in the architectural, engineering, and construction (AEC) industry because of the sector’s significant environmental impact. For such analysis, a climate file representing a typical meteorological year (TMY) is needed, including hourly values for the most important weather-related parameters. However, TMY shows little resemblance to the future of the particular location where a building has been used for decades. Therefore, using predicted future climates during building design is unfortunately rarely practiced, potentially undermining the strategies that should be the fundamental basis of the design. To explore this question, our study compared the heating and cooling energy consumption, indoor thermal comfort, and summer overheating potential of a selected building for three distinctive European climates, in Hungary, Portugal, and Lithuania. All of them were changed according to the IPCC RCP4.5 scenario, and were examined for the present, the 2050, and the 2100 scenarios. We also tested adaptive clothing to evaluate the indoor comfort parameters. The results show a 10% increase in heating and cooling energy use for the same construction and location between 2020 and 2100. The continental climate of Budapest is the most threatened by summer overheating, with an increase of 69% for the ODH26 indicator. A more balanced warming for Lisbon was found (23%), and moderate changes for the city of Kaunas (a 153% increase from a very low baseline).

A hierarchical classification/regression algorithm for improving extreme wind speed events prediction

A novel method for prediction of the extreme wind speed events based on a Hierarchical Classification/Regression (HCR) approach is proposed. The idea is to improve the prediction skills of different Machine Learning approaches on extreme wind speed events, while preserving the prediction performance for steady events. The proposed HCR architecture rests on three distinctive levels: first, a data preprocessing level, where training data are divided into clusters and accordingly associated labels. At this point, balancing techniques are applied to increase the significance of clusters with poorly represented wind gusts data. At a second level of the architecture, the classification of each sample into the corresponding cluster is carried out. Finally, once we have determined the cluster a sample belongs to, the third level carries out the prediction of the wind speed value, by using the regression model associated with that particular cluster. The performance of the proposed HCR approach has been tested in a real database of hourly wind speed values in Spain, considering Reanalysis data as predictive variables. The results obtained have shown excellent prediction skill in the forecasting of extreme events, achieving a 96% extremes detection, while maintaining a reasonable performance in the non-extreme samples. The performance of the methods has also been assessed using forecast data (GFS) as predictors.

Analisis Toksisitas Akut LC50-96 Jam Limbah Laundri Terhadap Ikan Mujair (Oreochromis sp.)

Laundry waste is one of the wastes that is wasted when it is disposed of continuously and continuously. This results in the destruction of aquatic ecosystems, especially fish. This study aims to determine the value of LC50-96 hours of laundry waste on tilapia fish (Oreochromis sp.). This study begins by knowing the parameters of BOD, COD, TSS, NH3, and detergent at the stage of Range Finding Test and Acute Toxicity Test. In addition, pH, temperature, and DO parameters were also tested every day. After that, acclimatization was carried out for 7 days without feeding the fish. Then continued with the range Finding test stage for 96 hours with variations of 0% (control), 5%, 10%, 20%, 40%, 60%, 80%, and 100%. The range obtained in the range Finding test stage is 20%. So that the variations in the acute toxicity test stageused include 6%, 9%, 12%, 15%, and 18%. After observing fish mortality approaching 50%, then these results were analyzed using Microsoft Excel. The LC50 value obtained in this test is 60002,5.

Development of a Simple Methodology Using Meteorological Data to Evaluate Concentrating Solar Power Production Capacity

Evaluation of the Concentrating Solar Power capacity factor is critical to support decision making on possible regional energy investments. For such evaluations, the System Advisor Model is used to perform capacity factor assessments. Among the required data, information concerning direct normal irradiance is fundamental. In this context, the Engerer model is used to estimate direct normal irradiance hourly values out of global horizontal irradiance ground measurements and other observed meteorological variables. Model parameters were calibrated for direct normal irradiance measurements in Évora (Southern Portugal), being then applied to a network of 90 stations, part of the Portuguese Meteorological Service. From the modelled direct normal irradiance, and for stations that comprise 20 years of data, typical meteorological years were determined. Finally, to identify locations of interest for possible installations of Concentrating Solar Power systems, annual direct normal irradiance availabilities and the respective capacity factor, for a predefined power plant using the System Advisor Model, were produced. Results show annual direct normal irradiance availabilities and capacity factors of up to ~2310 kWh/m2 and ~36.2% in Castro Marim and in Faro, respectively. Moreover, this study supports energy policies that would promote Concentrating Solar Power investments in Southern Portugal (Alentejo and Algarve regions) and eastern centre Portugal (Beira Interior region), which have capacity factors above 30%.

Research on the Spatiotemporal Characteristics and Concentration Prediction Model of PM2.5 during Winter in Jiangbei New District, Nanjing, China

Accurate prediction of PM2.5 concentration is one of the key tasks of air pollution assessment, early warning, and treatment. In this paper, four monitoring sites were arranged in Jiangbei New District of Nanjing City, China. The environmental parameters such as PM2.5/PM10 concentration, temperature, and humidity were monitored from January to February 2020. A gated recurrent unit (GRU) network based on the PM2.5 concentration prediction model was established to predict PM2.5 concentration. The mean relative error (MRE), root mean square error (RMSE), and Pearson correlation coefficient were selected as the evaluation criteria for the accuracy of the GRU model. The data set was divided into a training set, a test set and a validation set at a ratio of 7:2:1, and the GRU model was used to predict the hourly value of PM2.5 concentration in the next week. The prediction results show that the Pearson correlation coefficients between the predicted values and the monitored values of the four monitoring sites have reached more than 0.9, reflecting a strong correlation. The relative average errors are around 10%. The GRU model prediction of NJAU (Nanjing Agricultural University)-Pukou Campus Site is the most accurate, and the correlation coefficient, MRE, and RMSE are 0.970, 7.85%, and 9.6049, respectively, reflecting the good prediction performance of the model. Therefore, this research supports the prediction of air quality in different cities and regions, so people can take protective measures in advance and reduce the damage caused by air pollution to human bodies.

Validation of Global Solar Radiation Models on a Horizontal Surface in the Climatic Zones of Burkina

The evaluation of the solar deposit is essential for the sizing of photovoltaic systems. This requires the availability of radiation data. In Burkina Faso, weather data doesn’t cover all the country. That makes that solar radiation measured are not available for the all country. Theorical methods can help about it. This paper is written to fill the gap of adapted solar models for the country. In this work, an analysis of the results provided by four models for the estimation of hourly values ​​of global radiation on a horizontal plane was made. The radiation data for the year 2017 comes from the Burkina weather forecast. The validation of the models is carried out by a comparison between the radiation measured and that given by the various models provided by MATLAB code. The different models have been validated by several statistical indicators (RMSE and normalized MAE) and graphs for a clear sky. Scoring criteria have been established to assess the relative quality of each model. The models retained for the study are the Bird and Hulstrom model, the Davy and Hay model, the Capderou model and the Liu and Jordan model. Three sites were affected: Ouagadougou, Dori and Gaoua. We found that for some models, there is a good agreement between the measured values ​​and those estimated by some models for the Dori site, while they are not with the values ​​measured for the Ouagadougou and Gaoua sites. In the town of Dori, the most appropriate model for estimating solar radiation is that of Bird and Hulstrom. For the cities of Ouagadougou and Gaoua, the different models are not suitable.

Performance evaluation of using evacuated tubes solar collector, perforated fins, and pebbles in a solar still - experimental study and CO2 mitigation analysis.

The combination of various methods of increasing evaporation rate can highly impact the performance of solar desalination. This investigation aims to find the impact of using evacuated tubes solar collector, perforated fins, and pebbles on the performance enhancement of a solar still. Simultaneously six-evacuated-tube solar collector to raise the evaporation rate of the system, the perforated fins to increase the heat transfer surface between water and absorber, and the immersed pebbles stone in the water to keep the high water temperature at low solar radiation were considered. The hourly and cumulative distillate output (DO) values are presented separately for the daytime and nighttime to provide extensive insight. The results indicate that on a sample day from the six months of experiments, which was in February 2019, the time for DO peak shifts from 1 to 3 p.m. Moreover, the temperature values for MSS experience almost 43 ℃ jumps on the peak and almost 19 ℃ increase on average compared to CSS. Furthermore, the cumulative DO in the daytime reaches from 2.515 to 6.662 L, while during the nighttime, an increase from 0.057 to 0.872 L is observed. Additionally, during the six months, the average DO jumps from 2.88 to 7.03 L, which means a significant enhancement of 144.1%. Moreover, the costs per liter of MSS and CSS are 0.0051 and 0.0056 dollars per liter, respectively. The net amount of CO2 reduction of MSS was improved by about 2.44 times higher than CSS.

Deep Learning of Detecting Ionospheric Precursors Associated With M ≥ 6.0 Earthquakes in Taiwan

AbstractA short‐term (30 days before an earthquake) prediction of an earthquake is a big challenge in seismology. As a first step, we apply deep learning to the ionospheric total electron content (TEC) data between 2003 and 2014 to detect the seismo‐ionospheric precursors of M ≥ 6.0 earthquakes in Taiwan. The bidirectional Long Short‐Term Memory (Bi‐LSTM) network is employed to use observed input data (features) to obtain the sequential TEC variations. The five input features are sequential vectors of TEC, the geomagnetic index Dst, the solar activity index F10.7, sunspot number (SSN), and solar emission index Lyman‐α. The daily values of F10.7, SSN, and Lyman‐α are converted into hourly values, depending on the solar elevation angle. The calculated hourly TEC variations can be more precisely predicted with this data conversion. We calculate the normalized difference of errors between two 15‐day adjacent stages as the “relative error”. Three trained models with the best discrimination between the relative errors of earthquake and no‐earthquake cases are chosen as classifiers. These three classifiers are then used to have a majority vote to declare whether the 30‐day period is related to the preparation of an earthquake or not. The results show that all 22 positive cases (earthquakes) are successfully predicted, giving a true positive rate of 100%. Among the 19 negative cases (normal cases), 10 of them are true negative.” Overall, a high accuracy of 78.05% is obtained.

Thermal Model Validation Process for Building Environment Simulation: A Case Study for Single-Family House

Currently, more and more emphasis is being placed on reducing energy consumption in buildings to reduce greenhouse gases in the atmosphere. Building performance simulation is very useful to predict energy demand and indoor environment quality. An indispensable element of the simulation is the validation and calibration of the model, which is an arduous process. The aim of the study was to present a four-level validation (using measurement results) and calibration of a thermal model of a naturally ventilated single-family house. Numerical calculations using co-simulation between EnergyPlus and Contam were performed. The results of the one-year simulation measurements of the indoor temperature and ventilation airflows were compared. After the calibration was performed, a high convergence of the results was found. The normalized mean bias error for hourly and monthly values did not exceed 1% and the coefficient of variation of the root mean squared error was a maximum of 7% with a simultaneous high correlation of the results in the range from 0.85 to 0.89. It was found that the final results were significantly influenced by the appropriate modeling of air exchange in the building, including the opening of windows.