Effects of porous superhydrophilic surfaces on flow boiling critical heat flux in IVR accident scenarios

Critical Heat Flux (CHF) plays a key role in nuclear reactor safety both during normal operation as well as in accident scenarios. In particular,when an in-vessel retention (IVR) strategy is used as a severe accident management strategy, the reactor pressure vessel (RPV) cavity is flooded with water, to remove the decay heat from the corium relocated in the lower plenum by conduction through the RPV wall and flow boiling on the outer surface of the RPV. The CHF limit must not be exceeded to prevent RPV failure.Therefore, knowledge of the CHF under realistic conditions is necessary to assess coolability margins. Previous studies for prediction of CHF in the IVR situation were mostly based on data for as fabricated un-oxidized stainless steel. However, the RPV is made of low carbon steel and its surface has an oxide layer that results from pre-service heat treatment as well as oxidation during service. This oxide layer introduces significant differences in surface wettability, porosity, and roughness in comparison to an un-oxidized stainless steel surface. In this study, test heaters were fabricated out of RPV low carbon steel, pre-oxidized in a controlled high temperature wet air environment, which emulates the surface oxides present on the outer surface of the actual RPV; the heaters were then tested in a flow boiling loop designed specifically for the IVR conditions. Up to 70% enhancement in CHF value was observed for the oxidized in low carbon steel in comparison to the stainless steel

Sensorless Commutation Method for Low-Voltage BLDC Motors Based on Unfiltered Line Voltage

This study presents a filterless and sensorless commutation method for low-voltage brushless DC motors. The proposed method utilizes controlled DC-link inverter instead of the Pulse-Width Modulation (PWM) scheme. Therefore, motor voltages and currents become free from the high-frequency noise of PWM switching, thereby decreasing motor losses. Consequently, the method does not require any Low-Pass Filter (LPF) and it does not involve speed-dependent phase delay caused by the LPF. However, current commutation deteriorates waveform of line voltages. Thus, specific functions are defined to compensate for the current commutation spikes and remove false zero-crossing points of line voltages. Furthermore, the use of unfiltered line voltages eliminates the requirement of any phase shifter. Hence, the main superiority of the proposed method over preceding sensorless commutation methods is the simultaneous elimination of the phase shifter and LPF, which makes the method simple and cost-effective. The simulation and experimental results show the effectiveness and validity of the method

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

Model-based predictive direct power control of brushless doubly fed reluctance generator for wind power applications

In this paper, a predictive direct power control (PDPC) method for the brushless doubly fed reluctance generator (BDFRG) is proposed. Firstly, the BDFRG active and reactive power equations are derived and then the active and reactive power variations have been predicted within a fixed sampling period. The predicted power variations are used to calculate the required voltage of the secondary winding so that the power errors at the end of the following sampling period are eliminated. Switching pulses are produced using space vector pulse width modulation (SVPWM) approach which causes to a fixed switching frequency. The BDFRG model and the proposed control method are simulated in MATLAB/Simulink software. Simulation results indicate the good performance of the control system in tracking of the active and reactive power references in both power step and speed variation conditions. In addition, fast dynamic response and lower output power ripple are other advantages of this control method

Time Series Model for Forecasting the Prevalence of Some Important Parasitic Infections in Slaughtered Sheep in North-Central Iran

Uncontrolled parasitic infections in livestock can increase the potential risk of transmission between human societies. Owing to the socioeconomic challenges of these diseases in slaughtered sheep, the current study aimed to forecast the prevalence of these infections in a central slaughterhouse in Alborz Province, north-central Iran. Data from 2009 to 2018 on parasitic infections in slaughtered sheep presented at a slaughterhouse were compiled and the prevalence of these diseases was computed. The prevalence has been considered as a time series and afterward, RStudio software using the best-fitted ARIMA model was applied to forecast the monthly variation in prevalence rates. From 2009 to 2018, a total of 1,339,196 sheep were slaughtered in the studied slaughterhouse. The Iranian Afshari breed was the most slaughtered sheep and, a total of 77.6% of these animals were raised under traditional farming system. In addition to the Alborz province, slaughtered sheep were brought from five other provinces, including Zanjan, Qazvin, Qom, Kurdistan, and East Azerbaijan. The highest and lowest total prevalence of studied parasitic zoonoses in slaughtered livestock were cystic echinococcosis (12.76%) and Taenia ovis infection (0.01%), respectively. An approximate stationary trend for fascioliasis and CE and a mild decreasing trend for dicrocoeliasis and sarcocystosis has been forecasted for the next 10 years. Forecasting the prevalence of T. ovis infection showed that without implementing control strategies, this infection would be increased in the years ahead. The current study has demonstrated for the first time the predicting of some important parasitic infections in sheep in Iran. The results provide helpful data for authorities for controlling these diseases in the frontline of meat production. Vast and in-depth forecasting investigations is required to find evidence-based data about these infections for entire the country of Iran

Using Thomas Model to Evaluate Dye Removal from Aqueous Solutions in Fixed-bed Columns of Activated Carbon

For the purposes of this study, activated carbon was derived from pine-cone by a chemical-thermal process. Initially, its chemical and physical properties were determined before it was used for the removal of Acid Black 1 and Acid Blue 113 dyes. A batch sorption study was carried out in order to obtain the optimum isotherm model. The monolayer maximum saturation capacities of AB1 and AB113 dyes based on Langmuir isotherm model were determined to be 458 mg dye/g carbon and 286 mg dye/g carbon, respectively. Adsorption of dyes was also studied in a continuous-flow state using a fixed-bed column of activated carbon. The effects of operating variables such as flow rate, bed depth, and dye concentration on the column operation were studied. Data confirmed that the breakthrough curves depended on flow rate, bed depth, and initial dye concentration. Column behavior was investigated using Thomas Model and model parameters were determined by a non-linear regression method. The Langmuir and Freundlich isotherm models were used to fit the experimental data. The best fit of the adsorption isotherm data was obtained using the Langmuir model for both dyes. The results showed that Thomas Model was suitable for the description of breakthrough curves under the experimental condition. The column adsorption capacity was also compared with equilibrium adsorption capacities for each dye