Solar Radiation Input Research Articles

ОПРЕДЕЛЕНИЕ ОПТИМАЛЬНОЙ СТРУКТУРЫ ВЕТРОСОЛНЕЧНЫХ ЭЛЕКТРОСТАНЦИЙ В МОНГОЛЬСКОЙ ЧАСТИ ПУСТЫНИ ГОБИ

Актуальность работы обусловлена интенсивным экономическим развитием стран Северо-Восточной Азии, увеличением их потребности в электроэнергии и целесообразностью повышения экономической и экологической эффективности электроснабжения за счет реализации проектов электроэнергетической интеграции. При этом важную роль может играть широкомасштабное внедрение возобновляемых источников энергии. Цель: определение оптимальной структуры ветросолнечных электростанций в монгольской части пустыни Гоби (соотношения мощностей электростанций разных типов и выработки ими электроэнергии) для разных сочетаний экономических и климатических условий. Методы: систематизация климатической и метеорологической информации, предварительная оценка эффективности энергоисточников разных типов по критерию стоимости производимой электроэнергии, математическое моделирование структуры и режимов работы энергосистемы. Математическая модель учитывает случайный характер поступления солнечной и ветровой энергии. Результаты. Показано, что произведенная фотоэлектрическими преобразователями и ветротурбинами электроэнергия с учетом стоимости ее транспорта по линиям электропередачи конкурентоспособна на электроэнергетических рынках Китая и других стран Северо-Восточной Азии. Для различных значений прихода солнечной радиации и скорости ветра определены оптимальные соотношения между мощностями возобновляемых источников энергии, производством электроэнергии фотоэлектрическими преобразователями и ветротурбинами, а также поставками электроэнергии из энергосистемы Китая для компенсации неравномерности выработки возобновляемых источников энергии. Показана экономическая эффективность совместного использования солнечной и ветровой энергии в монгольской части пустыни Гоби за исключением некоторых районов с низкими скоростями ветра. Совместное использование солнечной и ветровой энергии позволяет снизить суммарные затраты на систему электроснабжения более чем на четверть по сравнению с вариантом использования только солнечной энергии.

The Rigid-Flexible-Thermal Coupled Analysis for Spacecraft Carrying Large-Aperture Paraboloid Antenna

Abstract Since the thermal load would adversely introduce degradation to the normal operation of spacecraft, resulting in unpredictable thermal-dynamic behavior, thermomechanical coupling problems are important and have been investigated extensively. Based on the absolute nodal coordinate formulation (ANCF), a thermal integrated ANCF thin plate element based on the unified description is constructed, which could depict the displacement and the temperature field integratedly. By means of the proposed element, the heat transfer and continuum mechanics are integrated in the unified finite element method (FEM) mesh of revolving paraboloid antenna. Additionally, the ANCF reference node is introduced for describing the rigid central hub where the antenna is mounted on to make the rigid-flexible-thermal coupled response being captured in a unified analysis procedure. The solar radiation input and the surface emitting radiation are included in the heat transfer equations. Furthermore, the influence of the rigid body motion and the deformation on the radiant absorption are also considered with the self-shadowing. The established rigid-flexible-thermal coupled simulation is performed on a modified generalized-α integrator which solves the set of multidisciplinary governing equations synchronously. For revealing the nonlinear behavior of the rigid-flexible-thermal coupled system, the observed thermally induced vibration and perturbation on the pointing accuracy of the spacecraft are given in the results, and the feasibility of the presented method is proved.

Modeling and experimental study of a triangular channel solar air heater

In this study, a pilot plant of a triangular channel solar air heater with a U-turn airflow pattern was constructed and its performance was investigated using a developed model and experimental data under different operating conditions. A new equivalent radiation-convection circuit was developed as the most sophisticated part of the model. Based on the circuit, a mathematical model with minimal simplifying assumptions was developed to predict the performance of the heater. Compared with the results of an integral model of overall energy balance equations, the developed model showed a 50% reduction of error in prediction of thermal efficiency and outlet air temperature. The maximum thermal efficiency of the system could be obtained at an air mass flow rate of 0.045 kg/s (i.e. mass flux of 8.18 kg/m2.s). Considering the air pressure drop (as the most important penalty) and outlet air temperature, the highest thermohydraulic performance was obtained at a channel internal peak angle of 60°. Besides, the results indicated that to achieve a certain thermal efficiency, the presented solar air heater requires less surface area than that of a flat plate solar air heater for the same input solar radiation.

Experimental and CFD investigation of a hybrid solar air heater

Solar air heaters may be used in a variety of applications such as space heating, pre-heating for industrial applications, drying of various materials and pre-heating for solar water desalinators. This research is aimed at evaluating a unique solar air heater design in terms of its thermal efficiency and temperature distributions within the solar air heater. The solar heater is unique as it combines parallel- and counter flows inside the heater in order to reduce mass and improve overall heat transfer. Current modelling techniques are not suitable to this type of SAH, as they apply to SAHs with simpler geometries, like counterflow heaters or parallel flow heaters. The solar air heater is evaluated using computational fluid dynamics and experiment. The computational models are validated experimentally. The computational models account for the solar load, surface to surface radiation, conduction, convection and turbulence. A screening of turbulence models is performed. The average conversion efficiency ranges between 23% and 83% and the average collector efficiency between 11% and 44%. The thermal efficiency values predicted by the computational models show good agreement with the experimentally derived values. The computational models over-predict the thermal efficiency by between 6.75% and 9.01% of the measured quantity, depending on the solar radiative power input used. The model predictions of temperatures show good qualitative agreement with the measured temperatures but do not compare well quantitatively for all points of comparison. The average error between predicted temperature and experimental results for the various points of comparison is 9.165 K.

A critical comparison of methods to estimate solar rooftop photovoltaic potential in Switzerland

To understand the opportunities and challenges of large shares of solar photovoltaics (PV) in our electricity mix, various large-scale studies of PV potential on building roofs have been conducted in recent years. The use of different datasets, methods and spatio-temporal resolutions leads to widely varying results, making a comparison across different studies intrinsically difficult. In this work, six studies carried out in Switzerland are compared in a quantitative way, in order to understand how different methods impact the potential estimates. We observe a strong trend towards increasing spatial and temporal resolutions, using larger and more accurate datasets for the analysis. While the earliest study relies on rules of thumb, later studies use data-driven estimations, enabled by the use of Machine Learning, scalable algorithms and powerful computational engines. Our analysis shows that the largest differences are caused by the source of the solar radiation input data, the computation of shading effects on rooftops and the estimation of available roof area for PV panel installation. The latter is the most uncertain parameter in the presented studies and offers opportunities for future work.

Snowmelt modeling using two melt-rate models in the Urumqi River watershed, Xinjiang Uyghur Autonomous Region, China

In this paper, the performance of the classic snowmelt runoff model (SRM) is evaluated in a daily discharge simulation with two different melt models, the empirical temperature-index melt model and the energy-based radiation melt model, through a case study from the data-sparse mountainous watershed of the Urumqi River basin in Xinjiang Uyghur Autonomous Region of China. Theclassic SRM, which uses the empirical temperature-index method, and a radiation-based SRM, incorporating shortwave solar radiation and snow albedo, were developed to simulate daily runoff for the spring and summer snowmelt seasons from 2005 to 2012, respectively. Dailymeteorological and hydrological data were collected from three stations located in the watershed. Snowcover area (SCA) was extracted from satellite images. Solarradiation inputs were estimated based on a digital elevation model (DEM). Theresults showed that the overall accuracy of the classic SRM and radiation-based SRM for simulating snowmelt discharge was relatively high. Theclassic SRM outperformed the radiation-based SRM due to the robust performance of the temperature-index model in the watershed snowmelt computation. Nosignificant improvement was achieved by employing solar radiation and snow albedo in the snowmelt runoff simulation due to the inclusion of solar radiation as a temperature-dependent energy source and the local pattern of snowmelt behavior throughout the melting season. Ourresults suggest that the classic SRM simulates daily runoff with favorable accuracy and that the performance of the radiation-based SRM needs to be further improved by more ground-measured data for snowmelt energy input.

Midwinter melts in the Canadian prairies: energy balance and hydrological effects

Abstract. Snowpack accumulation and depletion are important elements of the hydrological cycle in the Canadian prairies. The surface runoff generated during snowmelt is transformed into streamflow or fills numerous depressions driving the focussed recharge of groundwater in this dry setting. The snowpack in the prairies can undergo several cycles of accumulation and depletion in a winter. The timing of the melt affects the mechanisms of snowpack depletion and their hydrological implications. The effects of midwinter melts were investigated at four instrumented sites in the Canadian prairies. Unlike net radiation-driven snowmelt during spring melt, turbulent sensible heat fluxes were the dominant source of energy inputs for midwinter melt occurring in the period with low solar radiation inputs. Midwinter melt events affect several aspects of hydrological cycle with lower runoff ratios than subsequent spring melt events, due to their role in the timing of the focussed recharge. Remote sensing data have shown that midwinter melt events regularly occur under the present climate throughout the Canadian prairies, indicating applicability of the study findings throughout the region.

Solar–gliding arc plasma reactor for carbon dioxide decomposition: Design and characterization

The conversion of low-value feedstock such as carbon dioxide (CO2) into higher-value products using renewable energy, particularly solar, can help fulfill the increasing need for fuels and chemicals while mitigating environmental emissions. A direct solar receiver-reactor fitted with a gliding arc (glidarc) electrical discharge for potentially greater efficiency and continuous operation solar thermochemical synthesis is presented. The nonequilibrium plasma inside the reactor chamber leads to increased solar energy absorption by the gas-phase feedstock, potentially enhancing chemical conversion. Moreover, the reliance on electrical energy to sustain the plasma allows compensating for fluctuations in the solar radiation input. Two solar-glidarc reactor configurations are investigated and evaluated for the decomposition of CO2 at atmospheric pressure conditions, namely: axi-radial (AXR) and reverse-vortex (RVX) flow. The former provides greater control of residence time but presents limited solar-plasma interaction; whereas the latter allows for greater interaction, but requires higher flow rates to confine the plasma, lowering the residence time. Flow paths and residence times are evaluated via Computational Fluid Dynamics (CFD) models used to guide reactor design and operation. Evaluation of the plasma volume at different reactor orientations, aimed to mimic in-field operation, show that the AXR configuration leads to a larger plasma volume compared to that by the RVX design. Net-absorption tests, aimed to assess the extent of solar-plasma interaction, showed up to 18% net-absorption of solar radiation for the RVX configuration and 7% for the AXR one, compared to 0% in the absence of plasma. The AXR configuration, despite its lower absorption of solar energy, leads to greater CO2 homogeneous gas-phase decomposition (i.e. in the absence of any catalyst), of up to 4.5%, mainly due to its flexibility in operating with lower residence times. The results indicate solar-plasma direct-receiver reactors provide a compelling approach to solar thermochemical synthesis processes.

Quantifying the Clear‐Sky Bias of Satellite Land Surface Temperature Using Microwave‐Based Estimates

AbstractMost available long‐term databases of land surface temperature (LST) derived from space‐borne sensors rely on infrared observations and are therefore restricted to clear‐sky conditions. Hence, studies based on such data sets may not be representative of all‐weather conditions and may be considered as “biased” toward clear sky. An assessment of the impact of this restriction is made using 3 years of LST derived from passive microwave observations that are not affected by most clouds. A systematic analysis in space and time is performed of the “clear‐sky bias,” defined as the difference between average clear‐sky and average all‐weather LSTs. The amplitude of the bias is closely related to the fraction of clear‐sky days, and therefore, arid regions are associated to very low values of bias whereas midlatitudes present the highest values. During daytime, the input of solar radiation for clear‐sky situations leads to higher LST values, and therefore, the bias is generally positive (e.g., 2–8 K over the midlatitudes) whereas, during nighttime, the bias is generally negative although with lower amplitude (around −2 K), because of the increased radiative cooling for clear‐sky situations. The clear‐, cloudy‐, and all‐sky LSTs are also compared with near‐surface air temperature. Although LST is generally higher than air temperature, the contrast between the two may be strongly influenced by local weather conditions. Both the clear‐sky bias and differences between LST and air temperature are also analyzed at the local scale taking into account the predominant cloud regime.

Heat Transfer Model of a 50 kW Solar Receiver–Reactor for Thermochemical Redox Cycling Using Cerium Dioxide

This work reports on the development of a transient heat transfer model of a solar receiver–reactor designed for thermochemical redox cycling by temperature and pressure swing of pure cerium dioxide in the form of a reticulated porous ceramic (RPC). In the first, endothermal step, the cerium dioxide RPC is directly heated with concentrated solar radiation to 1500 °C while under vacuum pressure of less than 10 mbar, thereby releasing oxygen from its crystal lattice. In the subsequent, exothermic step, the reactor is repressurized with carbon dioxide as it cools, and at temperatures below 1000 °C, the partially reduced cerium dioxide is re-oxidized with a flow of carbon dioxide. To analyze the performance of the solar reactor and to gain insight into improved design and operational conditions, a transient heat transfer model of the solar reactor for a solar radiative input power of 50 kW during the reduction step was developed and implemented in ANSYS cfx. The numerical model couples the incoming concentrated solar radiation using Monte Carlo ray tracing, incorporates the reduction chemistry by assuming thermodynamic equilibrium, and accounts for internal radiation heat transfer inside the porous ceria by applying effective heat transfer properties. The model was experimentally validated using data acquired in a high-flux solar simulator (HFSS), where temperature evolution and oxygen production results from model and experiment agreed well. The numerical results indicate the prominent influence of solar radiative input power, where increasing it substantially reduces reduction time of the cerium dioxide structure. Consequently, the model predicts a solar-to-fuel energy conversion efficiency of >6% at a solar radiative power input of 50 kW; efficiency >10% can be obtained provided the RPC macroporosity is substantially increased, and better volumetric absorption and uniform heating is achieved. Managing the ceria surface temperature during reduction to avoid sublimation is a critical design consideration for direct absorption solar receiver–reactors.

Managing Spatial Orientation of Photovoltaic Module to Obtain the Maximum of Electric Power Generation at Preset Point of Time

To evaluate the possibility of obtaining the maximum of electric power generation at a preset point of time by varying the spatial orientation of photovoltaic modules, its effect on the amount of utilized solar radiation was studied. The experiment was conducted by the example of Zernograd, Rostov oblast, Russia, with specially designed research equipment. The analysis of input of solar radiation to surfaces with different spatial orientation revealed that, owing to different combinations of spatial placement of the receiving site with respect to cardinal directions and the horizon line, it is possible to shift the maximum of power takeoff with photovoltaic modules relative to midday to the morning and evening time about by 4.5 h.

Power forecast research of photovoltaic system based on double-level neural network

A photovoltaic generation system is affected by many factors. The traditional method of forecasting photovoltaic power generation is more complicated. A double-level neural network is designed with consideration of these factors: the first level network calculates a real solar radiation with input of theory radiation and weather coefficient; the second level network calculates the final result generation power with input of real solar radiation which comes from the first network and the highest temperature which comes from weather forecast. The final power results indicate this method has good forecast capacity, calculate results are very close to measure value and errors are less than single level network.

Thermodynamic development and design of a concentrating solar thermochemical water-splitting process for co-production of hydrogen and electricity

A concentrating solar plant is proposed for a thermochemical water-splitting process with excess heat used for electricity generation in an organic Rankine cycle. The quasi-steady state thermodynamic model consisting of 23 components and 45 states uses adjustable design parameters to optimize hydrogen production and system efficiency. The plant design and associated thermodynamic model demonstrate that cerium oxide is suitable for thermochemical water-splitting cycles involving the co-production of hydrogen and electricity. Design point analyses at 900 W/m2 DNI indicate that a single tower with solar radiation input of 27.74 MW and an aperture area of 9.424 m2 yields 10.96 MW total output comprised of 5.55 MW hydrogen (Gibbs free energy) and 5.41 MW net electricity after subtracting off 22.0% of total power generation for auxiliary loads. Pure hydrogen output amounts to 522 tonne/year at 20.73 GWh/year (HHV) or 17.20 GWh/year (Gibbs free energy) with net electricity generation at 14.52 GWh/year using TMY3 data from Daggett, California, USA. Annual average system efficiency is 38.2% with the constituent hydrogen fraction and electrical fraction being 54.2% and 45.8%, respectively. Sensitivity analyses illustrate that increases in particle loop recuperator effectiveness create an increase in hydrogen production and a decrease in electricity generation. Further, recuperator effectiveness has a measurable effect on hydrogen production, but has limited impact on total system efficiency given that 81.1% of excess heat is recuperated within the system for electricity generation.

Simulation of Convection Flow and Sensitivity Analysis of Model Parameters of Evacuated Glass Tube Solar Water Heater

The water-in-glass evacuated collectors are made up of parallel circular tubes. They are installed with some inclination angle to the horizontal. The thermal performance of water-in-glass evacuated tube solar water heater heavily depends on weather conditions. The analysis of the sensitivity of the model parameter and weather conditions on heat transfer process is extremely important to install a solar water heater system in order to achieve its maximum efficiency. The evaluation of the sensitivity of the system parameters is done by considering one parameter after another while keeping the remaining fixed. Further to the analysis of the heat transfer process, the average heat transfer coefficient and the average natural circulation flow rate are calculated.
 The fluid flow is assumed to be unsteady, two-dimensional, laminar and incompressible. The heat and fluid flow are analyzed using the Navier-Stokes equations and temperature equation for an incompressible fluid, subject to density variation with temperature. The discretization of the governing equations is done by Finite Volume Method (FVM). The Open FOAM computational fluid dynamic software with PISO-SIMPLE algorithm is used for the simulation.
 The results show that the heat transfer process is improved when there is a moderate level inclination angle. Further, it is found that when the ratio of tube length to diameter is high, the heat transfer process is improved. The solar radiation input highly affects the performance of a solar water heater. The cold-water inlet temperature does not directly affect the buoyancy induced flow, but it influences the temperature gain.
 The angle of the solar rays vary within the daytime, however it does not affect the performance of the solar water heater since an evacuated-tube has a circular absorbing surface, it passively tracks the sun throughout the day. 
 These results recommend using moderate level tube inclination angle and high ratio to improve the performance of a solar water heater.

Evaluation of the ENVI-Met Vegetation Model of Four Common Tree Species in a Subtropical Hot-Humid Area

Urban trees can significantly improve the outdoor thermal environment, especially in subtropical zones. However, due to the lack of fundamental evaluations of numerical simulation models, design and modification strategies for optimizing the thermal environment in subtropical hot-humid climate zones cannot be proposed accurately. To resolve this issue, this study investigated the physiological parameters (leaf surface temperature and vapor flux) and thermal effects (solar radiation, air temperature, and humidity) of four common tree species (Michelia alba, Mangifera indica, Ficus microcarpa, and Bauhinia blakeana) in both spring and summer in Guangzhou, China. A comprehensive comparison of the observed and modeled data from ENVI-met (v4.2 Science, a three-dimensional microclimate model) was performed. The results show that the most fundamental weakness of ENVI-met is the limitation of input solar radiation, which cannot be input hourly in the current version and may impact the thermal environment in simulation. For the tree model, the discrepancy between modeled and observed microclimate parameters was acceptable. However, for the physiological parameters, ENVI-met tended to overestimate the leaf surface temperature and underestimate the vapor flux, especially at midday in summer. The simplified calculation of the tree model may be one of the main reasons. Furthermore, the thermal effect of trees, meaning the differences between nearby treeless sites and shaded areas, were all underestimated in ENVI-met for each microclimate variable. This study shows that the tree model is suitable in subtropical hot-humid climates, but also needs some improvement.

Temperature-based model for monthly average hourly global solar radiation for the Caribbean island of Trinidad

Hourly global solar radiation data are required to optimize various solar energy based designs. In this study, a new empirical temperature-based model for determining monthly average hourly global solar radiation on a horizontal surface for the Caribbean island of Trinidad was developed and validated using calibration and validation datasets of hourly global solar radiation and temperature from 2001 to 2005 and 2006 to 2010, respectively. The new model was evaluated alongside five existing monthly average hourly radiation ratio models due to Whillier/Liu and Jordan, Collares-Pereira and Rabl, Gueymard, Newell, and Jain. For all six models, measured and calculated monthly average hourly global solar radiation over the five-year validation period 2006–2010 were compared statistically using mean bias error, root mean square error, correlation coefficient, and Nash-Sutcliffe efficiency. For an average year, the temperature-based model was the best performing model for two months, the Collares-Pereira and Rabl and Gueymard models for ten months, and the Whillier/Liu and Jordan model for one month. Over an average year, the temperature-based and Gueymard models yielded root mean square errors of 0.12 MJ m−2 h−1 and 0.10 MJ m−2 h−1, respectively. Over the single years from 2006 to 2010, the models were evaluated for performance and robustness toward inter-annual fluctuations in global solar radiation and temperature. Some re-distribution of the same four models occurred among the months over the years, but overall, they were in agreement with those obtained for an average year. The Newell model was the most robust. Over these five years, the temperature-based and Gueymard models yielded root mean square errors of 0.17 MJ m−2 h−1 and 0.14 MJ m−2 h−1, respectively. For modeling of monthly average hourly global solar radiation on both yearly and average year bases, the temperature-based and Gueymard models were most suitable with root mean square errors of 0.15 MJ m−2 h−1 and 0.12 MJ m−2 h−1, respectively. Advantageously, the temperature-based model is independent of global solar radiation input unlike the other models.

Humidity determines snowpack ablation under a warming climate

Climate change is altering historical patterns of snow accumulation and melt, threatening societal frameworks for water supply. However, decreases in spring snow water equivalent (SWE) and changes in snowmelt are not ubiquitous despite widespread warming in the western United States, highlighting the importance of latent and radiant energy fluxes in snow ablation. Here we demonstrate how atmospheric humidity and solar radiation interact with warming temperature to control snowpack ablation at 462 sites spanning a gradient in mean winter temperature from -8.9 to +2.9 °C. The most widespread response to warming was an increase in episodic, midwinter ablation events. Under humid conditions these ablation events were dominated by melt, averaging 21% (202 mm/year) of SWE. Winter ablation under dry atmospheric conditions at similar temperatures was smaller, averaging 12% (58 mm/year) of SWE and likely dominated by sublimation fluxes. These contrasting patterns result from the critical role that atmospheric humidity plays in local energy balance, with latent and longwave radiant fluxes cooling the snowpack under dry conditions and warming it under humid conditions. Similarly, spring melt rates were faster under humid conditions, yet the second most common trend was a reduction in spring melt rates associated with earlier initiation when solar radiation inputs are smaller. Our analyses demonstrate that regional differences in atmospheric humidity are a major cause of the spatial variability in snowpack response to warming. Better constraints on humidity will be critical to predicting both the amount and timing of surface water supplies under climate change.

Savings resulting from coupling the PV with the space cooling system

The paper presents results of analysis of possible cooperation of a photovoltaic system with the space cooling devices. The size of the photovoltaic system was determined on the basis of electricity demand of the selected single family house. The demand for the electricity use for cooling and air conditioning had not been taken into account while calculating the size of PV system. On the basis of the heat balance of the building, the demand for cooling in the following hours of a year was determined. The demand for cooling and heating is affected by the heat transfer through walls, windows, floor, roof, and air exchanged through ventilation. Also solar and internal gains were taken into account. Based on Next, a cooling unit was selected. A cooling device was selected to provide enough energy to maintain the thermal comfort of the building in summer. Taking into account parameters of the selected device, the demand for electricity was determined. Based on time and hours of operation of electrical appliances in the building, a chart of electricity demand was created. The demand for cooling was included. Calculated values of the energy demand required to power all devices in the building were compared with the energy gains from the photovoltaic system. In order to calculate the energy generated by the PV system (in following hours of a year) the isotropic model of solar irradiation was used. The input solar radiation data on horizontal surface were downloaded from the website of the Ministry of Investment and Economic Development. In the last paragraphs, savings obtained in result of using the energy generated by the PV system to drive the space cooling system were determined and conclusions from the calculations were presented.

Co-production of syngas and potassium-based fertilizer by solar-driven thermochemical conversion of crop residues

We report on the thermochemical conversion of inedible crop residues using concentrated solar energy as the source of high-temperature process heat. Experiments were performed using a 5kWth solar packed-bed reactor exposed to radiative fluxes up to 1788 suns. The waste biomass feedstock consisted of unprocessed batches of cotton boll, soybean husk, and black mustard husk and straw, which were pyrolysed and steam-based gasified at nominal temperatures in the range 879–1266°C, yielding high-quality syngas with molar ratios in the range H2:CO=1.43–3.25, CO2:CO=0.28–1.40, and CH4:CO=0.03–0.28. The solar-to-fuel energy conversion efficiency, defined as the ratio of the heating value of the syngas produced to the solar radiative energy input and the heating value of the feedstock, reached 18%. The heating value of the feedstock was solar-upgraded by 7%, thus outperforming autothermal gasification that typically downgrades by at least 15%. The ash contained 23% potassium. The solar-driven thermochemical process offers a sustainable and efficient path for the conversion of agricultural wastes into valuable fuels and soil fertilizers.

Numerical solution of MHD slip flow of a nanofluid past a radiating plate with Newtonian heating: A Lie group approach

In this paper, we have examined the magnetohydrodynamic flow of a nanofluid past a radiating sheet. The Navier velocity slip, Newtonian heating and passively controlled wall boundary conditions are considered. The governing equations are reduced into similarity equations with the help of Lie group. A collocation method is used for simulation. The influence of emerging parameters on velocity, temperature, nanoparticle volumetric fraction profiles, as well as on local skin friction factor and local Nusselt number is illustrated in detail. It is found that the friction (heat transfer rate) is lower (higher) for passively controlled boundary conditions as compared to the case of an actively controlled boundary condition. The magnetic field effects decrease both the skin friction and the rate of heat transfer. The findings are validated with existing results and found an excellent agreement. The model explores new applications in solar collectors with direct solar radiative input using magnetic nanofluids.