A Novel Mathematical Model of the Solar Assisted Dehumidification and Regeneration Systems

This paper introduces a state-of-the-art modelling technique to investigate the performance of solar assisted dehumidification and regeneration cycles. The dehumidification/regeneration system investigated in this study employs a solid adsorbent bed and enables use of both solar energy and returning warm air to deliver efficient dehumidification and regeneration of the treated air. Study of literature revealed a huge gap between model results and industrial performance of such systems. Hence, the modelling work presented in this paper employs Gaussian Process Regression (GPR) technique to close the gap between model outputs and real-life operation parameters of the system. An extensive amount of laboratory tests were also carried out on the dehumidification/regeneration system and model predictions were validated through comparison with experimental results. The model predictions were found to be in good agreement with experimental results, with maximum error not exceeding 10%. The GPR technique enables simultaneous analysis of a vast quantity of key system parameters derived from mathematical models and laboratory tests. The system parameters investigated in this study include: temperature, relative humidity and flow rate of process air, and temperature of regeneration air, solar radiation intensity, operating time, moisture extraction efficiency of the dehumidification cycle and moisture removal efficiency of the regeneration cycle. Investigation of both modelling and experimental results revealed that efficiencies of the both dehumidification and regeneration cycles decrease as relative humidity of the process air increases. The increase in regeneration temperature leads to an increase in regeneration efficiency whereas; it does not have a significant impact on the dehumidification efficiency. A similar trend was also observed when solar intensity were increased. The proposed technique reduced the complexity of model by eliminating the need for heat and mass transfer calculations; reduced the performance gap between model results and real-life performance data, and increased the reliability of model outputs by showing a good agreement with experimental results. The GPR based mathematical model delivers an effective design and performance evaluation tool for the solar assisted dehumidification and regeneration systems and provides an unprecedented opportunity for commercializing such systems

Population density and spatial distribution pattern of Hypera postica (Coleoptera: Curculionidae) in Ardabil, Iran

The alfalfa weevil, Hypera postica (Gyllenhal), feeds almost exclusively on alfalfa, Medicago saliva L. in most region of the world where forage crop is grown. It has been investigated the population density and spatial distribution of alfalfa weevil on alfalfa in Ardabil during 2010. Using a 0.25 m(2) quadrate sample unit a reliable sample size was 65, with maximum relative variation of 15%. The relative variation (RV) of the primary sampling data was 13.6. The highest population density of the alfalfa weevil was recorded on 17(th) April. To estimate the spatial distribution pattern of this pest, data were analyzed through index of dispersion. Lloyd's mean crowding. Morisita's index and two regression models (Taylor's Power Law and Iwao's Patchiness Regression). Taylor's model showed an aggregated distribution pattern for all life stages. Iwao's patchiness regression indicated that larvae, adult and total life cycle had aggregated spatial distribution (t(c

Laboratory toxicity and field efficacy of Lufenuron, Dinotefuran and Thiamethoxam against Hypera postica (Gyllenhal, 1813) (Coleoptera: Curculionidae)

Toxicity of the insect growth regulator lufenuron and two neonicotinoids, dinotefuran and thiamethoxam, for the alfalfa weevil, Hypera postica (Gyllenhal, 1813), was determined through exposure of the second instar larvae and adults to dipped alfalfa leaves under laboratory conditions at 25±1 °C, 60±5% RH ,16:8 L:D. Based on mode of action, the mortality of the treated larvae and adults was recorded after 72 hours for lufenuron, and after 24 hours for dinotefuran and thiamethoxam. LC50 values for second instar larvae were 34.32, 24.91.32.9, 15.82 AI L-1 and for adults were 175.67, 289.76, 164.02 AI L-1 for dinotefuran, thiamethoxam and lufenuran, respectively. Results showed that lufenuron was the most toxic to both larvae and adults of H. postica among insecticides tested. Once the height of alfalfa field reached to about 20 cm, a single treatment was made on May 11th. All insecticides reduced the mean number of alfalfa weevil. According to results of laboratory and field experiments, lufenuron might be a more valuable chemical to adequately control H. postica with little adverse effects on environment. lufenuron may be considered as alternative chemicals to other compounds with a high potential for controlling certain pests and with less adverse effects on natural enemies

Vitamin D3-loaded electrospun cellulose acetate/polycaprolactone nanofibers: Characterization, in-vitro drug release and cytotoxicity studies

Vitamin D deficiency is nowa global health problem; despite several drug delivery systems for carrying vitaminD due to low bioavailability and loss bioactivity. Developing a new drug delivery system to deliver vitamin D3 is a strong incentive in the current study. Hence, an implantable drug delivery system (IDDS) was developed from the electrospun cellulose acetate (CA) and ε-polycaprolactone (PCL) nanofibrous membrane, in which the core of implants consists of vitamin D3-loaded CA nanofiber (CAVD) and enclosed in a thin layer of the PCL membrane (CAVD/PCL). CA nanofibrousmat loadedwith vitaminD3 at the concentrations of 6, 12, and 20% (w/w) of vitamin D3 were produced using electrospinning. The smooth and bead-free fibers with diameters ranged from 324 to 428 nm were obtained. The fiber diameters increased with an increase in vitamin D3 content. The controlled drug release profile was observed over 30-days, which fit with the zero-order model (R2 > 0.96) in the first stage. The mechanical properties of IDDS were improved. Young's modulus and tensile strength of CAVD/PCL (dry) were161 ± 14 and 13.07 ± 2.5 MPa, respectively. CA and PCL nanofibers are non-cytotoxic based on the results of the in-vitro cytotoxicity studies. This study can further broaden in-vivo study and provide a reference for developing a new IDDS to carry vitamin D3 in the future

Statistical investigation of a dehumidification system performance using Gaussian process regression

Swift performance assessment of dehumidification systems, in design stage and while operation of the system is of substantial importance for commercialization and wide implementation of this technology. This paper presents a novel statistical model, employing Gaussian Process Regression (GPR) to investigate performance of a solar/waste energy driven dehumidification/regeneration cycle with a solid adsorbent bed. The statistical model takes thousands of operating conditions derived from a numerical model to predict the performance of the system. This predictive tool directly correlates the main operating parameters with the performance parameters of the system. The operating parameters considered in this study are: temperature, relative humidity and flow rate of process air, temperature of regeneration air, length of the desiccant bed, solar radiation intensity and operating time, and the selected performance parameters are: moisture extraction efficiency for the dehumidification cycle and moisture removal efficiency for the regeneration cycle. The model is evaluated by three metrics, namely: root mean square error (RSME), mean absolute percentage error (MAPE), and coefficient of determination (R2). The maximum RSME and MAPE for moisture extraction are only 0.045, 0.21%, and for moisture removal efficiencies are 0.082 and 0.39%, respectively, while the R2 value is derived as 0.97. The developed model is used to investigate the impact of four selected operating parameters on system performance. Additionally, the system performance is predicted for randomly generated operating conditions as well as warm and humid climates. The developed GPR model provides a swift and highly accurate predictive tool for design of the dehumidification systems and for commercialization of the investigated dehumidification systems

Estimating temperature-dependent developmental rates of potato tuberworm, Phthorimaea operculella (Lepidoptera: Gelechiidae)

The potato tuberworm, Phthorimaea operculella (Zeller) (Lepidoptera: Gelechiidae), is the most destructive pest of potato, Solanum tuberosum L. (Solanaceae), in tropical and subtropical regions in both field and storeroom situations. The modeling of temperature-dependent development can be useful in forecasting occurrence and population dynamics of the pests. Published developmental parameters for this pest vary greatly for many reasons. We determined temperature-dependent development of P. operculella at seven constant temperatures (16, 20, 24, 28, 32, 34 and 36 degrees C). Developmental period of whole immature stage (egg to the end of the pupal stage) varied from 75.5 days at 16 degrees C to 17 days at 32 degrees C. The population failed to survive at 36 degrees C. The observed data was modeled to determine mathematical functions for simulating P. operculella development in each stage of development and overall. Two linear models, ordinary linear regression and the Ikemoto linear model were used to describe the relationship between temperature and development rate of the different stages of P. operculella and estimating the thermal constant and lower temperature threshold. The lower temperature threshold (t) and thermal constant (k) of whole immature stage were estimated to be 11.6 degrees C and 338.5 DD by Ikemoto linear model, and the estimated parameters were not substantially different with those estimated by ordinary linear models. Different models provided a better fit to the various developmental stages. Of the eleven nonlinear models fitted, the Beriere-1, Logan-6 and Lactin-1 model was found to be the best for modeling development rate of egg, larva and pupa of P. operculella, respectively. Phenological models based on these findings can be part of a decision-support tool to improve the efficiency of pest management programs

Comparative life table analysis of Tetranychus urticae Koch (Acari: Tetranychidae) on ten rose cultivars

International audienceLife history parameters of plant feeders are useful tools to evaluate resistance or susceptibility of host plants including different cultivars. This study compared population growth parameters of Tetranychus urticae Koch on 10 rose cultivars, including Bella Vita, Cool Water, Dolce Vita, Maroussia, Orange Juice, Pink Promise, Roulette, Tea, Valentine, and Persian yellow in laboratory conditions at 24+/-1°C, 65+/-5% relative humidity, and a photoperiod of 16:8 (L:D) h. The results revealed that mite survival rate varied from 66.5% on Bella Vita to 85.9% on Persian yellow. The immature development time was different among the tested rose cultivars and ranged from 9.35 days on Orange Juice to 12.30 days on Bella Vita. The highest fecundity rate was recorded on Pink Promise. Consequently, population growth parameters were also significantly affected. The lowest intrinsic rate of increase (rm) was recorded on Roulette and this parameter was relatively higher on Cool Water, Orange Juice, and Persian yellow. In addition, the highest net reproductive rate (R0) was observed on Pink Promise, which was significantly higher than Roulette, Tea, and Valentine cultivars. The longest mean generation time (T) was calculated on Roulette and the shortest on Cool Water, Tea, and Orange Juice. The lowest performance of the two-spotted mite on Roulette could indicate that this is a suitable cultivar against mite infestation. Differences in mite susceptibility of tested rose cultivars here highlighted have the potential to be used for integrated pest management of T. urticae in ornamental rosa cultivations

Life table parameters of Callosobruchus maculatus on cowpea seeds (Vigna unguiculata) treated with some biological and chemical fertilizers

The cowpea weevil, Callosobruchus maculatus (F.) (Coleoptera: Chrysomelidae), a destructive insect pest of cowpea, Vigna unguiculata (L.), in the field and storage, causes significant losses in seed weight, germination ability, and the market value. The effect of cowpea (Mashhad cultivar) fertilization with chemical fertilizers (triple superphosphate (TSP) and urea) and some biofertilizers (Bradyrhizobium japonicum, Pseudomonas putida, mycorrhizal fungi) was studied on biology and life table parameters of C. maculatus at 28 ± 1°C, relative humidity of 65 ± 5%, and complete darkness. The highest immature survival (%) was on the grains treated with P. putida and control (97.75 and 95.69%, respectively), and the lowest survival was on the grains fertilized with TSP and B. japonicum (65.06 and 75%, respectively). Although the developmental time of C. maculatus reared on TSP- and B. japonicum-treated grains was longer than the control, the intrinsic rate of increase (0.124 day-1) and net reproductive rate (34.34 offspring) on the grains treated with TSP were lower than the control (0.143 day-1 and 51.07 offspring, respectively). Results of this research showed that the nutritional value of the grains obtained from TSP and B. japonicum treatments were lower than those obtained from other fertilizer treatments

Can whole building energy models outperform numerical models, when forecasting performance of indirect evaporative cooling systems?

This paper presents a whole building energy modelling work incorporating a state-of-the-art indirect evaporative cooling system. The model is calibrated and validated with real-life empirical data, and is capable of representing actual performance of the system with high reliability. The investigated system is a novel super-performance Dew Point Cooler (DPC) with a guideless and corrugated Heat and Mass Exchanger (HMX). The DPC is modelled as part of the whole building energy model through detailed description of system and building characteristics at source code level. The developed model has been simulated in all different climates that an Indirect Evaporative Cooling (IEC) system can be operated, namely: subtropical hot desert, humid continental, Mediterranean, and hot desert climates. The performance predictions has been tested against experiments and numerical model of the same system, and a detailed investigation of modelling approaches to efficiently and effectively model aforementioned systems has been provided. The calibrated and empirically validated whole building energy model predicted the key performance parameters of the dew point evaporative cooling system with mean error values limited to 4.1%. The highest COP values recorded by experiments and whole building energy simulations were 51.1 and 49, respectively. The whole building energy model proved to better predict the performance of dew point evaporative cooler, when compared to numerical models, by incorporating the building-side parameters into the model. This modelling work paves the way toward detailed investigation of the advanced cooling systems within building context to achieve optimised performance of the system in wide range of buildings and operating conditions

A constraint multi-objective evolutionary optimization of a state-of-the-art dew point cooler using digital twins

This study is pioneered in developing digital twins using Feed-forward Neural Network (FFNN) and multi objective evolutionary optimization (MOEO) using Genetic Algorithm (GA) for a counter-flow Dew Point Cooler with a novel Guideless Irregular Heat and Mass Exchanger (GIDPC). The digital twins, takes the intake air characteristics, i.e., temperature, relative humidity as well as main operating and design parameters, i.e., intake air velocity, working air fraction, height of HMX, channel gap, and number of layers as the inputs. GIDPC’s cooling capacity, coefficient of performance (COP), dew point efficiency, wet-bulb efficiency, supply air temperature and surface area of the layers are selected as outputs. The optimum values of aforementioned operating and design parameters are identified by the MOEO to maximise the cooling capacity, COP, wet-bulb efficiencies and to minimise the surface area of the layers in four identified climates within Köppen-Geiger climate classification, namely: tropical rainforest, arid, Mediterranean hot summer and hot summer continental climates. The system monthly and annual performances in the identified optimum conditions are compared with the base system and the results show the annual improvements of up to 72.75% in COP and 23.57% in surface area. In addition, the annual power consumption is reduced by up to 49.41% when the system is designed and operated optimally. It is concluded that identifying the optimum conditions for the GIDPC can increase the system performance substantially