Walid H. Shayya

Use of evaporation ponds for brine disposal in desalination plants

Abstract Desalination plants are being used increasingly in inland areas of many countries for supplying water for domestic purposes. If these areas are too far away from the sea, the opportunity to dispose the reject brine (also known as concentrate, reject water, or wastewater) in the ocean no longer exists, given that ocean disposal is the common practice for plants located in coastal areas. Evaporation ponds are especially suitable to dispose of reject brine from inland desalination plants in arid and semi-arid areas due to the abundance of solar energy. In irrigation projects facing a soil salinity problem due to a shallow saline groundwater table, evaporation ponds are also in use. Saline water tables are lowered by pumping or tile draining and the drainage water is stored in evaporation ponds. While evaporation ponds have long been used for salt production in many parts of the world, the disposal of concentrate from desalination plants in inland areas using evaporation ponds is of much significance both economically and environmentally. Guidelines are needed for the design, construction, maintenance, and operation of evaporation ponds for reject brine disposal in an economical and environmentally-sensitive manner. This paper provides a critical review of concentrate disposal technology using evaporation ponds. Relevant topics are also covered including chemistry of brine, brine disposal methods, use of evaporation ponds in agriculture, determination of evaporation rate, and evaporation enhancement methods.

Thermodynamic and economic considerations in solar desalination

Abstract The thermodynamic efficiency of single-basin and multiple-effect solar water desalination systems was critically reviewed with special emphasis on humidification-dehumidification processes. Solar energy may be used, either directly or indirectly, to produce fresh water. The concept of using the humidification-dehumidification process in combination with the growth of crops in a greenhouse system, however, is relatively new. System economics was also covered since it affects the final cost of produced water. While a system may be technically very efficient, it may not be economic. The challenges and opportunities of solar energy were also briefly discussed. The paper closes with a summary of key factors affecting system performance and recommendations for future areas of investigation and development.

Brine disposal from reverse osmosis desalination plants in Oman and the United Arab Emirates

Abstract Reverse osmosis (RO) desalination plants are used for supplying potable water to small communities in inland areas of Oman as well as small to large communities in the United Arab Emirates (UAE). Most of these desalination plants use brackish groundwater as feedwater. The production of brine (also known as concentrate or wastewater) is an integral part of the operation of desalination plants in the interior parts of Oman and eight RO plants in the coastal areas of the UAE were investigated with regard to their brine disposal methods. The capacity of the Omani plants varied from 50 m 3 /d to a maximum of 1000 m 3 /d. The salinity level of wastewater varied from 9.8 to 61.2 dS/m (1 dS/m = 640 mg/L). Various disposal methods were observed. These included lined evaporation ponds, ocean/beach disposal, and unlined small bores. The depth to the water table in the areas of the investigated desalination plants varies from 40 to 80m, while the average distance between feedwater intake and disposal areas was approximately 200 m. In the UAE, the capacities of the investigated plants varied between 950 to 15,000 m 3 /d. All the UAE plants dispose of their brine in the sea, although some of the plants dispose of their brine in nearby creeks that are linked to the sea. The chemical characteristics of the brine, feedwater, product water, and water from evaporation ponds (or bores) were determined. The presence of other chemicals including iron, copper, zinc, and cleaning agents (such as hydrochloric acid, sodium hexametaphosphate, and anti-scalants) is likely to pollute the groundwater, if the brine were to reach the underlying aquifers. Under certain conditions, brine from the desalination plants can have useful applications. Potentials for such applications are addressed in this paper.

An artificial neural network for non-iterative calculation of the friction factor in pipeline flow

Abstract A non-iterative procedure was developed, using an artificial neural network (ANN), for calculating the friction factor, f, in the Darcy-Weisbach equation when estimating head losses due to friction in closed pipes. The Regula-Falsi method was used as an implicit solution procedure to estimate the f values for a range of Reynolds numbers, Re, and relative roughness e/D values (where e is the pipe roughness and D is the pipe diameter). In developing the ANN model, three configurations were evaluated: (i) the input parameters Re and e/D were taken initially on a linear scale; (ii) the first input parameter Re was transformed to a logarithmic scale; and (iii) both input parameters (Re and e/D) were transformed to a logarithmic scale. Configuration (iii) yielded an optimal ANN model with 14 neurons in each of three hidden layers. This configuration was capable of predicting the values of f in the Darcy-Weisbach equation for any given Re in the range of 2×103–1×108 and e/D in the range of 1×10−6–5×10−2. These values were in close agreement with those obtained using the numerical technique. The developed ANN model may offer significant advantages when dealing with flow problems that involve repetitive calculations of the friction factor such as those encountered in the hydraulic analysis of pipe networks and pressurized irrigation systems.

Simulation of fresh water production using a humidification-dehumidification seawater greenhouse

A thermodynamic simulation study was performed on the influence of greenhouse-related parameters on a desalination process that combines fresh water production using humidification-dehumidification with the growth of crops in a greenhouse. With the system under study, surface seawater trickles down a porous front wall evaporator through which air is drawn into the greenhouse. The saturated air passes through a condenser, which is cooled using cold deep seawater or cool seawater coming out of the evaporators. Thermodynamic modeling of the seawater greenhouse system in our laboratory has shown that the dimension of the greenhouse had the greatest overall effect on water production and energy consumption. A wide shallow greenhouse, 200 m wide by 50 m deep gave 125 m3.d−1 of fresh water. This was greater than a factor oftwo compared to the worst-case scenario with the same area (50 m wide by 200 m deep), which gave 58 m3.d−1. Low power consumption went hand-in-hand with high efficiency. The wide shallow greenhouse consumed 1.16 kWh.m−3, while the narrow deep structure consumed 5.02 kWh.m−3 . The benefits of the development of the seawater greenhouse for arid regions are discussed.

Effects of pH and seasonal temperature variation on simultaneous partial nitrification and anammox in free-water surface wetlands

Design considerations to enhance simultaneous partial nitrification and anammox in constructed wetlands are largely unknown. This study examined the effects of pH and seasonal temperature variation on simultaneous partial nitrification and anammox in two free-water surface wetlands. In order to enhance partial nitrification and inhibit nitrite oxidation, furnace slag was placed on the rooting substrate to maintain different pH levels in the wetland water. The wetlands were batch operated for dairy wastewater treatment under oxygen-limited conditions at a cycle time of 7 d. Fluorescence in situ hybridization analysis found that aerobic ammonium oxidizing bacteria and anammox bacteria accounted for 42-73% of the bacterial populations in the wetlands, which was the highest relative abundance of ammonium oxidizing and anammox bacteria in constructed wetlands enhancing simultaneous partial nitrification and anammox. The two wetlands removed total inorganic nitrogen efficiently, 3.36-3.38 g/m(2)/d in the warm season with water temperatures at 18.9-24.9 °C and 1.09-1.50 g/m(2)/d in the cool season at 13.8-18.9 °C. Plant uptake contributed 2-45% to the total inorganic nitrogen removal in the growing season. A seasonal temperature variation of more than 6 °C would affect simultaneous partial nitrification and anammox significantly. Significant pH effects were identified only when the temperatures were below 18.9 °C. Anammox was the limiting stage of simultaneous partial nitrification and anammox in the wetlands. Water pH should be controlled along with influent ammonium concentration and temperature to avoid toxicity of free ammonia to anammox bacteria.

Aflaj irrigation and on-farm water management in northern Oman

This paper reports on results from a case study on water management within a traditional, falaj irrigation system in northern Oman. In the planning and design of regional irrigation development programs, generalized assumptions are frequently made as to the efficiency of traditional surface irrigation systems. Although qualitative accounts abound, very little quantitative research has been conducted on on-farm water management within falaj systems. Daily irrigation applications and crop water use was monitored during an 11-month period among 6 farm holdings at Falaj Hageer in Wilayat Al-Awabi. Contrary to the frequent assumptions that all surface irrigation systems incur unnecessarily high water losses, on-farm ratios of crop water demand to irrigation supply were found to be relatively high. Based on actual crop water use, irrigation demand/supply ratios among monitored farms varied from 0.60 to 0.98, with a mean of 0.79. Examination of the soil moisture budget indicates that during most irrigations of wheat (cultivated in the low evapotranspiration months of October–March) sufficient water is applied for the shallow root zone to attain field capacity. With the exception of temporary periods of high falaj delivery flows or periods of rainfall, field capacity is usually not attained during irrigations within the more extensive root zones of date palm farms. The data presented in this paper should provide a better understanding of water use performance by farmers within traditional falaj systems. Moreover, these data should also serve to facilitate more effective development planning for irrigation water conservation programs in the region.

Finite Element Analysis of Microirrigation Hydraulics Using a Virtual Emitter System

As the use of microirrigation expands, the need to analyze large systems (10,000 emitters or more) becomes more and more important. The purpose of this research was to improve the design of large microirrigation systems using the finite element method and a virtual emitter system. To accomplish this objective, a second-order partial differential equation describing flow in a microirrigation system was developed and solved using the finite element numerical procedure. Several alternative methods were developed for incorporating emitters to a virtual emitter system where multiple emitters can be combined within a pipe element or into a node. These alternative methods were evaluated using both linear and quadratic elements. The resulting procedures were found to be fast, accurate, and efficient in the hydraulic analysis of large microirrigation systems.

Explicit calculation of the friction factor in pipeline flow of Bingham plastic fluids: a neural network approach

Abstract An artificial neural network (ANN) approach was used in this paper to develop an explicit procedure for calculating the friction factor, f, under both laminar and turbulent flow conditions of Bingham plastic fluids in closed conduits and pipe networks. The procedure aims at reducing the computational efforts as well as eliminating the need for conducting complex and time-consuming iterative solutions of the governing implicit equations for calculating the friction factor, f. The ANN approach involved the establishment of an explicit relationship among the Reynolds number, Re, Hedstrom number, He, and the friction factor, f, under both laminar and turbulent flow conditions. Although, an analytical solution of the governing equation under the laminar flow regime was also feasible (such an equation is also provided in this paper), the ANN model is applicable under both laminar and turbulent flow conditions where the analytical approach will have major limitations (especially when considering the implicit equation that govern the turbulent flow regime).

Computerization of Stumbo's method of thermal process calculations using neural networks

Abstract The four heat penetration parameters in Stumbo’s method of thermal process calculations were correlated using artificial neural networks (ANN). The process involved the development of two different artificial neural network models, one named ANNG for the parameter g (the difference between the retort and food center temperatures) and the other named ANNFU for the parameter f h / U (the ratio of heating rate index to the sterilizing value). Both these models replace the 57 tables developed by Stumbo for assessing sterilizing effects. The ANNG model deals with estimating the process time for a given process lethality and involves g as the dependent (output) variable while f h / U , z (representing the temperature interval difference that causes a tenfold change in decimal reduction time), and j cc (the cooling rate lag factor) are taken as the independent (input) variables. The ANNFU model involves the prediction of the lethality of a given process with the f h / U being taken as the dependent variable and z , j cc , and g as the independent variables. In developing each of the ANN models, several configurations were evaluated: (i) the input and output parameters were taken on a linear scale, (ii) the input and output parameters were taken after the transformation of some or all the input and output parameters using a logarithmic scale to the base 10, and (iii) all input and output parameters were transformed using a logarithmic scale to the base two. The optimum ANN models, ANNG and ANNFU, were those of the third configuration. ANNG involved a network with six neurons in each of the three hidden layers while ANNFU included 16 neurons in each of the two hidden layers. The two optimal ANN models are capable of predicting the g and f h / U parameters in the range given in Stumbo’s tables. In each instance, the predicted values were in close agreement with those listed in the tables. In addition, the developed ANN models can predict the intermediate values of any combination of inputs. Therefore, they eliminate the need for excessive storage requirements of tables and interpolations while computerizing thermal process calculations using Stumbo’s method.