A solar powered liquid-desiccant cooling system for greenhouses

Liquid desiccant systems are of potential interest as a means of cooling greenhouses to temperatures below those achieved by conventional means. However, only very little work has been done on this technology with previous workers focussing on the cooling of human dwellings using expensive desiccants such as lithium salts. In this study we are designing a system for greenhouse cooling based on magnesium chloride desiccant which is an abundant and non-toxic substance. Magnesium chloride is found in seawater, for example, and is a by-product from solar salt works. We have carried out a detailed experimental study of the relevant properties of magnesium rich solutions. In addition we have constructed a test rig that includes the main components of the cooling system, namely a dehumidifier and solar regenerator. The dehumidifier is a cross-flow device that consists of a structured packing made of corrugated cellulose paper sheets with different flute angles and embedded cooling tubes. The regenerator is of the open type with insulated backing and fabric covering to spread the flow of desiccant solution. Alongside these experiments we are developing a mathematical model in gPROMS® that combines and simulates the heat and mass transfer processes in these components. The model can be applied to various geographical locations. Here we report predictions for Havana (Cuba) and Manila (Philippines), where we find that average wet-bulb temperatures can be lowered by 2.2 and 3°C, respectively, during the month of May.

State-owned enterprises, exporting and productivity in China:a stochastic dominance approach

A popular explanation for China's rapid economic growth in recent years has been the dramatic increase in the number of private domestic and foreign-owned firms and a decline in the state-owned sector. However, recent evidence suggest that China's state-owned enterprise (SOEs) are in fact stronger than ever. In this paper we examine over 78,000 manufacturing firms between 2002 and 2006 to investigate the relationship between ownership structure and the degree of firm-level exposure to export markets and firm-level productivity. Using a conditional stochastic dominance approach we reveal that although our results largely adhere to prior expectations, the performance of state-owned enterprises differs markedly between those that export and those that supply the domestic market only. It appears that China's internationally focused SOEs have become formidable global competitors.

Effects of engine cooling water temperature on performance and exhaust emission characteristics of a multi-cylinder CI engine operated with Jatropha-Butanol blend

Renewable alternatives such as biofuels and optimisation of the engine operating parameters can enhance engine performance and reduce emissions. The temperature of the engine coolant is known to have significant influence on engine performance and emissions. Whereas much existing literature describes the effects of coolant temperature in engines using fossil derived fuels, very few studies have investigated these effects when biofuel is used as an alternative fuel. Jatropha oil is a non-edible biofuel which can substitute fossil diesel for compression ignition (CI) engine use. However, due to the high viscosity of Jatropha oil, technique such as transesterification, preheating the oil, mixing with other fuel is recommended for improved combustion and reduced emissions. In this study, Jatropha oil was blended separately with ethanol and butanol, at ratios of 80:20 and 70:30. The fuel properties of all four blends were measured and compared with diesel and jatropha oil. It was found that the 80% jatropha oil + 20% butanol blend was the most suitable alternative, as its properties were closest to that of diesel. A 2 cylinder Yanmar engine was used; the cooling water temperature was varied between 50°C and 95°C. In general, it was found that when the temperature of the cooling water was increased, the combustion process enhanced for both diesel and Jatropha-Butanol blend. The CO2 emissions for both diesel and biofuel blend were observed to increase with temperature. As a result CO, O2 and lambda values were observed to decrease when cooling water temperature increased. When the engine was operated using diesel, NOX emissions correlated in an opposite manner to smoke opacity; however, when the biofuel blend was used, NOX emissions and smoke opacity correlated in an identical manner. The brake thermal efficiencies were found to increase slightly as the temperature was increased. In contrast, for all fuels, the volumetric efficiency was observed to decrease as the coolant temperature was increased. Brake specific fuel consumption was observed to decrease as the temperature was increased and was higher on average when the biofuel was used, in comparison to diesel. The study concludes that the effects of engine coolant temperature on engine performance and emission characteristics differ between biofuel blend and fossil diesel operation. The coolant temperature needs to be optimised depending on the type of biofuel for optimum engine performance and reduced emissions.

A procedure for the reconstruction of a stochastic stationary temperature field

An iterative procedure is proposed for the reconstruction of a temperature field from a linear stationary heat equation with stochastic coefficients, and stochastic Cauchy data given on a part of the boundary of a bounded domain. In each step, a series of mixed well-posed boundary-value problems are solved for the stochastic heat operator and its adjoint. Well-posedness of these problems is shown to hold and convergence in the mean of the procedure is proved. A discretized version of this procedure, based on a Monte Carlo Galerkin finite-element method, suitable for numerical implementation is discussed. It is demonstrated that the solution to the discretized problem converges to the continuous as the mesh size tends to zero.

A stochastic frontier approach to modelling financial constraints in firms:an application to India

We propose the use of stochastic frontier approach to modelling financial constraints of firms. The main advantage of the stochastic frontier approach over the stylised approaches that use pooled OLS or fixed effects panel regression models is that we can not only decide whether or not the average firm is financially constrained, but also estimate a measure of the degree of the constraint for each firm and for each time period, and also the marginal impact of firm characteristics on this measure. We then apply the stochastic frontier approach to a panel of Indian manufacturing firms, for the 1997–2006 period. In our application, we highlight and discuss the aforementioned advantages, while also demonstrating that the stochastic frontier approach generates regression estimates that are consistent with the stylised intuition found in the literature on financial constraint and the wider literature on the Indian credit/capital market.

Semiparametric smooth-coefficient stochastic frontier model

This paper proposes a semiparametric smooth-coefficient (SPSC) stochastic production frontier model where regression coefficients are unknown smooth functions of environmental factors (ZZ). Technical inefficiency is specified in the form of a parametric scaling function which also depends on the ZZ variables. Thus, in our SPSC model the ZZ variables affect productivity directly via the technology parameters as well as through inefficiency. A residual-based bootstrap test of the relevance of the environmental factors in the SPSC model is suggested. An empirical application is also used to illustrate the technique.

The preparation of a common technique for selecting counter flow and crossflow cooling towers

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Bayesian precalibration of a large stochastic microsimulation model

Calibration of stochastic traffic microsimulation models is a challenging task. This paper proposes a fast iterative probabilistic precalibration framework and demonstrates how it can be successfully applied to a real-world traffic simulation model of a section of the M40 motorway and its surrounding area in the U.K. The efficiency of the method stems from the use of emulators of the stochastic microsimulator, which provides fast surrogates of the traffic model. The use of emulators minimizes the number of microsimulator runs required, and the emulators' probabilistic construction allows for the consideration of the extra uncertainty introduced by the approximation. It is shown that automatic precalibration of this real-world microsimulator, using turn-count observational data, is possible, considering all parameters at once, and that this precalibrated microsimulator improves on the fit to observations compared with the traditional expertly tuned microsimulation. © 2000-2011 IEEE.

Effect of cooling rate on intercritically reheated microstructure and toughness in high strength low alloy steel

High strength low alloy steels have been shown to be adversely affected by the existence of regions of poor impact toughness within the heat affected zone (HAZ) produced during multipass welding. One of these regions is the intercritically reheated coarse grained HAZ or intercritical zone. Since this region is generally narrow and discontinuous, of the order of 0.5 mm in width, weld simulators are often employed to produce a larger volume of uniform microstructure suitable for toughness assessment. The steel usedfor this study was a commercial quenched and tempered steel of 450 MN m -2 yield strength. Specimen blanks were subjected to a simulated welding cycle to produce a coarse grained structure of upper bainite during the first thermal cycle, followed by a second thermal cycle where the peak temperature T p2 was controlled. Charpy tests carried out for T p2 values in the range 650-850°C showed low toughness for T p2 values between 760 and 790°C, in the intercritical regime. Microstructural investigation of the development of grain boundary martensite-retained austenite (MA) phase has been coupled with image analysis to measure the volume fraction of MAformed. Most of the MA constituent appears at the prior austenite grain boundaries during intercritical heating, resulting in a 'necklace' appearance. For values of T p2 greater than 790°C the necklace appearance is lost and the second phase areas are observed throughout the structure. Concurrent with this is the development of the fine grained, predominantly ferritic structure that is associated with the improvement in toughness. At this stage the microstructure is transforming from the intercritical regime structure to the supercritically reheated coarse grained HAZ structure. The toughness improvement occurs even though the MA phase is still present, suggesting that the embrittlement is associated with the presence of a connected grain boundary network of the MA phase. The nature of the second phase particles can be controlled by the cooling rate during the second cycle and variesfrom MA phase at high cooling rates to a pearlitic structure at low cooling rates. The lowest toughness of the intercritical zone is observed only when MA phase is present. The reason suggested for this is that only the MA particles debond readily, a number of debonded particles in close proximity providing sufficient stress concentration to initiate local cleavage. © 1993 The Institute of Materials.

Experiments for CFD-modelling of cooling water and Insulation debris two-phase flow phenomena during loss of coolant accidents

The knowledge of insulation debris generation and transport gains in importance regarding reactor safety research for PWR and BWR. The insulation debris released near the break consists of a mixture of very different fibres and particles concerning size, shape, consistence and other properties. Some fraction of the released insulation debris will be transported into the reactor sump where it may affect emergency core cooling. Experiments are performed to blast original samples of mineral wool insulation material by steam under original thermal-hydraulic break conditions of BWR. The gained fragments are used as initial specimen for further experiments at acrylic glass test facilities. The quasi ID-sinking behaviour of the insulation fragments are investigated in a water column by optical high speed video techniques and methods of image processing. Drag properties are derived from the measured sinking velocities of the fibres and observed geometric parameters for an adequate CFD modelling. In the test rig "Ring line-II" the influence of the insulation material on the head loss is investigated for debris loaded strainers. Correlations from the filter bed theory are adapted with experimental results and are used to model the flow resistance depending on particle load, filter bed porosity and parameters of the coolant flow. This concept also enables the simulation of a particular blocked strainer with CFDcodes. During the ongoing work further results of separate effect and integral experiments and the application and validation of the CFD-models for integral test facilities and original containment sump conditions are expected.

Cooling of greenhouses using seawater:a solar driven liquid-desiccant cycle for greenhouse cooling in hot climates

Evaporative pads are frequently used for the cooling of greenhouses. However, a drawback of this method is the consumption of freshwater. In this paper it is shown, both theoretically and through a practical example, that effective evaporative cooling can be achieved using seawater in place of fresh water. The advantages and drawbacks of using seawater are discussed more generally. In climates that are both hot and humid, evaporative systems cannot always provide sufficient cooling, with the result that cultivation often has to be halted during the hottest months of the year. To overcome this, we propose a concept in which a desiccant pad is used to dehumidify the air before it enters the evaporative pad. The desiccant pad is supplied with a hygroscopic liquid that is regenerated by the energy of the sun. The performance of this concept has been modelled and the properties of various liquids have been compared. An attractive option is to obtain the liquid from seawater itself, given that seawater contains hygroscopic salts such as magnesium chloride. Preliminary experiments are reported in which magnesium chloride solution has been regenerated beneath a solar simulator.

Fully probabilistic control for stochastic nonlinear control systems with input dependent noise

Robust controllers for nonlinear stochastic systems with functional uncertainties can be consistently designed using probabilistic control methods. In this paper a generalised probabilistic controller design for the minimisation of the Kullback-Leibler divergence between the actual joint probability density function (pdf) of the closed loop control system, and an ideal joint pdf is presented emphasising how the uncertainty can be systematically incorporated in the absence of reliable systems models. To achieve this objective all probabilistic models of the system are estimated from process data using mixture density networks (MDNs) where all the parameters of the estimated pdfs are taken to be state and control input dependent. Based on this dependency of the density parameters on the input values, explicit formulations to the construction of optimal generalised probabilistic controllers are obtained through the techniques of dynamic programming and adaptive critic methods. Using the proposed generalised probabilistic controller, the conditional joint pdfs can be made to follow the ideal ones. A simulation example is used to demonstrate the implementation of the algorithm and encouraging results are obtained.

One Class of Stochastic Local Search Algorithms

Accelerated probabilistic modeling algorithms, presenting stochastic local search (SLS) technique, are considered. General algorithm scheme and specific combinatorial optimization method, using “golden section” rule (GS-method), are given. Convergence rates using Markov chains are received. An overview of current combinatorial optimization techniques is presented.

Variational mean-field algorithm for efficient inference in large systems of stochastic differential equations

This work introduces a Gaussian variational mean-field approximation for inference in dynamical systems which can be modeled by ordinary stochastic differential equations. This new approach allows one to express the variational free energy as a functional of the marginal moments of the approximating Gaussian process. A restriction of the moment equations to piecewise polynomial functions, over time, dramatically reduces the complexity of approximate inference for stochastic differential equation models and makes it comparable to that of discrete time hidden Markov models. The algorithm is demonstrated on state and parameter estimation for nonlinear problems with up to 1000 dimensional state vectors and compares the results empirically with various well-known inference methodologies.

A decision support system for supplier selection and order allocation in stochastic, multi-stakeholder and multi-criteria environments

Integrated supplier selection and order allocation is an important decision for both designing and operating supply chains. This decision is often influenced by the concerned stakeholders, suppliers, plant operators and customers in different tiers. As firms continue to seek competitive advantage through supply chain design and operations they aim to create optimized supply chains. This calls for on one hand consideration of multiple conflicting criteria and on the other hand consideration of uncertainties of demand and supply. Although there are studies on supplier selection using advanced mathematical models to cover a stochastic approach, multiple criteria decision making techniques and multiple stakeholder requirements separately, according to authors' knowledge there is no work that integrates these three aspects in a common framework. This paper proposes an integrated method for dealing with such problems using a combined Analytic Hierarchy Process-Quality Function Deployment (AHP-QFD) and chance constrained optimization algorithm approach that selects appropriate suppliers and allocates orders optimally between them. The effectiveness of the proposed decision support system has been demonstrated through application and validation in the bioenergy industry.