In order to check the applicability of Artificial Intelligent (AI) techniques to act as reliable inverse models to solve the multi-input/multi-output heat flux estimation classes of inverse heat transfer problems (IHTPs), in a newly reconstructed experimental setup, a two-input/two-two output (TITO) heat flux estimation problem was defined in which the radiation acts as the main mode of thermal energy. A simple three-layer perceptron Artificial Neural Network (ANN) was designed, trained, and employed to estimate the input powers (represent emitted heats-heat fluxes from two halogen lamps) to irradiative batch drying process. To this end, different input power functions (signals) were input to the furnace/dryer's halogen lamps, and the resultant temperature histories were measured and recorded for two different points of the dryer/furnace. After determining the required parameters, the recorded data were prepared and arranged to be used for inverse modelling purposes. Next, an ANN was designed and trained to play the role of the inverse heat transfer model. The results showed that ANNs are applicable to solve heat flux estimation classes of IHTPs.

There are two major approaches in sequential (real-time) heat flux estimation problems using measured temperatures: (i) development of inverse heat transfer models that directly estimate heat flux and (ii) use of a combination of a direct heat transfer model (which estimates temperature using heat flux information) and an optimization algorithm. In physics-based solutions, using thermodynamics and heat transfer laws, the first approach is considered ill-posed and challenging, and the second approach is more popular. However, the use of artificial intelligence (AI) techniques has recently facilitated heat transfer inverse modelling, even for complex irradiative systems. Many of the claimed advantages of AI inverse models of irradiative systems result from the use of AI techniques rather than the inverse modelling approach. This research presents a rational comparison between the aforementioned approaches for an irradiative thermal system, both using AI techniques, for the first time. The results show that inverse models are superior because of their higher accuracy and shorter estimation delay time.

Protein instability in white wine can result in unsightly haze formation, and therefore, its prevention by adsorption of haze proteins onto bentonite is an important unit operation in commercial wine production. Optimisation of this process is challenging due to the performance impact of environmental factors and matrix effects which are difficult to control and study in wine systems. These issues are addressed in the present study; the effect of different factors on adsorption behaviour of a purified thaumatin-like grape protein (VVTL1) by sodium bentonite in a chemically defined model wine solution was investigated using a factorial design with surface response analysis. Bentonite adsorption of VVTL1 was well characterised by a multi-factor Langmuir adsorption model. The main effects of pH, temperature, potassium concentration as well as the pH*potassium matrix interaction all had a significant effect (p < 0.05) on the adsorption capacity, as did the aging of bentonite slurry before use. Observations support the hypothesis that VVTL1 adsorption onto sodium bentonite is affected by steric mass action and local interactions of exposed protein charge, with pH and temperature effects related to changes in protein conformation under those conditions. Variation in potassium concentration can cause similar effects and influence adsorption capacity by affecting bentonite swelling and charge potential, providing a greater surface area for adsorption. From a processing perspective, results suggest bentonite treatment efficiency will be optimised by treating wines at higher temperatures rather than during cold storage, at the lower pH and before cold (tartrate) stabilisation.

A novel Friday 13th (Fr 13) risk analysis of the vulnerability to surprise (unexpected) failure of a global milk pasteurizing plant consisting of heating, holding and cooling unit operations is developed and illustrated. We define two or more interconnected unit operations as a global model. The aim was to gain new insight into the effects of accumulating random (stochastic) changes that could lead to overall failure in an otherwise well-operated and well-maintained pasteurizing plant. The methodology is a development of the work of Davey and co-workers (Food Control 29, 1 (2015) 248-253, CES 127 (2015) 133-142). Failure is defined in terms of criteria that must be met to ensure safe operation. Realistic data for large-scale pasteurization are used. Results reveal that the overall global model is vulnerable to failure in 12.5% of all cases over the long term. If each simulation can be considered a daily process, this translates to some 46 failures each year to meet the design pasteurization criteria. This new process insight cannot be obtained using traditional risk and hazard approaches. How this new Fr 13 methodology can be used to simulate design changes to the physical system to minimize vulnerability to failure is discussed. The finding should be of immediate interest to milk processors. (c) 2015 Curtin University of Technology and John Wiley & Sons, Ltd.

Summary Although much research has been conducted on wheat flour dough rheology, the principal focus has been the role of the protein fraction. Starch is the main component of flour and plays a key role in dough dynamic properties, particularly during heating. This study assesses the effect of two different waxy flours, a durum and a bread wheat, and their blends with commercial bakers' flour on dough rheology during heating with a concurrent investigation into baking performance. Both waxy flour blends produced similar effects on dough rheological behaviour despite differences in protein content, acting to delay gelatinisation and reduce storage modulus. The main effects in bread were to increase loaf expansion during baking and reduce loaf firmness. It is postulated these effects are largely water mediated, with the higher swelling ability of the waxy starch granules reducing overall water availability and driving complete gelatinisation to higher temperatures.

Interface coupled dissolution-reprecipitation reactions (ICDR) are a common feature of fluid-rock interaction during crustal fluid flow. We tested the hypothesis that ICDR reactions can play a key role in scavenging minor elements by exploring the fate of U during the experimental sulfidation of hematite to chalcopyrite under hydrothermal conditions (220-300 degrees C). The experiments where U was added, either as solid UO2+X(s) or as a soluble uranyl complex, differed from the U-free experiments in that pyrite precipitated initially, before the onset of chalcopyrite precipitation. In addition, in UO2+X(s)-bearing experiments, enhanced hematite dissolution led to increased porosity and precipitation of pyrite+magnetite within the hematite core, whereas in uranyl nitrate-bearing experiments, abundant pyrite formed initially, before being replaced by chalcopyrite. Uranium scavenging was mainly associated with the early reaction stage (pyrite precipitation), resulting in a thin U-rich line marking the original hematite grain surface. This "line" consists of nanocrystals of UO2+X(s), based on chemical mapping and XANES spectroscopy. This study shows that the presence of minor components can affect the pathway of ICDR reactions. Reactions between U- and Cu-bearing fluids and hematite can explain the Cu-U association prominent in some iron oxide-copper-gold (IOCG) deposits.

The 3-stage Clean-In-Place (CIP) model of Xin (2003. A Study of the Mechanisms of Chemical Cleaning of Milk Protein Fouling Deposits Using a Model Material (Whey Protein Concentrate Gel). Ph.D. Thesis. The University of Auckland. Chapter 5, pp 99–137) and Xin et al. (2004. Am. Inst. Chem. Eng. J. 50 (8), 1961–1973) is used for the first time to illustrate a Friday 13th risk assessment. The aim was to reveal the risk of failure with auto-set CIP cleaning times (tT) to remove whey protein deposits on metal surfaces during the alkali cleaning step due to stochastic, within system changes. The approach is to define an underlying unit-operations model together with a computationally convenient risk factor (p) so that for all failures to remove the deposit in a set time with practical tolerance, p>0. CIP is simulated using Monte Carlo simulation with Latin Hypercube sampling of the temperature of the alkali cleaning fluid (0.5-wt% NaOH) together with a tolerance of 2% on tT. Results illustrate that with a widely used cleaning fluid temperature of 75°C some 2% of all alkali CIP operations will fail over the long term. These failures cannot be attributed to human error or faulty fittings. This new risk assessment illustrates that apparent continuous CIP operation is actually a mix of successful and unsuccessful operations. The application of this novel Fr 13 risk methodology to quantitatively reduce vulnerability to these failures and to assess control and other process intervention strategies to improve reliability and safety is discussed.

The present work has focused on a comparison between commonly employed artificial neural networks (ANNs) in engineering applications to identify the most efficient ANN for the inverse modelling of an irradiating furnace/ dryer in terms of accuracy and computing time. To this end, several ANNs were designed, trained and employed to estimate the heat emitted during the irradiative batch drying process with the aid of NeuroSolution (R).As part of the study, different ANNs were designed and trained to play the role of the inverse heat transfer model. The reasons for exploiting these ANNs were derived from various studies in the literature, in which ANNs were employed for engineering modelling purposes. The results showed that the multiple layer perceptron (MLP) with the Levenberg-Marquadt (LM) in the back propagation (BP) was the best ANN among the methods evaluated to solve the inverse heat estimation problems used in irradiative batch drying processes. An important advantage of the ANN method in comparison with the classical inverse heat transfer modelling approaches is that a detailed knowledge of geometrical and thermal properties of the system (such as wall conductivity, emissivity, etc.) is not required. Such properties are difficult to measure and may undergo significant changes during the temperature transient mode.In this study, genetic algorithms (GAs) have been employed to determine the key parameters of the employed ANNs. These parameters are normally found heuristically or by a trial and error brute force process. The results demonstrate that the aforementioned parameters may be estimated much more accurately and faster by the GA method. The performance of the networks has been improved as well and the number of required hidden layers has been discovered using a non trial-error method, which eliminates time-consuming repeating procedures and produces more accurate results. (C) 2014 Elsevier Ltd. All rights reserved.

In situ XAS data of Ni(II) chloride solutions with various salinities (0–7.68m) were collected to investigate the stoichiometry and geometry of Ni(II) chloride complexes from room temperature up to 369°C at 400bar, and to 434°C at 600bar. Increasing temperature and/or salinity results in a change in the coordination of the Ni(II) chlorocomplexes from octahedral to (distorted) tetrahedral. Octahedral species predominate within the whole salinity range at room temperature and up to ~200°C, and tetrahedral species become significant beyond this temperature. At 369°C and 400bar, octahedral species remain in equilibrium with tetrahedral species, and the number of chloride ligands in the first coordination shell depends on the Cl:Ni molar ratio. EXAFS refinements and ab initio XANES calculations show that the highest order chlorocomplex present over the investigated pressure, temperature and composition ranges is the distorted tetrahedral complex [NiCl3(H2O)]−, which predominates in the highest Cl concentration (7.68m) solution at 434°C and 600bar. A quantitative thermodynamic analysis of the XANES and EXAFS data reveals that the XAS data are consistent with the speciation models derived from recent UV-Vis spectrophotometric measurements (25°C–250°C, 100bar; Liu et al., 2012b) and the high temperature, high pressure solubility experiments of Lin and Popp (1984) and Fahlquist and Popp (1989), if the NiCl2(aq) species exists in both octahedral ([NiCl2(H2O)4](aq)) and tetrahedral ([NiCl2(H2O)2](aq)) forms, with the ratio of octahedral to tetrahedral decreasing at high temperature (>200°C). The new XAS data show that the octahedral to tetrahedral transition in Ni(II) chloride complexes occurs at higher temperature and/or salinity than the corresponding Co(II) complexes (Liu et al., 2011).

The aim of this study was to fabricate porous scaffolds of zein/poly(ε-caprolactone) (PCL) biocomposite by solvent casting–particulate leaching method using sodium chloride particles as the porogen. Porous biocomposite scaffolds with porosity around 70% and well-interconnected network were obtained. The incorporation of zein into PCL led to the improvement of hydrophilicity as indicated by the results of water contact angle measurement. After immersion in phosphate buffered saline (PBS) in vitro for 28days, it was observed that the degradation rate of the zein/PCL biocomposite scaffold was faster than the PCL scaffold and that the rate could be tailored by adjusting the amount of zein in the composite. The results demonstrate the potential of the zein/PCL biocomposite scaffolds to be used in tissue engineering strategies to regenerate bone defects.

In this study, porous scaffolds made of magnesium phosphate (MP)/polycaprolactone (PCL) biocomposite were developed for bone tissue engineering applications. The composite scaffolds were fabricated by the particulate leaching method using sodium chloride particles as porogen. The obtained scaffold with porosity around 73% presents a porous structure with interconnected open pores. Hydrophilicity of the scaffolds was enhanced by the incorporation of MP component as demonstrated by the water contact angle measurement. The results of the in vitro degradation study show that the MP/PCL composite scaffolds degraded faster than PCL scaffolds in phosphate buffered saline (PBS). In addition, the degradation rate of the scaffolds could be tuned by adjusting the content of MP component in the composite. The results indicate that the MP/PCL composite scaffold has a potential application in bone tissue engineering. (C) 2012 Elsevier B.V. All rights reserved.

In this work, a variety of new approaches are developed and results are compared for solving inverse heat transfer problems where radiation is the dominant mode of thermal energy transport. An artificial neural network (ANN), two hybrid methods of genetic algorithms and artificial neural networks (GA–ANNs), and an adaptive neuro-fuzzy inference system network (ANFIS) were designed. These were trained and then employed to estimate the required input power in an irradiative batch drying process. A comparison of the results shows that the most accurate method is ANFIS but the number of parameters in ANFIS is larger than ANNs. Consequently, the ANFIS solution is time consuming in this application; however other neuro-fuzzy techniques may require fewer parameters and these will be considered in future studies. For the studied ANNs, the hybrid method of GA–ANN is optimal using the Levenberg–Marquardt optimization algorithm during back propagation in terms of accuracy and network's performance.

A large-volume single-pass flow-through cell forin situneutron diffraction investigation of hydrothermal crystallization processes is reported. The cell is much more versatile than previous designs owing to the ability to control independently and precisely temperature (up to 673 K), pressure (up to 46 MPa), flow rate (0.01–10 ml min−1) and reaction-fluid volume (≥65 ml). Such versatility is realized by an innovative design consisting of a room-temperature and ambient-pressure external fluid supply module, a high-pressure reaction module which includes a high-temperature sample compartment enclosed in a vacuum furnace, and a room-temperature and high-pressure backpressure regulation module for pressure control. The cell provides a new avenue for studying various parameters of hydrothermal crystallizations independently,in situand in real time at extreme hydrothermal conditions (e.g.supercritical). The cell was successfully commissioned on the high-intensity powder diffractometer beamline, Wombat, at the Australian Nuclear Science and Technology Organisation by investigating the effect of pressure on the hydrothermal pseudomorphic conversion from SrSO4(celestine) to SrCO3(strontianite) at a constant temperature of 473 K and flow rate of 5 ml min−1. The results show that the increase of pressure exerts a nonlinear effect on the conversion rate, which first increases with increasing pressure from 14 to 20 MPa, and then decreases when pressure further increases to 24 MPa.

Cyanobacterial metabolites, both toxic and non-toxic, are a major problem for the water industry. Nanofiltration (NF) may be an effective treatment option for removing organic micropollutants, such as cyanobacterial metabolites, from drinking water due to its size exclusion properties. A rapid bench scale membrane test (RBSMT) unit was utilised to trial four NF membranes to remove the cyanobacterial metabolites, microcystin, cylindrospermopsin (CYN), 2-methylisoborneol (MIB) and geosmin (GSM) in two treated waters sourced from the Palmer and Myponga water treatment plants. Membrane fouling was observed for both treated waters; however, only minor differences were observed between feed waters of differing natural organic matter (NOM) concentration. Low molecular weight cut-off (MWCO), or 'tight' NF, membranes afforded average removals above 90% for CYN, while removal by higher MWCO, or 'loose' NF membranes was lower. MIB and GSM were removed effectively (above 75%) by tight NF but less effectively by loose NF. Microcystin variants (MCRR, MCYR, MCLR, MCLA) were removed to above 90% by tight NF membranes; however, removal using loose NF membranes depended on the hydrophobicity and charge of the variant. Different NOM concentration in the treated waters had no effect on the removal of cyanobacterial metabolites.

By using a non-aqueous solution as the mixing liquid, the washout resistance of the calcium deficient apatite biocement (cd-AB) was significantly improved, over that of the conventional method of using cd-AB with water as the liquid phase. In this study, premixed and injectable cd-AB was prepared, which had the advantage of being stable in the syringe and hardens only after being delivered to the defect area. The cd-AB powder with a Ca/P ratio of 1.5 consists of a mixture of tetracalcium phosphate (TTCP) and dicalcium phosphate anhydrous (DCPA). A solution of polylactide (PLA) in N-methyl-2-pyrrolidone (NMP) was used as the liquid phase of the premixed cd-AB. The premixed cd-AB paste injected into an aqueous environment exhibited excellent washout resistance. The premixed cd-AB had longer setting time and lower compressive strength than conventional cd-AB. The hydration products of premixed cd-AB were a mixture of calcium deficient hydroxyapatite (cd-HA) and PLA. In vitro Tris–HCl immersion tests demonstrated that the premixed cd-AB could be degradable. The results revealed that the premixed cd-AB was cytocompatible and had no adverse effects on the attachment and proliferation of MG-63 osteoblast-like cells in vitro. The most distinct advantages of premixed and injectable PLA-modified cd-AB were its excellent washout resistance and in vitro degradability, suggesting that it may be a promising candidate for bone repair.