Can the uncertainty in brass casting blending problem be managed? A probability/possibility transformation approach

Problems about the uncertainty in raw material compositions are a critical issue for the blending problems. It is feared that uncertainty in raw material compositions would often cause percent values of the actual blend to go out of specification limits. In this paper, the aleatory and epistemic uncertainties have been handled simultaneously in a blending optimization problem for brass casting. The aleatory and epistemic uncertainties are modeled by using probability and possibility theories respectively. However, the probabilistic and the possibilistic uncertainties are different from the each other. Therefore to solve the mathematical model, including these uncertainties, a transformation of any type of uncertainty to the other is needed. In this study, probabilistic uncertainties are transformed to the possibilistic uncertainties by considering Rong and Lahdelma’s (2008) and the Dubois, Prade, and Sandri (1993) and Dubois, Foulloy, Mauris, and Prade (2004) transformation approaches. This transformation process converts the former model to a possibilistic model. Then the possibilistic models, obtained from each transformation, are solved by using α cuts approach. The solutions of the two possibilistic models have shown that the model, which uses Dubois’s transformation, prepares blends with lower cost than the other model, which uses Rong and Lahdelma’s transformation.     

Experimental study of a micro-scale sloped solar chimney power plant

Journal of Mechanical Science and Technology - Solar chimney power plants (SCPP) are structures that have the potential to generate a significant amount of electrical energy without harming the...     

A simulation as a service cloud middleware

Many seemingly simple questions that individual users face in their daily lives may actually require substantial number of computing resources to identify the right answers. For example, a user may want to determine the right thermostat settings for different rooms of a house based on a tolerance range such that the energy consumption and costs can be maximally reduced while still offering comfortable temperatures in the house. Such answers can be determined through simulations. However, some simulation models as in this example are stochastic, which require the execution of a large number of simulation tasks and aggregation of results to ascertain if the outcomes lie within specified confidence intervals. Some other simulation models, such as the study of traffic conditions using simulations may need multiple instances to be executed for a number of different parameters. Cloud computing has opened up new avenues for individuals and organizations with limited resources to obtain answers to problems that hitherto required expensive and computationally-intensive resources. This paper presents SIMaaS, which is a cloud-based Simulation-as-a-Service to address these challenges. We demonstrate how lightweight solutions using Linux containers (e.g., Docker) are better suited to support such services instead of heavyweight hypervisor-based solutions, which are shown to incur substantial overhead in provisioning virtual machines on-demand. Empirical results validating our claims are presented in the context of two case studies.     

Convergence of rule-of-thumb sizing and allocating rules of distributed generation in meshed power networks

This paper presents different approaches to find out and address some rules for distributed generation (DG) integrated mesh type networks, which can be used in the management of future power systems. There are so many influencing factors of efficiency in the integration of DG that we need to analyze these influencing factors obviously. Hence, carefully planning plays a key role in tackling these challenges in the future power systems. In contrast to the majority of existing observations, we focus on the case where the underlying states are multiple and single DG allocations with changing conditions. In several previous studies, the best single bus has been investigated under the specified conditions. However, it follows from the results of this study that all issues concerning DG strongly depend on power network structure and DG locations, and it is worth to note that the best location changes with penetration levels. Also, it is observed that the all buses show different characteristics in terms of DG integrations under the different cases, moreover their optimum size and power factor are different. It means that optimum bus in a network changes with the conditions. On the other hand, the problematic buses can be occurred in voltage profile after the DG integration. As a result, an investigation of rule of thumb approach is performed for evaluation of performance enhancement of DG integrated meshed networks. The results are also used to discuss the integration of DG management strategies under various operating conditions.     

Evaluation of greenhouse residues gasification performance in hydrogen production

In this study, a modeling study was carried out to investigate the potential of hydrogen production from greenhouse tomato and pepper residues blending in different rates (0%, 25%, 50%, 75% and 100%) by air-steam gasification. The numerical model developed for the gasification system assumes that all carbon in the mixture is gasified. Air to fuel rate and steam to fuel rates are 0.05 due to high content of O₂ in biomass residues. The gasifier temperature is 877 °C (1150 K) for developed model. According to the result of this study, increasing tomato residues blending rate increases hydrogen content of syngas. It is mainly caused by the content of O₂ in tomato residues being higher than content of O₂ in pepper residues. This study shows that the O₂ content of greenhouse residues is an important factor in syngas production, especially in H₂ production.     

Mechanical,chemical, thermal,and rheological properties of recycled PA6/ABS binary and PA6/PA66/ABS ternary blends

The effects of multiple injection molding cycles on the chemical and mechanical properties of PA6/ABS and PA6/PA66/ABS blends are investigated. The chemical structures of both PA6/ABS binary and PA6/PA66/ABS ternary blends do not alter after recycling process. For PA6/ABS binary blend, it is found that the tensile strength, strain at break, elastic modulus, impact strength, flexural strength, and modulus of recycled blend decrease by 6.49%, 15.19%, 21.00%, 9.41%, 7.09%, and 8.25%, respectively, while MFI increases by 23.59% as compared with the virgin blend. After five recycling process for PA6/PA66/ABS ternary blend, the tensile strength, strain at break, and impact strength of recycled blend decrease by 18.00%, 50.80%, and 87.27%, respectively. However, flexural strength and modulus of PA6/PA66/ABS blend increase slightly. For virgin PA6/PA66/ABS blend, MFI value was 7.7 g/10 min and with recycling this value showed an important increase to 31.56 g/10 min after five cycles. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 40810.     

Effect of high hydrostatic pressure on physicochemical and biochemical properties of milk

Interest in high hydrostatic pressure (HHP) applications on milk and dairy products has recently increased as HHP offers a new technology for food preservation to the food industry. Although HHP-induced microbial destruction, rennet or acid coagulation of milk and increase in cheese yield has been reported, the actual effect of HHP application on milk constituents still remains to be unexplained. Therefore, we have analyzed the effect of HHP on physicochemical and biochemical properties such as turbidity, pH and especially protein micelle surface hydrophobicity of milk proteins. To serve for this purpose, milk samples with different fat contents were pressurized from 110 to 440 MPa at 25 °C for 10 and 20 min. Turbidity decreased with pressure increase and there was a slight change in pH. In order to measure the extent of exposure of hydrophobic groups of proteins to HHP, the method described by Bonomi et al. [1], based on use of a fluorescent probe, was utilized. In the light of the results obtained, it can be concluded that HHP has an effect on non-covalent interactions and especially hydrophobic bonds in milk. As the pressure is increased from 110 to 440 MPa, the micelles possibly decompose into sub-micelles and the embedded hydrophobic areas inside these micelles re-position in such a way that they can readily interfere with the fluorescent marker, ANS. These results may lead to practical applications of HHP treatment in the dairy industry to produce microbiologically safe, minimally processed products with high nutritional and sensory quality and novel texture.     

One-pot two-step lipase-catalyzed synthesis of α,ω-thiophene-capped poly(ε-caprolactone) macromonomers and their use in electropolymerization

Macromonomers based on poly(ε-caprolactone) (PCL) with α,ω-thiophene functional end groups were prepared in bulk by enzymatic polymerization using immobilized Candida Antarctica lipase B (Novozym 435) as the catalyst. In the synthesis strategy, 3-thiophenemethanol was used to initiate the enzyme-assisted ring-opening polymerization of ε-caprolactone (ε-CL) to yield PCL with α-thiophene end group (initiation reaction, ThPCL) and then 3-thiopheneacetic acid was added to prepolymerized ε-CL to introduce ω-thiophene functionality in termination step (ThPCLTh). Macromonomers were characterized by ¹H and ¹³C NMR, FTIR, and GPC. Moreover, the obtained macromonomers were employed in electropolymerization experiments and copolymers with thiophene or pyrrole were synthesized through their end thiophene groups. These polymers were characterized by cyclic voltammetry (CV), FTIR, and scanning electron microscopy (SEM). Conductivity measurements were carried out by the four-probe technique.