Thermophysical properties of processed meat and poultry products

Thermophysical properties of various meat and poultry emulsions were evaluated at four temperatures (20, 40, 60 and 80 °C). Thermal conductivities (0.26–0.48 W m⁻¹ K⁻¹) increased linearly with temperature between 20 and 60 °C. Between 60 and 80 °C, it remained constant for most products except bologna. Curves for thermal conductivity as a function of temperature could be roughly grouped into two different categories: products containing meat particles and those containing meat emulsions. The application of various models was investigated for thermal conductivity prediction. It was found that a three phase structural based Kirscher model had the potential for predicting thermal conductivities with acceptable accuracy. Densities decreased slightly as a function of temperature from 20 to 40 °C. A transition phase was observed from 40 to 60 °C, which was followed by a decrease from 60 to 80 °C. There was a decrease of about 50 kg m⁻³ between the density of a raw product at room temperature (at maximum 1070 kg m⁻³) and the product heated to 80 °C (at minimum 970 kg m⁻³), due to the gelation or setting of the structure. After a transition period from 10 to 30 °C, the heat capacity increased linearly from 30 to 80 °C, and ranged from 2850 to 3380 J kg⁻¹ °C⁻¹, respectively. Densities and heat capacities were strongly influenced by the carbohydrate content (i.e. as the carbohydrate content increased the density decreased). The salt content adversely affected thermal conductivity and thermal diffusivity values. However, these parameters increased with moisture content.     

Developing Stepwise m5 Tree Model to Determine the Influential Factors on Rainfall Prediction and to Overcome the Greedy Problem of its Algorithm

Water Resources Management - Large scale climatic phenomenon with lag time may be used as essential variables for stepwise prediction of rainfall, but the interaction of these signals on the...     

Microbiological Aspects of Ozone Applications in Food: A Review

ABSTRACT: Ozone is a powerful antimicrobial agent that is suitable for application in food in the gaseous and aqueous states. Molecular ozone or its decomposition products (for example, hydroxyl radical) inactivate microorganisms rapidly by reacting with intracellular enzymes, nucleic material and components of their cell envelope, spore coats, or viral capsids. Combination of ozone with appropriate initiators (for example, UV or H₂O₂) results in advanced oxidation processes (AOPs) that are potentially effective against the most resistant microorganisms; however, applications of AOPs in food are yet to be developed. When applied to food, ozone is generated on-site and it decomposes quickly, leaving no residues. Ozone is suitable for decontaminating produce, equipment, food-contact surfaces, and processing environment.     

Efficacy of Ozone Against Escherichia coli O157:H7 on Apples

Apples were inoculated with Escherichia coli O157:H7 and treated with ozone. Sanitization treatments were more effective when ozone was bubbled during apple washing than by dipping apples in pre‐ozonated water. The corresponding decreases in counts of E. coli O157:H7 during 3‐min treatments were 3.7 and 2.6 log₁₀ CFU on apple surface, respectively, compared to < 1 log₁₀ CFU decrease in the stem‐calyx region in both delivery methods. Optimum conditions for decontamination of whole apples with ozone included a pretreatment with a wetting agent, followed by bubbling ozone for 3 min in the wash water, which decreased the count of E. coli O157:H7 by 3.3 log₁₀CFU/g.     

MODELING AND SIMULATION OF SPARK IGNITION ENGINES

ABSTRACT

Modeling is important because it saves time, effort and cost needed for engine development and prediction of performance. In this work, losses due to imperfect construction of the real engine, including progressive combustion, valve timing and heat transfer have been modeled besides engine friction. Hence, it becomes possible to convert the output of the fuel-air cycle into net brake performance. Simulation of engine performance was carried out by varying engine speed, compression ratio and spark advance over wide range. Hence, it was possible to compare the results with those from experiments on a single cylinder engine. The model predictions were found to compare favourably with experiment within 4·6% in power and 2·9% in SFC. The losses considered in this work amount to about 14% of the fuel energy input.     

PERFORMANCE OF AUTOMOTIVE RECIPROCATING ENGINES WITH DIFFERENT FUELS

ABSTRACT

A single cylinder reciprocating engine test rig was used to measure power output, specific fuel consumption, exhaust gas temperature and energy balance for different speeds, air-fuel ratios and compression ratios with gasoline and diesel oil as fuels. Comparison of the results for the same compression ratios and range of running speeds shows that gasoline produces higher power and exhaust temperatures than diesel oil. However, it produced less thermal efficiency up to 2000 rpm speed. The energy balance shows slightly higher percentage in power and exhaust energy but markedly less radiation energy to the atmosphere with diesel oil.     

A POTENTIALLY CAPABLE KODEL FOR PREDICTING COMBUSTOR LINER TEMPERATURE IN CAS TURBINES

Abstract

The continuous trend towards using higher pressure ratio engines combined with the effects of using fuels of high aromatic content and boiling range and less hydrogen content, have Increased the vulnerability of combustor wall to high temperatures.

In order to overcome this difficulty and optimize the quantity and distribution of cooling air, prediction of temperature should be as accurate as possible.

In this work an empirical model has been developed, which enables predicting liner temperature with 7% deviation for different types of combustors at different loading conditions using fuels of wide range of aromatic content, hydrogen percent and boiling range. This is in comparison with 60%-100percnt; obtained with other models.     

Selecting the Best Flood Flow Frequency Model Using Multi-Criteria Group Decision-Making

Several criteria should be considered when selecting a probability distribution to describe hydrological data. This study examines how multiple criteria can be combined to make the best selection. Selection becomes more difficult and subjective when more than two criteria are used to determine the best distribution. Under these conditions, multi-criteria decision-making is necessary. In this study, 12 distributions were tested and compared for flood frequency analysis based on five selection criteria: root mean square error, Kolmogorov-Smirnov test statistic, relative average bias, modified Anderson-Darling test, and deviation in skewness and kurtosis. The comparisons are made using a multi-criteria group decision-making (MCGDM) based on ordered weighted averaging (OWA). Two preemptive goal programming models based on variance and entropy methods for a predetermined level of optimism by a group of decision-makers, determined the weight of the OWA operator. The model was applied to a case study of Mahabad River, a major river flowing into Lake Urmia in northwestern Iran. A sensitivity analysis of the results of MCGDM was done by changing the degree of optimism of the decision-makers. The results of sensitivity analysis showed the dependence of the rankings to the optimism degrees of the decision-makers. The 3-parameter Weibull (WBL3) and Pearson type 3 (PE3) distributions had the best results for Mahabad River flood data. A Monte Carlo simulation was conducted to test the ability of the models. It was concluded from the findings of the simulation that the PE3 distribution is the most appropriate for short sample sizes, while WBL3 is preferable for larger sample sizes.     

New Approach for Sediment Yield Forecasting with a Two-Phase Feedforward Neuron Network-Particle Swarm Optimization Model Integrated with the Gravitational Search Algorithm

Water Resources Management - Predicting sediment yield is an important task for decision-makers in environmental monitoring and water management since the benefits of applying non-linear,...