Quasi-static and dynamic crushing behaviors of aluminum and steel tubes with a cutout

Tubular members are commonly used as an energy absorber in engineering structures and many such members have a cutout. In this study, the crushing behaviors of tubes with a cutout are characterized and the effects of cutout on the energy absorption capabilities of these tubes are quantified. Systematic parametric studies were carried out to study the effect of material properties, including yield and ultimate strength of material, strain rate effect, location of cutout, tube length and impact speed on the crushing behaviors and energy absorption capacity of aluminum and steel tubes. First, a numerical model was constructed with a commercial explicit finite element code. It will be first proven that the numerical simulation can produce sufficiently accurate results in an economic manner. Subsequently, the crushing behavior of aluminum and steel tubes with a cutout was experimentally characterized and their energy absorption capacity was evaluated in terms of mean crushing force, peak crushing force and specific energy absorption (SEA). Tubes of various lengths with a cutout located at different locations, subject to both quasi-static and dynamic impact loadings were considered. For steel tubes, the numerical simulation investigated the influence of the strain rate effect and variation in strain hardening ratio of the material. Empirical equations describing the mean and peak crushing forces of aluminum and steel tubes with a cutout were developed using linear and nonlinear regression methods applied to the results obtained from the numerical and experimental studies.     

THEORETICAL STUDY OF NONUNIFORM DROPLETS CONCENTRATION DISTRIBUTION ON VENTURI SCRUBBER PERFORMANCE

A new three-dimensional dispersion model has been developed and was used to study particulate removal operations in a venturi type scrubber. The model takes into account the effect of nonuniform droplets concentration distribution on the particulate removal efficiency of the scrubber of Brink and Contant (1958). Experimental data was used to test the results of the mathematical model. The results from the model are in good agreement with the experimental data. After validating the model, it was used to predict the effect of parameters such as liquid to gas flow rate ratio, gas throat velocity, and angle of the divergent section and nozzle diameter on the extent of nonuniformity of drops. Removal efficiency will increase with increasing uniformity of droplets concentration distribution. Thus, any factor that increases removal efficiency increases uniformity and vice versa. The factors affecting uniformity are: droplet diameter, liquid jet penetration length and size of scrubber.     

Bayesian estimation based on vague lifetime data

In Classical Bayesian approach, estimation of lifetime data usually is dealing with precise information. However, in real world, some informations about an underlying system might be imprecise and represented in the form of vague quantities. In these situations, we need to generalize classical methods to vague environment for studying and analyzing the systems of interest. In this paper, we propose the Bayesian estimation of failure rate and mean time to failure based on vague set theory in the case of complete and censored data sets. To employ the Bayesian approach, model parameters are assumed to be vague random variables with vague prior distributions. This approach will be used to induce the vague Bayes estimate of failure rate and mean time to failure by introducing and applying a theorem called “Resolution Identity” for vague sets. In order to evaluate the membership degrees of vague Bayesian estimate for these quantities, a computational procedure is investigated. In the proposed method, the original problem is transformed into a nonlinear programming problem which is then divided into eight subproblems to simplifying computations.     

Predicting roadheader performance by using artificial neural network

With growing use of roadheaders in the world and its significant role in the successful accomplishment of a tunneling project, it is a necessity to accurately predict performance of this machine in different ground conditions. On the other hand, the existence of some shortcomings in the prediction models has made it necessary to perform more research on the development of the new models. This paper makes an attempt to model the rate of roadheader performance based on the geotechnical and geological site conditions. For achieving the aim, an artificial neural network (ANN), a powerful tool for modeling and recognizing the sophisticated structures involved in data, is employed to model the relationship between the roadheader performance and the parameters influencing the tunneling operations with a high correlation. The database used in modeling is compiled from laboratory studies conducted at Azad University at Science and Research Branch, Tehran, Iran. A model with architecture 4-10-1 trained by back-propagation algorithm is found to be optimum. A multiple variable regression (MVR) analysis is also applied to compare performance of the neural network. The results demonstrate that predictive capability of the ANN model is better than that of the MVR model. It is concluded that roadheader performance could be accurately predicted as a function of unconfined compressive strength, Brazilian tensile strength, rock quality designation, and alpha angle R ² = 0.987. Sensitivity analysis reveals that the most effective parameter on roadheader performance is the unconfined compressive strength.     

On the ‘curiosity’ of electrical self‐heating,static charge and electromagnetic shielding effectiveness from carbon black/aluminium flakes reinforced epoxy‐resin composites

This paper shows the wide application range (such as electrical self‐heating and electromagnetic shielding effectiveness) of composites consisting of conductive carbon black/aluminum flakes (CBA) filler and epoxy insulative matrix. The effect of CBA content on the network structure of epoxy matrix was investigated in detail. Static electrical conductivity increases linearly with the increase of filler concentration at the interface in epoxy composites. The large decrease of the conductivity as a function of the temperature is analyzed in terms of the negative temperature coefficient of conductivity (NTCC) effect. The influence of viscosity, surface energy and barrier highest energy on the NTCC behaviour in the composite is also considered. Based on these results, a new interpretation is proposed to explain the NTCC phenomena by computing the swelling force among conductive phases. The correlations of conductivity during the temperature cycling and activation energy were analyzed. The effects of dynamic ageing at various temperatures on the resistivity are reported. Current–voltage–temperature characteristics for epoxy with different contents of CBA were examined in detail. A model based on the law of energy conservation is proposed to calculate the specific heat and amount of heat dissipation. The static charge of the epoxy–CBA composites was estimated. The correlation between electromagnetic wave‐shielding effectiveness (EMS), conductivity and frequency of epoxy composites with different filler contents is also discussed. Furthermore, the effect of annealing on EMS of epoxy composites was examined. © 2002 Society of Chemical Industry     

Algorithms for Quantum Branching Programs Based on Fingerprinting

In the paper, we develop a method for constructing quantum algorithms for computing Boolean functions by quantum ordered read-once branching programs (quantum OBDDs). Our method is based on ˉngerprinting technique and representation of Boolean functions by their characteristic polynomials. We use circuit notation for branching programs for desired algorithms presentation. For several known functions our approach provides optimal QOBDDs. Namely we consider such functions as MODm, EQn, Palindromen, and PERMn (testing whether given Boolean matrix is the Permutation Matrix). We also propose a generalization of our method and apply it to the Boolean variant of the Hidden Subgroup Problem.     

Thermodynamics of ionic-association in aqueous solutions of Ca and Mg organic salts using ion-selective electrode technique—II. benzoate, o-toloate, o-chlorobenzoate and salycylate

The stoichiometric association constants, K, the thermodynamic association constant, K_A, and the other thermodynamic parameters such as ΔS°, ΔH° and ΔG° for the association between each of the Ca and Mg ions with benzoate, o-toloate, o-chlorobenzoate and salycylate have been determined at 25°C, 35°C and 45°C in aqueous media. Ion-selective electrode technique has been used in the measurements of Ca and Mg ion activitiesThe trend of association behavior of both Ca and Mg aromatic salts could not be explained on the basis of pK_a of the mother organic acids but could be explained based on the trend of Hammet function σ of these salts themselves relative to the corresponding benzoate salt.     

Solving singular control problems using uniform trigonometrization method

This study investigates the application of a recently developed construct, the uniform trigonometrization method (UTM), to the singular control problems in chemical engineering. The UTM involves minimal modifications to the original problem, thereby generating near-singular control solutions that can be used for conceptual design and serve as an alternate to direct techniques like nested and simultaneous approaches. Eight classical singular control problems with known analytical solutions and three complex singular control problems from chemical engineering domain are solved in this study. The results obtained using the UTM for these problems are found to match well with the literature and are of higher resolution as compared to the results obtained using a direct pseudospectral-based solver. The ability of the UTM to handle complex chemical engineering problems with both singular controls and state path constraints has also been demonstrated in this study.     

Temperature and processing effects on lithium ion conductivity of solution-deposited lithium zirconium phosphate (LiZr2P3O12) thin films

Lithium zirconium phosphate (LiZr₂P₃O₁₂) thin films have been prepared on platinized silicon substrates via a chemical solution deposition approach with processing temperatures between 700°C and 775°C. Films that were subject to a single high-temperature anneal were found to crystallize at temperatures above 725°C. Crystallization was observed in films annealed after each deposited layer at 700°C and above. In both cases, grain size was found to increase with annealing temperature. Ion conductivity was found to increase with annealing temperature in singly annealed films. In per-layer annealed films ion conductivity was found to initially increase then decrease with increasing annealing temperature. A maximum ion conductivity of 1.6 × 10⁻⁶ S/cm was observed for the singly annealed 775°C condition, while a maximum ion conductivity of 5.8 × 10⁻⁷ S/cm was observed for the 725°C per-layer annealed condition. These results are consistent with an increasing influence of cross-plane, internal interface resistance and vapor phase carrier loss in the per-layer annealed samples. This work demonstrates that post-deposition processing methods can strongly affect the ion conducting properties of LiZr₂P₃O₁₂ thin films.     

Development of Si3Na/Al composite by pressureless melt infiltration

Pressureless infiltration process to synthesize Si3N4/Al composite was investigated. Al-2%Mg alloy was infiltrated into Si3N4 and Si3N4 containing 10% Al2O3 preforms in the atmosphere of nitrogen. It is possible to infiltrate Al-2%Mg alloy in Si3N4 and Si3N4 containing 10% Al2O3 preforms. The growth of the dense composite of useful thickness was facilitated by the presence of magnesium powder at the interface and by flowing nitrogen. During infiltration Si3N4 reacted with aluminium to form Si and AIN, the growth of composite was found to proceed in two ways, depending on the Al2O3 content in the initial preform. Firstly, preform without Al2O3 content gives rise to AIN, Al3.27Si0.47 and Al type phases after infiltration. Secondly, perform with 10% Al2O3 content gives rise to AIN-Al2O3 solid solution phase （AION）, MgAl2O4, Al and Si type phases. AlON phase was only present in composite, containing 10% Al2O3 in the Si3N4 preforms before infiltration.