Isogeometric level set topology optimization for elastoplastic plane stress problems

International Journal of Mechanics and Materials in Design - This article aims to utilize IsoGeometric analysis (IGA) and Level set method for topology optimization of elastoplastic plane stress...     

Robust Platelet Logistics Planning in Disaster Relief Operations Under Uncertainty: a Coordinated Approach

Resource sharing, as a coordination mechanism, can mitigate disruptions in supply and changes in demand. It is particularly crucial for platelets because they have a short lifespan and need to be transferred and allocated within a limited time to prevent waste or shortages. Thus, a coordinated model comprised of a mixed vertical-horizontal structure, for the logistics of platelets, is proposed for disaster relief operations in the response phase. The aim of this research is to reduce the wastage and shortage of platelets due to their critical role in wound healing. We present a bi-objective location-allocation robust possibilistic programming model for designing a two-layer coordinated organization strategy for multi-type blood-derived platelets under demand uncertainty. Computational results, derived using a heuristic ε-constraint algorithm, are reported and discussed to show the applicability of the proposed model. The experimental results indicate that surpluses and shortages in platelets remarkably declined following instigation of a coordinated disaster relief operation.     

Cyclic behavior of concentrically braced frames with built-up braces composed of channel sections

Concentrically braced frames are earthquake resistant systems commonly used in buildings. Seismic behavior of this type of structures is affected by their configurations, brace properties, and brace to gusset plate connections. In this paper, the results of three experiments conducted to investigate the cyclic behavior of concentrically braced frames with braces built-up of double channels are reported. Significant damage was observed in beam to column connections. Large out of plane deformation of braces caused some cracks in the connector welds; however they did not result in fracture. Although large drift was applied to the frames, no brace fracture was observed. Furthermore, experiments showed that the majority of compressive strength in post-buckling state and a noticeable portion of tensile strength originated from frame action. By choosing connector spacing as the main parameter and using finite element models, a parametric study was performed to investigate the effect of this parameter on this type of frames with two different details of brace to gusset plate connections. It is observed that reducing the connector spacing increases the inelastic strain demand in braces and decreases it in gusset plates. However, gusset plates, which accommodate 2t linear clearance, are less dependent on connector spacing, compared to those accommodating 6t elliptical clearance. It seems that the limitations of slenderness ratio of individual section, stipulated in current seismic provisions, need further study.     

Prediction of FRP-confined compressive strength of concrete using artificial neural networks

Strengthening and retrofitting of concrete columns by wrapping and bonding FRP sheets has become an efficient technique in recent years. Considerable investigations have been carried out in the field of FRP-confined concrete and there are many proposed models that predict the compressive strength which are developed empirically by either doing regression analysis using existing test data or by a development based on the theory of plasticity. In the present study, a new approach is developed to obtain the FRP-confined compressive strength of concrete using a large number of experimental data by applying artificial neural networks. Having parameters used as input nodes in ANN modeling such as characteristics of concrete and FRP, the output node was FRP-confined compressive strength of concrete. The idealized neural network was employed to generate empirical charts and equations for use in design. The comparison of the new approach with existing empirical and experimental data shows good precision and accuracy of the developed ANN-based model in predicting the FRP-confined compressive strength of concrete.     

Cloud Marginal Resource Allocation: A Decision Support Model

Mobile Networks and Applications - One of the significant challenges for cloud providers is how to manage resources wisely and how to form a viable service level agreement (SLA) with consumers to...     

The explosion at institute: Modeling and analyzing the situation awareness factor

In 2008 a runaway chemical reaction caused an explosion at a methomyl unit in West Virginia, USA, killing two employees, injuring eight people, evacuating more than 40,000 residents adjacent to the facility, disrupting traffic on a nearby highway and causing significant business loss and interruption. Although the accident was formally investigated, the role of the situation awareness (SA) factor, i.e., a correct understanding of the situation, and appropriate models to maintain SA, remain unexplained. This paper extracts details of abnormal situations within the methomyl unit and models them into a situational network using dynamic Bayesian networks. A fuzzy logic system is used to resemble the operator’s thinking when confronted with these abnormal situations. The combined situational network and fuzzy logic system make it possible for the operator to assess such situations dynamically to achieve accurate SA. The findings show that the proposed structure provides a useful graphical model that facilitates the inclusion of prior background knowledge and the updating of this knowledge when new information is available from monitoring systems.     

An innovative approach for bond strength modeling in FRP strip-to-concrete joints using adaptive neuro–fuzzy inference system

Engineering with Computers - In this study, a new computational approach for determination of the bond strength of fibre reinforced polymer (FRP) strip-to-concrete joints is presented based on...     

Adsorption behavior of Cr(VI) on modified natural zeolite by a new bolaform N,N,N,N',N',N'-hexamethyl-1,9-nonanediammonium dibromide reagent

The demand for effective adsorbents is to increase in response to the widespread recognition of the deleterious health effects of Cr(VI)-oxyanions exposure through drinking water. In this study, Cr(VI)-oxyanions uptake from aqueous solutions by a new bolaform N,N,N,N',N',N'-hexamethyl-1,9-nonanediammonium dibromide reagent-modified natural zeolitic materials from Zahedan, Iran, was investigated using batch technique. Spectrophotometry method was used for Cr determination. The Cr(VI)-solution concentration varied between 2 and 104 mg L(-1). It was shown that the Cr(VI) uptake strongly depended on pH. The maximum removal of Cr(VI) occurred in acidic media at pH<1.5. The amounts of Cr(VI) adsorbed increased with increase in dose of both adsorbents and their contact time. Based on results an adsorption mechanism has been suggested. The adsorption data for modified zeolite using the amine was consistent with Langmuir isotherm equation and the equilibrium data was analyzed using the Langmuir isotherm.     

Adaptive neuro‐fuzzy inference modelling and sensitivity analysis for capacity estimation of fiber reinforced polymer‐strengthened circular reinforced concrete columns

In this study, a fuzzy logic‐based model for predicting the ultimate strength of FRP‐confined circular reinforced concrete (RC) columns is presented. The adaptive neuro‐fuzzy inference system (ANFIS) model was generated using valid experimental data with seven input variables. Input parameters were considered in such a way that all the parameters affecting the compressive strength of the column were simultaneously involved. Different models for compressive strength of fiber reinforced polymer (FRP)‐confined concrete including the model in American Concrete Institute (ACI), to calculate the maximum stress endured by the column under axial load, were presented and compared with the results of the ANFIS model. Also, for similarity to other models, the ACI equation for calculating the maximum compressive strength tolerated by a column was considered without reducing coefficients as ACI‐N and was compared with other models. The results obtained from the ANFIS model were compared with results from other models. ANFIS model showed the highest accuracy among all models in predicting the experimental results.     

Shear strength estimation of reinforced concrete beam–column sub‐assemblages using multiple soft computing techniques

The aim of the present study is to propose innovative predictive models for shear capacity of reinforced concrete (RC) exterior joints in terms of multiple soft computing techniques. Existing models were evaluated and by a preliminary sensitivity analysis, seven parameters including compressive strength of concrete, product of the yield stress and the reinforcement ratio of the joint stirrups, the effective width of the joint panel, cross‐sectional column width, beam tensile longitudinal reinforcement ratio, beam compressive longitudinal reinforcement ratio, and column longitudinal reinforcement ratio were considered. Then, a large data set having the details of experimental programs on shear capacity of exterior RC beam–column joints was provided. The experimental data were utilized in developing the proposed models. After verification of the new models against available database, their efficiency compared with existing models was confirmed. Finally, a sensitivity analysis was performed in order to find the relative importance of each input parameter on the shear strength of RC joints. The results indicated that the beam reinforcement is the most important factor in shear capacity estimation of exterior RC beam–column connections.