The finite element analysis of equal channel angular pressing (ECAP) considering the strain path dependence of the work hardening of metals

It is widely known that extreme grain refinement of metals can be attained through multiple passes of equal channel angular pressing (ECAP). Such processing can follow various strain paths, which correspond to different work hardening behaviors of the material being deformed. The available finite element analyses (FEA) of multiple pass ECAP do not consider this strain path effect, and employ a single stress–effective strain curve of the material for all passes. The present paper presents a FEA of a two pass ECAP processing of copper following route C. This processing route involves the shearing of the material in the same plane as in the first pass, but in a reversed shear direction. The experimental stress–strain curve of the material, considering this strain path change, was determined through reversed torsion at various strain levels associated with the strain heterogeneity in the material caused by the first ECAP pass. The consideration of the strain path effects changed the final strain distribution in the material and led to a lower punch force in the second pass, in comparison with the results from the analysis considering a single stress–strain curve for all passes.     

Urban Walkability Design Using Virtual Population Simulation

We present a system to generate a procedural environment that produces a desired crowd behaviour. Instead of altering the behavioural parameters of the crowd itself, we automatically alter the environment to yield such desired crowd behaviour. This novel inverse approach is useful both to crowd simulation in virtual environments and to urban crowd planning applications. Our approach tightly integrates and extends a space discretization crowd simulator with inverse procedural modelling. We extend crowd simulation by goal exploration (i.e. agents are initially unaware of the goal locations), variable‐appealing sign usage and several acceleration schemes. We use Markov chain Monte Carlo to quickly explore the solution space and yield interactive design. We have applied our method to a variety of virtual and real‐world locations, yielding one order of magnitude faster crowd simulation performance over related methods and several fold improvement of crowd indicators.     

Hungarian algorithm for subcarrier assignment problem using GPU and CUDA

General purpose graphics processing units (GPGPUs) have gained much popularity in scientific computing to speedup computational intensive workloads. Resource allocation in terms of power and subcarriers assignment, in current wireless standards, is one of the challenging problems due to its high computational complexity requirement. The Hungarian algorithm (HA), which has been extensively applied to linear assignment problems (LAPs), has been seen to provide encouraging result in resource allocation for wireless communication systems. This paper presents a compute unified device architecture (CUDA) implementation of the HA on graphics processing unit (GPU) for this problem. HA has been implemented on a parallel architecture to solve the subcarrier assignment problem and maximize spectral efficiency. The proposed implementation is achieved by using the “Kuhn‐Munkres” algorithm with effective modifications, in order to fully exploit the capabilities of modern GPU devices. A cost matrix for maximum assignment has been defined leading to a low complexity matrix compression along with highly optimized CUDA reduction and parallel alternating path search process. All these optimizations lead to an efficient implementation with superior performance when compared with existing parallel implementations.     

SDN‐DMM for intelligent mobility management in heterogeneous mobile IP networks

Mobility management applied to the traditional architecture of the Internet has become a great challenge because of the exponential growth in the number of devices that can connect to the network. This article proposes a Software‐Defined Networking (SDN)‐based architecture, called SDN‐DMM (SDN‐Distributed Mobility Management), that deals with the distributed mode of mobility management in heterogeneous access networks in a simplified and efficient way, ensuring mainly the continuity of IP sessions. Intent‐based mobility management with an IP mapping schema for mobile node identification offers optimized routing without tunneling techniques, hence, an efficient use of the network infrastructure. The simplified mobility control API reduces both signaling and handover latency costs and provides a better scalability and performance in comparison with traditional and SDN‐based DMM approaches. An analytical evaluation of such costs demonstrated the better performance of SDN‐DMM, and a proof of concept of the proposal was implemented in a real environment.     

Contributions from cognitive engineering to requirements specifications for complex sociotechnical systems: A case study in the context of healthcare in Brazil

This paper aims at presenting a case study on the use of human factors and ergonomics to enhance requirement specifications for complex sociotechnical system support tools through enhancing the understanding of human performance within the business domain and the indication of high‐value requirements candidates to information technology support. This work uses methods based on cognitive engineering to build representations of the business domain, highlighting workers’ needs, and contributing to the improvement of software requirements specifications, used in the healthcare domain. As the human factors discipline fits between human sciences and technology design, we believe that its concepts can be combined with software engineering to improve understanding of how people work, enabling the design of better information technology.     

Mixed Logical Dynamical Nonlinear Model Predictive Controller for Large‐Scale Solar Fields

This paper presents a control algorithm for reducing heat losses caused by clouds in large solar fields. The formulation is based on a Mixed Logical Dynamical (MLD) representation of the solar field plus the application of a Practical Nonlinear Model Predictive Controller (PNMPC) for calculating the optimal control action. The main purpose of the controller is to deactivate fields with inlet temperature greater than outlet temperature and to manipulate the oil flow rate of the activated fields for tracking the reference of the outlet temperature. A simplified lumped parameters model is used for prediction and simulation of the solar fields.     

Mechanical properties of bio compatible functional prototypes for joining applications in clinical dentistry

In the presented research, work investigations have been made for mechanical properties of the functional prototypes prepared from biocompatible filament of fused deposition modelling (FDM), comprising of hydroxyapatite (HAp), polypropylene (PP) and polyvinyl chloride (PVC). The functional prototypes will be used in clinical dentistry (mainly for joining application for job-type production activities). The filament has been prepared in house using twin screw extrusion process. For evaluation purpose, standard tensile specimens as per ASTM D-638 have been prepared on FDM. This study highlights the effect of three parameters of FDM (namely: infill percentage, layer thickness and speed of extrusion head) on the mechanical properties (namely: load at peak and load at break). The results of the study suggest that infill density has majorly contributed, 92% on load at peak and 89% for load at break, and deposition speed has very less contribution i.e., 1% towards the mechanical strength of the specimen. Further, the results are supported with thermal analysis using differential scanning calorimeter (DSC), which ensures that the specimen prepared are thermally stable and can be put in for joining applications for job-type production activities in clinical dentistry.     

Patient visits in poorly developed territories: a case study with community health workers

In this paper, we study the effects of poor conditions of territories in patient visits performed by community health workers and the consequences to primary care policies. We carried a case study with community health workers in Rio de Janeiro, Brazil, including ethnographic observations in two primary healthcare clinics. Moreover, we present an analysis of the collected data with the support of the function resonance analysis method and we point out relations between the findings and the execution of the primary healthcare policy in a systemic approach. Thus, our study highlights the impacts of work situations in the health assistance of poorly developed communities, indicating how community health workers cope with adverse conditions, and how such situations affect the effectiveness of primary care policies.     

Automated conceptual model clustering: a relator-centric approach

Software and Systems Modeling - In recent years, there has been a growing interest in the use of reference conceptual models to capture information about complex and sensitive business domains...     

Disclosing the Role of Defect-Engineered Metal–Organic Frameworks in Mixed Matrix Membranes for Efficient CO2 Separation: A Joint Experimental-Computational Exploration

Incorporation of defects in metal–organic frameworks (MOFs) offers new opportunities for manipulating their microporosity and functionalities. The so-called “defect engineering” has great potential to tailor the mass transport properties in MOF/polymer mixed matrix membranes (MMMs) for challenging separation applications, for example, CO₂ capture. This study first investigates the impact of MOF defects on the membrane properties of the resultant MOF/polymer MMMs for CO₂ separation. Highly porous defect-engineered UiO-66 nanoparticles are successfully synthesized and incorporated into a CO₂-philic crosslinked poly(ethylene glycol) diacrylate (PEGDA) matrix. A thorough joint experimental/simulation characterization reveals that defect-engineered UiO-66/PEGDA MMMs exhibit nearly identical filler–matrix interfacial properties regardless of the defect concentrations of their parental UiO-66 filler. In addition, non-equilibrium molecular dynamics simulations in tandem with gas transport studies disclose that the defects in MOFs provide the MMMs with ultrafast transport pathways mainly governed by diffusivity selectivity. Ultimately, MMMs containing the most defective UiO-66 show the most enhanced CO₂/N₂ separation performance—CO₂ permeability = 470 Barrer (four times higher than pure PEGDA) and maintains CO₂/N₂ selectivity = 41—which overcomes the trade-off limitation in pure polymers. The results emphasize that defect engineering in MOFs would mark a new milestone for the future development of optimized MMMs.