Size effects in elastic-plastic functionally graded materials

We develop a strain gradient plasticity formulation for composite materials with spatially varying volume fractions to characterize size effects in functionally graded materials (FGMs). The model is grounded on the mechanism-based strain gradient plasticity theory and effective properties are determined by means of a linear homogenization scheme. Several paradigmatic boundary value problems are numerically investigated to gain insight into the strengthening effects associated with plastic strain gradients and geometrically necessary dislocations (GNDs). The analysis of bending in micro-size functionally graded foils shows a notably stiffer response with diminishing thickness. Micro-hardness measurements from indentation reveal a significant increase with decreasing indenter size. And large dislocation densities in the vicinity of the crack substantially elevate stresses in cracked FGM components. We comprehensively assess the influence of the length scale parameter and material gradation profile to accurately characterize the micro-scale response and identify regimes of GNDs relevance in FGMs.Ministry of Economy and Competitiveness of Spain through Grant MAT2014-58738-C3 People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme (FP7/2007–2013) under REA Grant agreement n 609405 (COFUNDPostdocDTU

Examining queue-jumping phenomenon in heterogeneous traffic stream at signalized intersection using UAV-based data

© 2020, Springer-Verlag London Ltd., part of Springer Nature. This research presents an in-depth microscopic analysis of heterogeneous and undisciplined traffic at the signalized intersection. Traffic data extracted from the video recorded using an unmanned aerial vehicle (UAV) at an approach of a signalized intersection is analyzed to study the within green time dynamics of traffic flow. Various parameters of Wiedemann 74, Wiedemann 99, and lateral behavior models used in microscopic traffic simulation package, Vissim, are calibrated for the local heterogeneous traffic. This research is aimed at exploring the queue-jumping phenomenon of motorbikes at signalized intersections and its impact on the saturation flow rate, travel time, and delay. The study of within green time flow dynamics shows that the flow of traffic within green time is not uniform. Surprisingly, the results indicate that the traffic flow for the first few seconds of the green time is significantly higher than the remaining period of green time, which shows a contradiction to the fact that traffic flow for the first few seconds is lower due to accelerating vehicles. Mode-wise traffic counted per second shows that this anomaly is attributed to the presence of motorbikes in front of the queue. Consequently, the outputs of simulation results obtained from calibrated Vissim show that the simulated travel time for motorbikes is significantly lower than the field-observed travel times even though the average simulated traffic flow matches accurately with the field-observed traffic flow. The findings of this research highlight the need to incorporate the queue-jumping behavior of motorbikes in the microsimulation packages to enhance their capability to model heterogeneous and undisciplined traffic

Rubber Clay Nanocomposites

The use of nanofillers allows the development of nanocomposites with improved properties and novel applications. The technological goal is possible due to the new compounding method that allows a particle dispersion in the nanometer scale increasing the specific surface area.Fil: Cova Sánchez, Mariajose. Instituto Nacional de Tecnología Industrial. Instituto Nacional de Tecnología Industrial - Caucho; Argentina. Universidad Nacional de San Martín. Instituto de Investigación e Ingeniería Ambiental. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación e Ingeniería Ambiental; ArgentinaFil: Bacigalupe, Alejandro. Universidad Nacional de San Martín. Instituto de Investigación e Ingeniería Ambiental. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación e Ingeniería Ambiental; Argentina. Instituto Nacional de Tecnología Industrial. Instituto Nacional de Tecnología Industrial - Caucho; ArgentinaFil: Escobar, Mariano Martin. Instituto Nacional de Tecnología Industrial. Instituto Nacional de Tecnología Industrial - Caucho; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Mansilla, Marcela Angela. Instituto Nacional de Tecnología Industrial. Instituto Nacional de Tecnología Industrial - Caucho; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

A common biological basis of obesity and nicotine addiction

J. Kaprio ja J. Tuomilehto työryhmien jäseniä (yht. 281).Peer reviewe

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Capacity Expansion Problem for Large Urban Transportation Networks

A traffic network design problem attempts to find optimal network expansion policies under budget constraints. This can be formulated as a bilevel optimization problem: the upper level determines the optimal link capacity expansion vector and the lower level determines the link flows subject to user equilibrium conditions. The upper level is a capacity expansion problem which minimizes the total system cost and can be solved using any optimization algorithm. In the present study, genetic algorithm (GA) is used in the upper level because of its modeling simplicity and ability to handle large problems. The proposed model is first applied to a small sized network and then to a medium sized test network and the results are compared with other existing solution approaches. The sensitivity analysis of the model is performed by designing the networks at different demand levels. The resilience of the solution when demand increases the design demand is also carried out. Finally, the network design for the city of Pune, India was taken as a case study. This is a large sized network having 1,131 links and 370 nodes. The capacity expansion is carried out under various budget scenarios and the results are discussed. This study shows the potential of GA to obtain a high quality solution for large network design problems

Intelligent Agent Optimization of Urban Bus Transit System Design

The transit route network design (TRND) problem seeks a set of bus routes and schedules that is optimal in the sense that it maximizes the utility of an urban bus system for passengers while minimizing operator cost. Because of the computational intractability of the problem, finding an optimal solution for most systems is not possible. Instead, a wide variety of heuristic and meta-heuristic approaches have been applied to the problem to attempt to find near-optimal solutions. This paper presents an optimization system that synthesizes aspects of previous approaches into a scalable, flexible, intelligent agent architecture. This architecture has successfully been applied to other transportation and logistics problems in both research studies and commercial applications. This study shows that this intelligent agent system outperforms previous solutions for both a benchmark Swiss bus network system and the very large bus system in Delhi, India. Moreover, the system produces in a single run a set of Pareto equivalent solutions that allow a transit operator to evaluate the trade-offs between operator costs and passenger costs. DOI: 10.1061/(ASCE)CP.1943-5487.0000095. (C) 2011 American Society of Civil Engineers

Hybrid Stochastic Cellular Automata-Driver-Vehicle-Object Simulation Model for Heterogeneous Traffic at Urban Signalized Intersections

The traffic flow at intersections is generally chaotic, and signalization is a control measure to reduce this chaos. Heterogeneous traffic at signalized intersections behave much differently from homogeneous traffic. Also, in many countries, nonlane-based traffic prevails; hence, designing control systems for such situations is a challenging task. Traffic simulation helps the analyst to model the behavior of such complex systems. Cellular automata (CA), a recent entrant in traffic flow modeling, represents the traffic flow by means of simple rules, and thus has proved to be a versatile tool in traffic simulation. The present study aims to develop a computationally efficient traffic flow simulation model integrating the concepts of cellular automata and driver-vehicle-objects, thus making a behavioral model of traffic. The model emphasizes the diversity in human behavior, and represents the traffic using the minimal modeling concept of CA. To represent multiple vehicle types, a multicell representation was adopted. Further, to address the issue of nonlane-based movement, new lateral movement rules were proposed. The model incorporated behavior at amber and lateral movements, thus attempting to achieve a near to reality representation of nonlane-based heterogeneous traffic. The model was calibrated and validated using delay data from selected intersections in India. This model was then used to predict saturation flows at signalized intersections. The model performed reasonably well in predicting the delays, but the saturation flow values showed up to 30% variability. DOI: 10.1061/(ASCE)CP.1943-5487.0000207. (C) 2013 American Society of Civil Engineers