Heat transfer and thermal stress analysis in grooved tubes

Heat transfer and thermal stresses, induced by temperature differences in the internally grooved tubes of heat transfer equipment, have been analysed numerically. The analysis has been conducted for four different kinds of internally grooved tubes and three different mean inlet water velocities. Constant temperature was applied from the external surface of the tube. Energy and governing flow equations were solved using finite difference scheme. Finite element method (FEM) was used to compute the thermal stress fields. Grooving effects on the thermal stress ratio have been discussed. As a result, maximum thermal stress occurs in the case ofp =d for all water inlet velocities. The maximum thermal stress ratio positions inside the tube have been indicated as MX for all investigated cases. In the light of the thermal stress values, various designs can be applied to reduce thermal stress in grooved tubes.     

Flexibility Based Approach for Damage Characterization: Benchmark Application

A flexibility based damage characterization technique is described and its performance is examined in the context of Phase 1 of the benchmark study developed by the IASC-ASCE SHM Task Group. Noteworthy features of the analytical development are: (1) the methodology used to extract a matrix that is proportional to the flexibility when the excitation is stochastic; (2) the technique used to interrogate the changes in flexibility (or flexibility proportional matrices) with regards to the location of the damage; and (3) the method used to quantify the damage without the use of a model. The strategy proved successful in all the cases considered.     

Bi-modal emotion recognition from expressive face and body gestures

Psychological research findings suggest that humans rely on the combined visual channels of face and body more than any other channel when they make judgments about human communicative behavior. However, most of the existing systems attempting to analyze the human nonverbal behavior are mono-modal and focus only on the face. Research that aims to integrate gestures as an expression mean has only recently emerged. Accordingly, this paper presents an approach to automatic visual recognition of expressive face and upper-body gestures from video sequences suitable for use in a vision-based affective multi-modal framework. Face and body movements are captured simultaneously using two separate cameras. For each video sequence single expressive frames both from face and body are selected manually for analysis and recognition of emotions. Firstly, individual classifiers are trained from individual modalities. Secondly, we fuse facial expression and affective body gesture information at the feature and at the decision level. In the experiments performed, the emotion classification using the two modalities achieved a better recognition accuracy outperforming classification using the individual facial or bodily modality alone.     

User behavior modeling of voice communications: an empirical study

In this study, analysis and modeling of arrival and service processes are presented in a comprehensive fashion in order to determine statistical properties of voice traffic from end‐user perspective in accordance with the queueing theory. For the first time in the literature, we introduce a user centric approach and examine these services considering both flow directions of voice traffic, the uplink and the downlink as opposed to existing studies with the network centric approach. In our study, we use experimental data composed of actual phone calls collected from 2G/3G networks. To achieve this, we designed and implemented a data collection system for mobile users and compared the results by using data from an operational cellular network. In order to determine the time correlation of voice calls, Hurst parameter estimation methods are used. On the basis of the outcomes, independency of call arrivals is shown. Additionally, it is shown that calls acquired from user and network centric approaches are both Poisson distributed. Next, looking at the problem from service process perspective, thorough analyses are performed to determine mathematical models that can best characterize call holding times. Maximum likelihood estimation and expectation maximization algorithm are used, and it is shown that the optimum mathematical model for the characterization of call holding times is the lognormal distribution family. Copyright © 2014 John Wiley & Sons, Ltd.     

Evaluation of nanoparticulate fillers for development of shape memory polyurethane nanocomposites

The effects of nano-size fillers on shape memory (SM) properties of polyurethane (PU) nanocomposites were evaluated. Organoclay, carbon nanofiber (CNF), silicon carbide (SiC), and carbon black (CB) were selected as the fillers in an attempt to reinforce the PU and to obtain significantly increased shape recovery stress. The shape memory PU was synthesized from diphenylmethane diisocyanate, 1,4-butanediol, and poly(caprolactone)diol, the latter with a molecular weight of 4000 g/mol. The composites were prepared by melt mixing of extended chain PU with the fillers. The shape memory behavior was triggered by heating the specimen above the melting point of the crystalline soft segment. Our results indicate that exfoliated organoclay significantly augments SM performance, while CNF and SiC diminish it by interfering with crystallization of the soft segment. CB destroys the shape memory properties beyond a certain loading. Better SM performance with organoclay can be attributed to mechanical reinforcement without much interference with the soft segment crystallinity. The reduction of soft segment crystallinity in the presence of CNF and SiC was analyzed. It was found that the extent of crystallinity, as well as the crystallization temperature, was significantly reduced in the presence of these fillers.     

A fracture-based model for FRP debonding in strengthened beams

This paper presents an experimental and analytical research study aimed at understanding and modeling of debonding failures in fiber reinforced polymer (FRP) strengthened reinforced concrete (RC) beams. The experimental program investigated debonding failure modes and mechanisms in beams strengthened in shear and/or flexure and tested under monotonic loading. A newly developed fracture mechanics based model considers the global energy balance of the system and predicts the FRP debonding failure load by characterizing the dominant mechanisms of energy dissipation during debonding. Validation of the model is performed using experimental data from several independent research studies and a design procedure is outlined.     

Synthesis,Characterization, Crystal Structures and Thermal and Fluorescence Studies of Dinuclear and Polymeric Silver(I) Complexes of 5,5-Diethylbarbiturate with 2,5-Dimethylpyrazine and Piperazine Involving Ag–Ag Interactions

Two silver(I) complexes, [Ag(dmpyz)₂][Ag(barb)₂] (1) and {[Ag(ppz)][Ag(barb)₂]·H₂O} _n (2) (barb = 5,5-diethylbarbiturate, dmpyz = 2,5-dimethylpyrazine and ppz = piperazine), have been synthesized and characterized by elemental analyses, IR, thermal analysis (TG-DTA) and single-crystal X-ray diffraction. Complex 1 consists of [Ag(dmpyz)₂]⁺ and [Ag(barb)₂]^? ions in which the silver(I) ions are linearly coordinated by two dmpyz or two barb ligands. These two ions are connected by strong Ag–Ag interactions (Ag–Ag = 2.896 (1) Å). Complex 2 is a 1D coordination polymer in which the silver(I) ions are bridged by the ppz ligands in a linear fashion, leading to a zigzag chain of [Ag(ppz)] _n ⁺ , which interacts with the [Ag(barb)₂]^? units by Ag–Ag interactions of 3.183 (1) Å. The 1D chains are further assembled to form 3D networks by strong N–H···O and OW–H···O hydrogen bonds. IR spectra and TG-DTA data are in agreement with the crystal structures. The fluorescent properties of 1 were also evaluated.     

Homofermentative lactic acid bacteria of a traditional cheese, Comlek peyniri from Cappadocia region

Comlek peyniri is a typical artisanal cheese in Central Anatolia. This type of cheese was made by using the indigenous lactic acid bacteria (LAB) flora of cow or ewes' milk. Majority of the samples were taken from fresh cheese because the aim was to isolate homofermentative LAB. Initially 661 microbial isolates were obtained from 17 cheese samples. Only 107 were found to be homofermentative LAB. These isolates were selected and identified by using both phenotypic and molecular methods. Phenotypic identification included curd formation from skim milk, catalase test, Gram staining and light microscopy, growth at different temperatures and salt concentrations, arginine hydrolysis, gas production from glucose, and carbohydrate fermentation. Molecular identification was based on the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) of the 16S rRNA gene-ITS (internally transcribed spacer) region. By combining the phenotypic and molecular identification results, isolates belonging to each of the following genera were determined at species or subspecies level: 54 Lactococcus lactis subsp. lactis, 21 Enterococcus faecium, 3 Ec. faecalis, 2 Ec. durans, 10 Ec. sp., 15 Lactobacillus paracasei subsp. paracasei, and 2 Lb. casei strains. Technological characterisation was also performed by culturing each of the strains in UHT skim milk, and by monitoring pH change and lactic acid production at certain time intervals through the 24 h incubation. Results of the technological characterisation indicated that 33% of the isolates (35 strains) were capable of lowering the pH of UHT milk below 5.3 after 6 h incubation at 30 degrees C. Thirty four of these strains were Lc. lactis subsp. lactis, and only one was an Ec. faecium strain.     

Temperature distribution in nuclear fuel rod and variation of the neutronic performance parameters in (D–T) driven hybrid reactor system

Temperature distribution in nuclear fuel rod and variation of the neutronic performance parameters are investigated for different coolants under various first wall loads (P_w=2, 5, 7, 8, 9, and 10 MW m⁻²) in (D, T) (deuterium and tritium) driven and fueled with UO₂ hybrid reactors. Plasma chamber dimension, DR, with a line fusion neutron source is 300 cm. The fissile fuel zone is considered to be cooled with four different coolants with various volume fractions, the volumetric ratio of coolant-to-fuel [(Vm/V_f) = 1:2, 1:1, and 2:1], gas (He, CO₂), flibe (Li₂BeF₄), natural lithium (Li), and eutectic lithium (Li₁₇Pb₈₃). Calculation in the fuel rods and the behavior of the fissile fuel have been observed during 4 years for discrete time intervals of Δt=15 days and by a plant factor (PF) of 75%. As a result of the calculation, cumulative fissile fuel enrichment (CFFE) value indicating rejuvenation performance has increased by increasing P_w for all coolants and . Although CFFE and neutronic performance parameter values increase to the higher values by increasing P_w, the maximum temperature in the centerline of the fuel roads has exceeded the melting point (T_m>2830°C) of the fuel material during the operation periods. However, the best CFFE (11.154%) is obtained in gas coolant blanket for =1:2 (29.462% coolant, 58.924% fuel, 11.614% clad), under 10 MW m⁻² first wall load, followed by flibe with CFFE=11.081% for =2:1 (62.557% coolant, 31.278% fuel, 6.165% clad), under 7 MW m⁻², and flibe with CFFE=9.995% for =1:1 (45.515% coolant, 45.515% fuel, 8.971% clad), under 7 MW m⁻² during operation period without reaching the melting point of the fuel material. While maximum CFFE value has been obtained in fuel rod row#10 in gas, natural lithium, and eutectic lithium coolant blankets, it has been obtained in fuel rod row#1 in flibe coolant blanket for all and P_w. At the same condition, the best neutronic performance parameter values, tritium breeding ratio (TBR)= 1.4454, energy multiplication factor (M)= 9.2018, and neutron leakage (L)= 0.0872, have been obtained in eutectic lithium coolant blankets for the =1:2, followed by gas, natural lithium, and flibe coolant blankets. The isotopic percentage of ²⁴⁰Pu is higher than 5% in all blankets for P_w 7 MW m⁻², so that plutonium component in all blankets can be never reach a nuclear weapon grade quality during the operation period.     

Biomarkers for Alzheimer’s Disease in the Current State: A Narrative Review

Alzheimer’s disease (AD) has become a problem, owing to its high prevalence in an aging society with no treatment available after onset. However, early diagnosis is essential for preventive intervention to delay disease onset due to its slow progression. The current AD diagnostic methods are typically invasive and expensive, limiting their potential for widespread use. Thus, the development of biomarkers in available biofluids, such as blood, urine, and saliva, which enables low or non-invasive, reasonable, and objective evaluation of AD status, is an urgent task. Here, we reviewed studies that examined biomarker candidates for the early detection of AD. Some of the candidates showed potential biomarkers, but further validation studies are needed. We also reviewed studies for non-invasive biomarkers of AD. Given the complexity of the AD continuum, multiple biomarkers with machine-learning-classification methods have been recently used to enhance diagnostic accuracy and characterize individual AD phenotypes. Artificial intelligence and new body fluid-based biomarkers, in combination with other risk factors, will provide a novel solution that may revolutionize the early diagnosis of AD.