Organochlorine Formation in Tertiary Amine Catalyzed Pulp Bleaching

An oxygen delignified eucalyptus kraft pulp was bleached by applying a catalytic amount of a tertiary amine, 1,4-diazabicyclo[2,2,2]octane, and hypochlorous acid at varying pH, temperature, and time. The bleaching filtrate was analyzed for chloroform and AOX and the pulp for residual lignin, hexenuronic acid, and OX. In comparison with chlorine dioxide bleaching, the novel catalytic bleaching (pH < 6) generated only traces of chloroform and low contents of AOX and OX. Separate catalytic oxidations of authentic hexenuronic acid showed that it was a major precursor of chloroform. The results demonstrate a practical way to reduce organochlorine formation in pulp bleaching and provide new understanding on the reaction pathways that yield chloroform.     

Tuning of Cloud Point by the Nature of Surfactant Headgroup: Influence of Counterion and Additives

Work was performed to distinguish the role of sulfonate (–SO₃ ^?) and sulfate (–OSO₃ ^?) with respect to the micellization and clouding phenomenon in ionic surfactant solutions. The clouding phenomenon is a recent addition to the conventional one observed with nonionic surfactants. Three ionic surfactants [sodium dodecylsulfate (SDS), sodium dodecylbenzenesulfonate (SDBS), and sodium dodecylsulfonate (SDSo)] are chosen and the effects of added tetra-n-pentylammonium bromide (TPeAB) and benzyl tributylammonium bromide (BTAC) have been studied on micellization and clouding behaviors in aqueous solution. Based on critical micelle concentration (CMC) and cloud point (CP) measurements, the following order has been observed: SDBS < SDS < SDSo. Though both SDBS and SDSo contain sulfonate groups, they are found at the two ends of the ordering. Therefore, the role of the phenyl ring is also having importance in clouding phenomena. For a typical surfactant, TPeAB was found to be more effective than BTAC. Based on the CP studies, two compositions of SDSo + TPeAB/BTAC were chosen and the effects of different additives (carbohydrate, amino acid, and l-ascorbic acid) on the CP were investigated. Additive may either decrease or increase CP, depending on the structure of the counterion or additive. The present work shows a few novelties: (1) headgroup/counterion dependence of CP and (2) hydrophobicity of counterion/surfactant has an important bearing on the phenomenon. The data can be utilised in improving cloud point extraction methodologies (CPEMs).     

Corrosion of Alloy Haynes 230 in High Temperature Supercritical Carbon Dioxide with Oxygen Impurity Additions

The corrosion of Ni-based alloy Haynes 230 in supercritical carbon dioxide at temperatures of 650 and 750 °C at a pressure of 20 MPa was investigated. In high-purity research grade CO₂, the corrosion performance of the alloy was excellent with a thin, uniform, protective chromium-rich oxide layer forming on the surface. Introduction of 10 and 100 ppm O₂ impurity in the CO₂ environment noticeably enhanced oxidation with evidence of oxide spallation and nodule formation. In these oxygen impurity added tests, increased oxidation led to subsurface voids due to the more rapid outward diffusion of chromium as well as intergranular alumina and chromia. The oxygen concentration at the inlet and the outlet of the autoclave was measured and used to support the results of characterization of the surface oxide to develop a more holistic understanding of the role of oxygen impurity on the corrosion process. In all cases, there some carbon was observed, which manifested as slightly higher concentration of chromium–carbide phase at the grain boundaries compared to the unexposed alloy.     

Non-uniform Euler-Bernoulli beams under a single moving oscillator: An approximate analytical solution in time domain

Dynamic responses of simply supported non-uniform beams traversed by a moving oscillator are analysed in this paper. An approximate analytical method based on Rayleigh-Ritz (R-R) formulation is developed. The fundamental approximate mode obtained from R-R method is used in the present formulation to determine the responses of the beam and the oscillator. Effects of surface irregularities on the displacement and acceleration responses of the beam and the vehicle are also analysed. The results are compared with those obtained using Finite element method (FEM). A numerical example is provided to illustrate the validity of the present method which shows that the proposed method is simple, computationally more efficient compared to FEM and gives fairly good results. Though the single-mode approach used in the present paper is a classical one and numerous studies on the responses of uniform beams under moving loads have been reported in the past, its application to non-uniform beams (for which there does not exist any closed form expression for mode shapes) under a moving load, especially a moving oscillator, is presented for the first time.     

Pruning deep convolutional neural networks for efficient edge computing in condition assessment of infrastructures

Health monitoring of civil infrastructures is a key application of Internet of things (IoT), while edge computing is an important component of IoT. In this context, swarms of autonomous inspection robots, which can replace current manual inspections, are examples of edge devices. Incorporation of pretrained deep learning algorithms into these robots for autonomous damage detection is a challenging problem since these devices are typically limited in computing and memory resources. This study introduces a solution based on network pruning using Taylor expansion to utilize pretrained deep convolutional neural networks for efficient edge computing and incorporation into inspection robots. Results from comprehensive experiments on two pretrained networks (i.e., VGG16 and ResNet18) and two types of prevalent surface defects (i.e., crack and corrosion) are presented and discussed in detail with respect to performance, memory demands, and the inference time for damage detection. It is shown that the proposed approach significantly enhances resource efficiency without decreasing damage detection performance.     

Concrete crack detection using context‐aware deep semantic segmentation network

Computer‐vision and deep‐learning techniques are being increasingly applied to inspect, monitor, and assess infrastructure conditions including detection of cracks. Traditional vision‐based methods to detect cracks lack accuracy and generalization to work on complicated infrastructural conditions. This paper presents a novel context‐aware deep convolutional semantic segmentation network to effectively detect cracks in structural infrastructure under various conditions. The proposed method applies a pixel‐wise deep semantic segmentation network to segment the cracks on images with arbitrary sizes without retraining the prediction network. Meanwhile, a context‐aware fusion algorithm that leverages local cross‐state and cross‐space constraints is proposed to fuse the predictions of image patches. This method is evaluated on three datasets: CrackForest Dataset (CFD) and Tomorrows Road Infrastructure Monitoring, Management Dataset (TRIMMD) and a Customized Field Test Dataset (CFTD) and achieves Boundary F1 (BF) score of 0.8234, 0.8252, and 0.7937 under 2‐pixel error tolerance margin in CFD, TRIMMD, and CFTD, respectively. The proposed method advances the state‐of‐the‐art performance of BF score by approximately 2.71% in CFD, 1.47% in TRIMMD, and 4.14% in CFTD. Moreover, the averaged processing time of the proposed system is 0.7 s on a typical desktop with Intel^® Quad‐Core? i7‐7700 CPU@3.6 GHz Processor, 16GB RAM and NVIDIA GeForce GTX 1060 6GB GPU for an image of size 256 × 256 pixels.     

Water generation from atmospheric air by using different composite desiccant materials

In this communication, new composite desiccant materials having 37% concentration of CaCl₂ have been compared for water production from atmospheric air. The vermiculite–saw wood, jute and burnt-clay have been used as host materials and CaCl₂ as a hygroscopic salt. All the desiccant materials have been tested with the solar glass desiccant box type system (SGDBS) with a collector area of 0.36?m². Design parameters for water production are: height of the glass from the desiccant bed to be 0.22?m, an inclination angle of 30°, the effective thickness of the glass as 3?mm and the number of glazing is single. It has been found that on the experimental day, the maximum amount of fresh water generated by the vermiculite–saw wood/CaCl₂ is 130?ml/kg/day.     

Experimental analysis of the effects of cerium oxide nanoparticles on a single-cylinder diesel engine using biofuel blended with diesel as fuel

Energy demand is the hot topic of all developing and developed countries. Energy demand has been increasing day by day at a high rate. So, it is necessary to find an alternative solution that is eco-friendly. Biodiesel can be the alternative solution for this problem. The main purpose of this paper is to test the engine performance and emission parameters of a diesel engine using pure cinnamon oil blended with diesel and using cerium oxide as a catalyst. The parameters measured are brake power, brake thermal efficiency, specific fuel conception, CO₂, CO, NO_x and HC.