Development and testing of analytical models for the pebble bed type HTRs

The pebble bed type gas cooled high temperature reactor (HTR) appears to be a good candidate for the next generation nuclear reactor technology. These reactors have unique characteristics in terms of the randomness in geometry, and require special techniques to analyze their systems. This study includes activities concerning the testing of computational tools and the qualification of models. Indeed, it is essential that the validated analytical tools be available to the research community. From this viewpoint codes like MCNP, ORIGEN and RELAP5, which have been used in nuclear industry for many years, are selected to identify and develop new capabilities needed to support HTR analysis. The geometrical model of the full reactor is obtained by using lattice and universe facilities provided by MCNP. The coupled MCNP-ORIGEN code is used to estimate the burnup and the refuelling scheme. Results obtained from Monte Carlo analysis are interfaced with RELAP5 to analyze the thermal hydraulics and safety characteristics of the reactor. New models and methodologies are developed for several past and present experimental and prototypical facilities that were based on HTR pebble bed concepts. The calculated results are compared with available experimental data and theoretical evaluations showing very good agreement. The ultimate goal of the validation of the computer codes for pebble bed HTR applications is to acquire and reinforce the capability of these general purpose computer codes for performing HTR core design and optimization studies.     

Signal decomposition of transmembrane voltage-sensitive dye fluorescence using a multiresolution wavelet analysis

Fluorescence imaging of transmembrane voltage-sensitive dyes is used to study electrical activation in cardiac tissue. However, the fluorescence signals, typically, have low SNRs and may be contaminated with motion artifact. In this report, we introduce a new processing approach for fluoresced transmembrane potentials (fTmps) that is based upon a discrete wavelet transform. We show how fTmp signals can be decomposed and reconstructed to form three subsignals that contain signal noise (noise signal), the early depolarization phase of the action potential (rTmp signal), and motion artifact (rMA signal). A coiflet4 wavelet is used for fTmp decomposition and reconstruction of these subsignals. Results using fTmp signals that are contaminated with motion artifact indicate that the approach is a useful processing step to remove baseline drift, reduce noise, and reveal wavefronts. It streamlines the preprocessing of fTmps for the subsequent measurement of activation times and conduction velocities. It is a promising approach for studying wavefronts without aggressive mechanical tissue constraint or electromechanical uncoupling agents and is, useful for single-camera systems that do not provide for ratiometric imaging.     

Performances of novel Pd/Sn and Pd/Sn/Au ohmic metallizations to n-GaAs

Performance of novel Pd/Sn and Pd/Sn/Au Ohmic metallizations to n-GaAs have been investigated. Metallizations were deposited using a resistance heating evaporator and annealings were performed utilizing a conventional graphite strip annealer (cGSA). Metallization samples were characterized using scanning tunneling microscopy (STM), secondary ion mass spectrometry (SIMS) and current–voltage (I–V) measurements. Contact resistivities, ρ_c, of the metallizations were measured utilizing conventional transmission line model (cTLM) method. Novel Pd/Sn and Pd/Sn/Au Ohmic contacts exhibit better thermal stability compared to non-alloyed Pd/Ge metallization. In order to investigate the effectiveness of novel Pd/Sn and Pd/Sn/Au Ohmic metallizations in device applications, gallium arsenide metal-semiconductor field-effect transistors (GaAs MESFETs) have been fabricated. MESFETs fabricated with Pd/Sn/Au Ohmic contacts show a extrinsic transconductance, g_me, of more than 133 mS/mm for a gate length, L_G, of 2 μm.     

Brain Tumor Auto-Segmentation on Multimodal Imaging Modalities Using Deep Neural Network

Due to the difficulties of brain tumor segmentation, this paper proposes a strategy for extracting brain tumors from three-dimensional Magnetic Resonance Image (MRI) and Computed Tomography (CT) scans utilizing 3D U-Net Design and ResNet50, taken after by conventional classification strategies. In this inquire, the ResNet50 picked up accuracy with 98.96%, and the 3D U-Net scored 97.99% among the different methods of deep learning. It is to be mentioned that traditional Convolutional Neural Network (CNN) gives 97.90% accuracy on top of the 3D MRI. In expansion, the image fusion approach combines the multimodal images and makes a fused image to extricate more highlights from the medical images. Other than that, we have identified the loss function by utilizing several dice measurements approach and received Dice Result on top of a specific test case. The average mean score of dice coefficient and soft dice loss for three test cases was 0.0980. At the same time, for two test cases, the sensitivity and specification were recorded to be 0.0211 and 0.5867 using patch level predictions. On the other hand, a software integration pipeline was integrated to deploy the concentrated model into the webserver for accessing it from the software system using the Representational state transfer (REST) API. Eventually, the suggested models were validated through the Area Under the Curve–Receiver Characteristic Operator (AUC–ROC) curve and Confusion Matrix and compared with the existing research articles to understand the underlying problem. Through Comparative Analysis, we have extracted meaningful insights regarding brain tumour segmentation and figured out potential gaps. Nevertheless, the proposed model can be adjustable in daily life and the healthcare domain to identify the infected regions and cancer of the brain through various imaging modalities.     

Heat transfer analysis with temperature-dependent viscosity for the peristaltic flow of nano fluid with shape factor over heated tube

The present article address the nanofluid flow with the interaction of shape factor and heat transfer in a vertical tube with temperature-dependent viscosity. Flow study has been done in a flexible tube with low Reynolds number (Re<<0 i.e and long wavelength (δ<<0 i.e assumption. Mathematica software is employed to evaluate the exact solutions of velocity profile, temperature profile, axial velocity profile, pressure gradient and stream function. The influence of heat source/sink parameter (β), Grashof number (G_r) and the viscosity parameter (α) and nanoparticle volume fraction (?) on velocity, temperature, pressure gradient, pressure rise and wall shear stress distributions is presented graphically. Three types of shape factor i.e cylinder platelets and bricks are discussed. Streamline plots are also computed to illustrate bolus dynamics and trapping phenomena which characterize peristaltic propulsion. It is seen that with an increment in Grash of number, G_r, nanofluid velocity is significantly increases i.e. flow acceleration is induced across the tube diameter. Once again the copper-methanol nanofluid in shape of platelets achieves the best acceleration.     

Fire Safety in the Readymade Garment Sector in Bangladesh: Structural Inadequacy Versus Management Deficiency

The readymade garment (RMG) industry plays a vital role in the socio-economic development of Bangladesh, yet the sector suffers from poor fire safety records. Given the lack of fire risk assessment in the industry, this paper develops a Fire Risk Index (FRI) for individual RMG factories and surveys 60 such factories to develop an understanding of the fire safety conditions in the sector. The paper differentiates the risk factors into structural (hard) and management related (soft) parameters and develops FRIs for the structural factors. The FRI for structural parameters is then compared with the FRI for management factors, published earlier. While an overall mean FRI of 2.12 on a 4 point scale indicates that fire safety condition is quite poor, the FRI for soft parameters (1.80) are even lower than the FRI for hard parameters (2.58), indicating the critical importance of the soft parameters in fire safety assessment of the RMG factories. Within the hard parameters, there appears to be more reliance on firefighting and means for escape than on precautionary measures to contain the fire, which could explain the higher frequency of fire occurrences in the industry. FRI for both hard and soft parameters appear to follow a U shaped relationship with factory size, possibly indicating a Kuznet’s effect in fire safety in the garment sector. The poor FRI for hard factors indicates large deviations from safety requirements set in this work and asks for a stricter monitoring and enforcement regime. Improving the performance in the soft parameters, however, would require changes in the safety culture and practices.     

Envisioning the future of cooperation on common rivers in South Asia: a cooperative security approach by Bangladesh and India to the Tipaimukh Dam

Using the historical trends in Bangladesh–India water disputes as a background, this article argues that if Bangladesh and India approach the proposed Tipaimukh Dam on the trans-boundary Barak River from a cooperative security angle, they will be successful in making a significant deviation from the sovereignty-based approach that has been a prevailing feature of negotiations on water issues in South Asia. By emphasizing the benefit from a ‘share the resources’ model, as opposed to a ‘divide the resources’ model, such an approach will be mutually beneficial and may have significant ‘spill-over’ repercussions for multilateral cooperation on rivers in South Asia.     

“Suction Caps”: Designing Anisotropic Core/Shell Microcapsules with Controlled Membrane Mechanics and Substrate Affinity

Core/shell microcapsules with low‐permeability membranes and controlled morphology are crucial for the delivery and controlled release of fragrance molecules, pharmaceuticals, inks, or vitamins. Design criteria for next generation microcapsules must include chemical and mechanical stability, and also provide enhanced substrate interactions to improve deposition onto relevant complex surfaces. Here, a coupled approach is presented to synthesize core/shell delivery systems by interfacial polymerization to enhance both the microcapsule–substrate interactions and the mechanical properties of the capsules to induce a burst‐type release. By combining membrane synthesis, nonlinear mechanics, interfacial rheology, analysis of mass transfer, and capsule morphology generated during interfacial polymerization, large permanent deformations into the capsule geometry are programmed, resulting in chemically stable, yet mechanically rupturing microcapsules with anisotropic geometry. To promote interactions and capsule adhesion onto complex substrates, the capsule contact area is controlled to form prominent “suction cup” shaped rims. These capsules have favorable, far‐reaching electrostatic interactions with oppositely charged substrates such as glass, hair, skin, or fabric. By modulating membrane mechanical properties and morphology during synthesis, formulation‐independent physical criteria are used to improve the overall performance of a functional delivery system while expanding knowledge of the key parameters influencing the interfacial polymerization process and membrane formation.