Unsteady Transport Phenomena of Hybrid Al2O3-Cu/H2O Nanofluid Past a Shrinking Slender Cylinder

Theoretical investigations of unsteady boundary layer flow gain interest due to its relatability to practical settings. Thus, this study proposes a unique mathematical model of the unsteady flow and heat transfer in hybrid nanofluid past a permeable shrinking slender cylinder. The suitable form of similarity transformations is adapted to simplify the complex partial differential equations into a solvable form of ordinary differential equations. A built-in bvp4c function in MATLAB software is exercised to elucidate the numerical analysis for certain concerning parameters, including the unsteadiness and curvature parameters. The bvp4c procedure is excellent in providing more than one solution once sufficient predictions are visible. The present analysis further observed dual solutions that exist in the system of equations. Notable findings showed that by increasing the nanoparticles volume fraction, the skin friction coefficient increases in accordance with the heat transfer rate. In contrast, the decline of the unsteadiness parameter demonstrates a downward trend toward the heat transfer performance.

Ammonia converter Simulation and Optimization Based on an Innovative Correlation for (KP) Prediction

In this paper, the simulation and optimization of an industrial ammonia synthesis reactor is illustrated. The converter under study is of a vertical design, equipped with three radial-flow catalyst beds with inter-stage cooling and two quenching points. For building the model, a modified kinetic equation of ammonia synthesis reaction, based on Temkin- Pyzhev equation and an innovative correlation for (KP) prediction, was developed in suitable form for the implementation in Aspen HYSYS plug flow reactor using the spreadsheet embedded in the software with the introduction of some invented simulation techniques. A new parameter, which is a function of (T, P and α), was introduced into the reaction rate equation to account for the variation of KP with pressure. The simulation model is able to describe the converter behavior with acceptable accuracy. A case study was done, using Aspen HYSYS Optimizer, illustrated the optimum reactor temperature profile, after 12 years of operation, to achieve maximum production. The result predicts an increase of 8 tons ammonia per day accompanied with an increase of steam production of 12 tons per day.

Solar-Powered Improved Full Bridge Resonant Inverter for High-Frequency Industrial Applications

Electrical energy consumption is alarmingly rising, but the availability of conventional sources is limited. To meet the increasing demand; the implementation of non-conventional sources is the need of the hour. Solar energy is the most sustainable alternative for power generation among non-conventional sources families. Resonant inverters are used in low-power high-frequency induction heating appliances. Full-bridge resonant inverters are most commonly used to convert solar received power into the suitable form required for high-frequency application device by providing maximum power to the load at resonant frequency The aim of the paper is to analyze the working of the resonant inverter by taking the input supply from the solar panel and converting the obtained dc input to ac input through the resonant inverter. This obtained output is supplied for the high-frequency industrial application which mainly includes Induction frequency heating Applications. Induction heating is one of the techniques used in casting foundry for the treatment of metals. It involves the heat treatment of the metals namely annealing, hardening tempering method. goes here.

Characterization of magnetized CNT-based hybrid nanofluid subjected to convective phenomenon

Hybrid nanofluid gains attention of scientists due to its dynamic properties in various fields, and thus, hybrid nanofluids can be taken as an innovative form of nanofluids. Even though analysts acquire tremendous results in the field of hybrid nanofluids but yet no study has been carried out to predict magnetohydrodynamic effects in such fluid models. In this present analysis, influence of MHD has been investigated for the micro hybrid nanofluid over a stretched surface under convective conditions. Combine boundary layer equations for the flow have been altered into a suitable form via boundary layer approximations. Further, complete nonlinear system of equations has been numerically solved via BVP-4C method. Interesting results have been demonstrated for an exponentially stretched surface and expressed in the form of shear stress and rate of heat transfer. Results have also been visualized in the form of streamlines and isotherms. This study reveals after observing the numeric values of skin friction and Nusselt number that micropolar hybrid nanofluid models have greater heat transfer rate as compared to nanofluids.

Evaluation of Machine Learning Methodologies Using Simple Physics Based Conceptual Models For Flow in Porous Media

Machine learning (ML) techniques have drawn much attention in the engineering community due to recent advances in computational techniques and an enabling environment. However, often they are treated as black-box tools, which should be examined for their robustness and range of validity/applicability. This research presents an evaluation of their application to flow/transport in porous media, where exact solutions (obtained from physics-based models) are used to train ML algorithms to establish when and how these ML algorithms fail to predict the first order flow-physics. Exact solutions are used so as not to introduce artifacts from the numerical solutions. To test, validate, and predict the physics of flow in porous media using ML algorithms, one needs a reliable set of data that may not be readily available and/or the data might not be in suitable form (i.e. incomplete/missing reporting, metadata, or other relevant peripheral information). To overcome this, we first generate structured datasets for flow in porous media using simple representative building blocks of flow physics such as Buckley-Leverett, convection-dispersion equations, and viscous fingering. Then, the outcomes from those equations are fed into ML algorithms to examine their robustness and predictive strength of the key features, such as breakthrough time, and saturation and component profiles. In this research, we show that a physics-informed ML algorithm can capture the physical behavior and effects of various physical parameters (even when shocks and sharp gradients are present). Further the ML approach can be utilized to solve inverse problems to estimate physical parameters.

From China to Japan and Back Again: An Energetic Example of Bidirectional Sino-Japanese Esoteric Buddhist Transmission

Sino-Japanese religious discourse, more often than not, is treated as a unidirectional phenomenon. Academic treatments of pre-modern East Asian religion usually portray Japan as the passive recipient of Chinese Buddhist traditions, while explorations of Buddhist modernization efforts focus on how Chinese Buddhists utilized Japanese adoptions of Western understandings of religion. This paper explores a case where Japan was simultaneously the receptor and agent by exploring the Chinese revival of Tang-dynasty Zhenyan. This revival—which I refer to as Neo-Zhenyan—was actualized by Chinese Buddhist who received empowerment (Skt. abhiṣeka) under Shingon priests in Japan in order to claim the authority to found “Zhenyan” centers in China, Hong Kong, Taiwan, Malaysia, and even the USA. Moreover, in addition to utilizing Japanese Buddhist sectarianism to root their lineage in the past, the first known architect of Neo-Zhenyan, Wuguang (1918–2000), used energeticism, the thermodynamic theory propagated by the German chemist Freidrich Wilhelm Ostwald (1853–1932; 1919 Nobel Prize for Chemistry) that was popular among early Japanese Buddhist modernists, such as Inoue Enryō (1858–1919), to portray his resurrected form of Zhenyan as the most suitable form of Buddhism for the future. Based upon the circular nature of esoteric transmission from China to Japan and back to the greater Sinosphere and the use of energeticism within Neo-Zhenyan doctrine, this paper reveals the sometimes cyclical nature of Sino-Japanese religious influence. Data were gathered by closely analyzing the writings of prominent Zhenyan leaders alongside onsite fieldwork conducted in Taiwan from 2011–2019.

Pengaruh Komposisi Ekstrak Mengkudu (Morinda citrifilia L.) Sebagai Antibakteri Pada Shampo Herbal Berbasis Methyl Ester Sulfonat (MES)

Shampoo is a preparation that contains surfactants in a suitable form and is useful for removing dirt and grease attached to the hair and scalp so as not to harm the hair and scalp. In this study the ingredients used were noni fruit extracts and surfactants using Methyl Ester Sulfonate (MES). The purpose of this study was to analyze the effect of time when making herbal shampoo, the effect of adding noni fruit extract to the quality of shampoo. To obtain the noni fruit extract maceration process is used by using distilled water. Noni ripe fruit is cut and then blended and then added 2 liters of aquadest, evaporated in a rotary evaporator. The processing of herbal shampoo is done by the influence of the volume of noni fruit extract and time by comparison: 5 ml: (1,2,3,4) minutes, 10 ml: (1,2,3,4) minutes, 15 ml: (1, 2,3,4) minutes, 20 ml (1,2,3,4) minutes. Tests carried out pH testing, foam stability test (%), foam height test (cm), viscosity (cps) and anti-bacterial test (colony, cm2). Based on the research results obtained high foam with 88 mm, foam stability 92.04%, Viscosity 2.31, antibacterial 31.7 colonies / cm2, and pH 4.2. The research results are expected to meet Indonesian National Standards.

PREPARATION OF AQUEOUS EXTRACT OF TINOSPORA CORDIFOLIA (WILD) MIERS EX. HOOK F. & THOMS.: AN AYURVEDA FORMULATION

Guduchi is an important Rasayan drug in Ayurveda. It is used different dosage forms to cure diseases. Guduchi is described in our classics to cure the various types of diseases i.e., Kamala, prameha, vatrakata, etc. it is used by the patient there in a suitable form. So, the requirement of the patient and good palatable, it is converted into a suitable form by using various types of methods. In Ayurveda, five major Kalpana which are called Pancvidha Kashaya Kalpana is described first in Charak Samhita. Another minor Kalpana like vati, churna, ghana, sandhan Kalpana is derived from panchvidha kashaya Kalpana. Guduchi Ghana is an important and unique preparation of Ayurveda. It is prepared from an aqueous extract of Guduchi. It is the secondary Kalpana which is derived from the primary Kalpana kwatha. In the present study preparation of Guduchi Ghana according to classical text “Siddha Yoga Sangraha” by Acharya Yadavji Trikamji. Guduchi is a soft drug so, water has been taken for the preparation of kwatha is four-time to Guduchi Dravya. When a confirmatory test of kwatha or reduced 1⁄4, it was filtered with the help of the cloth. After filtered, it was kept on the heat for preparation of Ghana. End of the whole procedure, the dark brown and sticky nature of Ghana was obtained. It is bitter and not specific smell. It has taken 5-6 hrs to complete the process. In the initial raw material has been taken 1.5 kg and the final product is obtained about 105gm. Keywords: Guduchi, Rasayan, Prameha, Kashaya Kalpana, Kwatha. etc.

Antidiarrhoeal Potential of various Solvent Extracts of Achyranthes aspera against three diverse diarrhoeal animal models

Diarrhoea is a condition characterized by a variation in the bowel movement. It is one of the major health issues in developing countries. Its severity is more in children’s. Diarrhoea causes severe dehydration and some time it may lead to death. Globally, over 5 million children’s are dying each year because of diarrhoea. In the present scenario, herbal medicines are used by the people in a wider range because of its safety as compared to synthetic drugs. So it is very crucial to identify and investigate available natural drugs for treating diarrhoea. Hence, the present study endeavor the evaluation of antidiarrhoeal activity of Achyranthus aspera. The anti-diarrhoeal activity was performed by using different animal models like castor oil-induced diarrhoea, prostaglandin-E2 induced enteropooling and gastrointestinal motility test. All the extracts of Achyranthus aspera showed considerable antidiarrhoeal activity in all the three animal models by reducing diarrhoeal episodes. The findings of the present investigation revealed the significant antidiarrhoeal property of Achyranthes aspera. Hence this plant can be used in the suitable form as an alternative to available synthetic antidiarrhoeal medicines which are not completely safe. Thus the adverse effects of synthetic drugs can be minimized by reducing its use.

The Effects of Image Augmentation on Efficiency of a Convolutional Neural Network of a Self-Driving Car

The objective of this paper was to study the effectiveness of image augmentation techniques in training a Convolutional Neural Network (CNN) of a self-driving car and identify the most suitable form of image augmentation technique, using the Udacity Car Simulator. Firstly, a dataset of augmented and non-augmented images from a training track, consisting of left-, right-, and front-facing views from the car cameras was created. Various image augmentation techniques were used: zoom, brightness, pan, flip, random (augments the image by arbitrarily choosing a technique from the previous four), and no augmentation. Secondly, training datasets consisting of the aforementioned images and a log of car turning angles, throttle, and brake were built. The final training datasets were then used with NVIDIA training method to train different CNN. The different trained networks generated steering commands from the front-facing camera of the simulation and test track had no effect on the generalization of the CNN. Lastly, different trained networks were used on the test track of Udacity Car Simulator to calculate the following variables: distance travelled, and number of crashes made by the car. After these values were acquired, an efficiency analysis was performed. The results suggested augmentation of training data is a crucial factor when it comes to the process of generalizing a model to perform tasks. Random augmentations performed the best, but a combination of flip and brightness augmentations performed equally efficiently.