Supercritical CO2 Heat Transfer Study Near Critical Point in a Heated Circular Pipe

Supercritical CO2 (sCO2) power cycle is an up-and-coming technology to produce electricity from various heat sources. Apart from power cycles, sCO2 can also be used as coolant in centralized cooling system and stand-alone cooling device. However, lack of accurate predication tools such as heat transfer coefficient correlations and insufficient knowledge behind fundamental heat transfer processes can hinder its practical realization in key energy and cooling systems. The overall objective of the study is to extend fundamental knowledge about heat transfer and fluid flow processes in conduits pertinent to sCO2 power cycle. The emphasis here is investigation of heat transfer effects of three testing parameters: heat flux, inlet mass flux and inlet temperature. Experimental setup for this heat transfer study is designed considering limitations due to high pressure rating requirements and thus follows unconventional approach to calculate heat transfer coefficient. Test section chosen is a horizontal stainless steel tubing of inner diameter of 9.4 mm and heated length of 1.23 m with uniform volumetric heat generation within tubing walls. The designed test apparatus and data reduction process are validated with high pressure air experiments. Nusselt numbers are calculated at top, bottom and side- wall locations to demonstrate effects of buoyancy. Enhancement of heat transfer at bot- tom wall surfaces and deterioration at top wall surfaces is observed as the main effect of buoyancy. It was observed that effects of buoyancy increase with heat flux and decrease with mass flux. Buoyancy effects are also decreased for fluid temperatures higher than pseudocritical temperature. Nusselt numbers calculated from experimental results are compared with Nusselt number from available correlations in literature. It is hinted that near critical region where property variations are significant, one correlation alone may not accurately predict heat transfer for different regimes of geometry, mass flux and heat flux

Learning orbital dynamics of binary black hole systems from gravitational wave measurements

We introduce a gravitational waveform inversion strategy that discovers mechanical models of binary black hole (BBH) systems. We show that only a single time series of (possibly noisy) waveform data is necessary to construct the equations of motion for a BBH system. Starting with a class of universal differential equations parameterized by feed-forward neural networks, our strategy involves the construction of a space of plausible mechanical models and a physics-informed constrained optimization within that space to minimize the waveform error. We apply our method to various BBH systems including extreme and comparable mass ratio systems in eccentric and non-eccentric orbits. We show the resulting differential equations apply to time durations longer than the training interval, and relativistic effects, such as perihelion precession, radiation reaction, and orbital plunge, are automatically accounted for. The methods outlined here provide a new, data-driven approach to studying the dynamics of binary black hole systems

A Concise Review Based on Analytical Method Development and Validation of Apremilast in Bulk and Marketed Dosage Form

Apremilast is used for treatment of psoriasis and psoriatic arthritis. It may also be beneficial for other inflammatory diseases relevant to the immune system. The drug functions as a selective enzyme phosphodiesterase 4 (PDE4) inhibitor and avoids the spontaneous development of TNF-alpha from human synovial rheumatoid cells. The present review assesses the different approaches for evaluation of apremilast in bulk material as well as different formulations. A concise review consists of compile and discuss about over 30 methods for analysing apremilast in the biological matrices, the samples of bulk and in different dosage formulations including HPLC, HPTLC, UPLC, LC-MS and UV-spectrophotometry. A concise review represents the compilation and discussion of about more than 30 analytical methods which includes HPLC, HPTLC, UPLC, LC-MS and UV-Spectrophotometry methods implemented for investigation of apremilast in biological matrices, bulk samples and in different dosage formulations. This detailed review will be of great help to the researcher who is working on apremilast. Keywords: Apremilast; Analytical Profile; HPLC; HPTLC; Bioanalytical; Stability indicatin

Cohort for Tuberculosis Research by the Indo-US Medical Partnership (CTRIUMPH): protocol for a multicentric prospective observational study

INTRODUCTION: Tuberculosis disease (TB) remains an important global health threat. An evidence-based response, tailored to local disease epidemiology in high-burden countries, is key to controlling the global TB epidemic. Reliable surrogate biomarkers that predict key active disease and latent TB infection outcomes are vital to advancing clinical research necessary to ‘End TB’. Well executed longitudinal studies strengthening local research capacity for addressing TB research priorities and advancing biomarker discovery are urgently needed. METHODS AND ANALYSIS: The Cohort for Tuberculosis Research by the Indo-US Medical Partnership (CTRIUMPH) study conducted in Byramjee Jeejeebhoy Government Medical College (BJGMC), Pune and National Institute for Research in Tuberculosis (NIRT), Chennai, India, will establish and maintain three prospective cohorts: (1) an Active TB Cohort comprising 800 adults with pulmonary TB, 200 adults with extrapulmonary TB and 200 children with TB; (2) a Household Contact Cohort of 3200 adults and children at risk of developing active disease; and (3) a Control Cohort consisting of 300 adults and 200 children with no known exposure to TB. Relevant clinical, sociodemographic and psychosocial data will be collected and a strategic specimen repository established at multiple time points over 24 months of follow-up to measure host and microbial factors associated with (1) TB treatment outcomes; (2) progression from infection to active TB disease; and (3) Mycobacterium tuberculosis transmission among Indian adults and children. We anticipate CTRIUMPH to serve as a research platform necessary to characterise some relevant aspects of the TB epidemic in India, generate evidence to inform local and global TB control strategies and support novel TB biomarker discovery. ETHICS AND DISSEMINATION: This study is approved by the Institutional Review Boards of NIRT, BJGMC and Johns Hopkins University, USA. Study results will be disseminated through peer-reviewed journals and research conferences. FUNDING: NIH/DBT Indo-US Vaccine Action Programme and the Indian Council of Medical Research

Two Types Of Analytical Methods For A Centrifugal Compressor Impeller For Supercritical Co2Power Cycles

The present study provides aerodynamic analysis of a centrifugal compressor impeller blade with supercritical carbon dioxide (sCO2) as the working fluid through a comparative study between three dimensional (3-D) computational fluid dynamics (CFD) and a one dimensional (1-D) mean-line analyses. The main centrifugal compressor in reference to a 100 MW sCO2closed loop Recuperated Recompression Brayton cycle is investigated. Considering modeling becomes increasingly complex with such an unconventional gas, a mean line analysis is selected as the starting point of this study. The boundary conditions are derived through the mean line analysis of the main centrifugal compressor with a pressure ratio and efficiency relative to the specified cycle. Through the use of loss correlations for centrifugal compressors within the literature search, and parameters found through the mean-line design, losses are calculated for the specified compressor impeller. Furthermore, the CFD study of the single centrifugal compressor impeller blade is performed with sCO2as the working fluid. Carbon dioxide is modeled as a compressible real gas with the application of a user defined equation of state (EOS). An EOS is established through a pressure and temperature dependent thermodynamic property table. Consequently, a better understanding is developed on best practices for modeling a real gas sCO2 centrifugal compressor within the commercial CFD solver, STAR-CCM+. Ultimately, the aerodynamic losses from the 1-D approach are evaluated by comparing with the ones derived from the CFD analysis

Optimization Of Supercritical Co2 Brayton Cycle For Simple Cycle Gas Turbines Exhaust Heat Recovery Using Genetic Algorithm

For the application of waste heat recovery (WHR), supercritical CO2. (S-CO2) Brayton power cycles offer significant suitable advantages such as compactness, low capital cost and applicable to a broad range of heat source temperatures. The current study is focused on thermodynamic modelling and optimization of Recuperated (RC) and Recuperated Recompression (RRC) S-CO2 Brayton cycles for exhaust heat recovery from a next generation heavy duty simple cycle gas turbine using a genetic algorithm. The Genetic Algorithm (GA) is mainly based on bio-inspired operators such as crossover, mutation and selection. This non-gradient based algorithm yields a simultaneous optimization of key S-CO2 Brayton cycle decision variables such as turbine inlet temperature, pinch point temperature difference, compressor pressure ratio. It also outputs optimized mass flow rate of CO2 for the fixed mass flow rate and temperature of the exhaust gas. The main goal of the optimization is to maximize power out of the exhaust stream which makes it single objective optimization. The optimization is based on thermodynamic analysis with suitable practical assumptions which can be varied according to the need of user. Further the optimal cycle design points are presented for both RC and RRC configurations and comparison of net power output is established for waste heat recovery

Optimization Of Supercritical Co2 Brayton Cycle For Simple Cycle Gas Turbines Exhaust Heat Recovery Using Genetic Algorithm

For the application of waste heat recovery (WHR), supercritical CO2 (S-CO2) Brayton power cycles offer significant suitable advantages such as compactness, low capital cost, and applicability to a broad range of heat source temperatures. The current study is focused on thermodynamic modeling and optimization of recuperated (RC) and recuperated recompression (RRC) configurations of S-CO2 Brayton cycles for exhaust heat recovery from a next generation heavy duty simple cycle gas turbine using genetic algorithm (GA). This nongradient based algorithm yields a simultaneous optimization of key S-CO2 Brayton cycle decision variables such as turbine inlet temperature, pinch point temperature difference, compressor pressure ratio, and mass flow rate of CO2. The main goal of the optimization is to maximize power out of the exhaust stream which makes it single objective optimization. The optimization is based on thermodynamic analysis with suitable practical assumptions which can be varied according to the need of user. The optimal cycle design points are presented for both RC and RRC configurations and comparison of net power output is established for WHR. For the chosen exhaust gas mass flow rate, RRC cycle yields more power output than RC cycle. The main conclusion drawn from the current study is that the choice of best cycle for WHR actually depends heavily on mass flow rate of the exhaust gas. Further, the economic analysis of the more power producing RRC cycle is performed and cost comparison between the optimized RRC cycle and steam Rankine bottoming cycle is presented

Optimization of Supercritical CO2 Brayton Cycle for Simple Cycle Gas Turbines Exhaust Heat Recovery Using Genetic Algorithm

For the application of waste heat recovery (WHR), supercritical CO2 (S-CO2) Brayton power cycles offer significant suitable advantages such as compactness, low capital cost, and applicability to a broad range of heat source temperatures. The current study is focused on thermodynamic modeling and optimization of recuperated (RC) and recuperated recompression (RRC) configurations of S-CO2 Brayton cycles for exhaust heat recovery from a next generation heavy duty simple cycle gas turbine using genetic algorithm (GA). This nongradient based algorithm yields a simultaneous optimization of key S-CO2 Brayton cycle decision variables such as turbine inlet temperature, pinch point temperature difference, compressor pressure ratio, and mass flow rate of CO2. The main goal of the optimization is to maximize power out of the exhaust stream which makes it single objective optimization. The optimization is based on thermodynamic analysis with suitable practical assumptions which can be varied according to the need of user. The optimal cycle design points are presented for both RC and RRC configurations and comparison of net power output is established for WHR. For the chosen exhaust gas mass flow rate, RRC cycle yields more power output than RC cycle. The main conclusion drawn from the current study is that the choice of best cycle for WHR actually depends heavily on mass flow rate of the exhaust gas. Further, the economic analysis of the more power producing RRC cycle is performed and cost comparison between the optimized RRC cycle and steam Rankine bottoming cycle is presented