Power generation with a supercritical CO2 closed regenerative Brayton cycle has been successfully demonstrated using a bench scale test facility. A set of a centrifugal compressor and a radial inflow turbine of finger top size is driven by a synchronous motor/generator controlled using a high-speed inverter. A 110 W power generating operation is achieved under the operational condition of rotational speed of 1.15kHz, CO2 flow rate of 1.1 kg/s, and respective thermodynamic states (7.5 MPa, 304.6 K) at compressor and (10.6 MPa, 533 K) at turbine inlet. Compressor work reduction owing to real gas effect is experimentally examined. Compressor to turbine work ratio in supercritical liquid like state is measured to be 28% relative to the case of ideal gas. Major loss of power output is identified as rotor windage. It is found the isentropic efficiency depends little on compressibility coefficient. Off design performance of gas turbine working in supercritical state is well predicted by a Meanline program. The CFD analysis on compressor internal flow indicates that the presence of backward flow around the tip region might create a locally depressurized region leading eventually to the onset of flow instability.

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Background COVID-19 currently poses a global public health threat. Although Tokyo, Japan, is no exception to this, it was initially affected by only a small-level epidemic. Nevertheless, medical collapse nearly happened since no predictive methods were available to assess infection counts. A standard susceptible-infectious-removed (SIR) epidemiological model has been widely used, but its applicability is limited often to the early phase of an epidemic in the case of a large collective population. A full numerical simulation of the entire period from beginning until end would be helpful for understanding COVID-19 trends in (separate) counts of inpatient and infectious cases and can also aid the preparation of hospital beds and development of quarantine strategies. Objective This study aimed to develop an epidemiological model that considers the isolation period to simulate a comprehensive trend of the initial epidemic in Tokyo that yields separate counts of inpatient and infectious cases. It was also intended to induce important corollaries of governing equations (ie, effective reproductive number) and equations for the final count. Methods Time-series data related to SARS-CoV-2 from February 28 to May 23, 2020, from Tokyo and antibody testing conducted by the Japanese government were adopted for this study. A novel epidemiological model based on a discrete delay differential equation (apparent time-lag model [ATLM]) was introduced. The model can predict trends in inpatient and infectious cases in the field. Various data such as daily new confirmed cases, cumulative infections, inpatients, and PCR (polymerase chain reaction) test positivity ratios were used to verify the model. This approach also derived an alternative formulation equivalent to the standard SIR model. Results In a typical parameter setting, the present ATLM provided 20% less infectious cases in the field compared to the standard SIR model prediction owing to isolation. The basic reproductive number was inferred as 2.30 under the condition that the time lag T from infection to detection and isolation is 14 days. Based on this, an adequate vaccine ratio to avoid an outbreak was evaluated for 57% of the population. We assessed the date (May 23) that the government declared a rescission of the state of emergency. Taking into consideration the number of infectious cases in the field, a date of 1 week later (May 30) would have been most effective. Furthermore, simulation results with a shorter time lag of T=7 and a larger transmission rate of α=1.43α0 suggest that infections at large should reduce by half and inpatient numbers should be similar to those of the first wave of COVID-19. Conclusions A novel mathematical model was proposed and examined using SARS-CoV-2 data for Tokyo. The simulation agreed with data from the beginning of the pandemic. Shortening the period from infection to hospitalization is effective against outbreaks without rigorous public health interventions and control.

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A Moisture Air Turbine (MAT) cycle is proposed for improving the characteristics of land based gas turbine by injecting atomized water at inlet to compressor. The power boosting mechanism of MAT is understood as composits of those of following existing systems: inlet air cooling system, inter-cooling and steam injection. Experiments using a 15MW class axial flow load compressor have been carried out to reveal that water evaporation in compressor could reduce compressor work in an efficient manner. Moreover, this technology has been demonstrated by means of 130MW class simple cycle gas turbine power plant to show that a small amount of water consumption is sufficient to increase power output. Very efficient evaporation could be achieved provided the size of water droplet is controlled properly. The amount of water consumption is much less than that of conventional inlet air cooling system with cooling tower for heat rejection. Incorporating water droplet evaporation profile into consideration, realistic cycle calculation model has been developed to predict power output with water injection. It has been shown that this technology is economically achievable. It should be stressed that contrary to well known evaporative cooler, MAT cycle could provide power output at a desired value within its capability regardless of ambient humidity condition.