An efficient coalescent epoch model for Bayesian phylogenetic inference

We present a two headed approach called Bayesian Integrated Coalescent Epoch PlotS (BICEPS) for efficient inference of coalescent epoch models. Firstly, we integrate out population size parameters and secondly we introduce a set of more powerful Markov chain Monte Carlo (MCMC) proposals for flexing and stretching trees. Even though population sizes are integrated out and not explicitly sampled through MCMC, we are still able to generate samples from the population size posteriors, which allows demographic reconstruction through time. Altogether, BICEPS can be considered a more muscular version of the popular Bayesian skyline model. We demonstrate its power and correctness by a well calibrated simulation study. Furthermore, we demonstrate with an application to COVID-19 genomic data that some analyses that have trouble converging with the traditional Bayesian skyline prior and standard MCMC proposals can do well with the BICEPS approach. BICEPS is available as open source package for BEAST 2 under GPL license and has a user friendly graphical user interface.

Using Calibrated Simulation to Quantify The energy Savings From Residential Passive Solar Design in Canada

Energy savings from passive solar design applied to a typical Canadian house were quantified using calibrated whole building energy simulation. A detailed energy simulation model was created for a research house which represents a typical Canadian tract house with basic passive solar measures. The model was calibrated to measured furnace gas consumption data. Eight design scenarios were evaluated for eight climate locations. Design parameters included increased thermal mass, increased south window area, and high performance windows. In addition, an advanced house scenario was evaluated which featured optimized geometry, a further increase in south window area, high thermal mass, advanced glazing, and no north facing windows. For the typical house predicted solar heating fractions ranged from 20% to 34% with basic passive solar measures, and 35% to 52% for more aggressive passive solar measures. For the advanced house predicted solar fractions ranged from 40% to 69%.

Using Calibrated Simulation to Quantify The energy Savings From Residential Passive Solar Design in Canada

Energy savings from passive solar design applied to a typical Canadian house were quantified using calibrated whole building energy simulation. A detailed energy simulation model was created for a research house which represents a typical Canadian tract house with basic passive solar measures. The model was calibrated to measured furnace gas consumption data. Eight design scenarios were evaluated for eight climate locations. Design parameters included increased thermal mass, increased south window area, and high performance windows. In addition, an advanced house scenario was evaluated which featured optimized geometry, a further increase in south window area, high thermal mass, advanced glazing, and no north facing windows. For the typical house predicted solar heating fractions ranged from 20% to 34% with basic passive solar measures, and 35% to 52% for more aggressive passive solar measures. For the advanced house predicted solar fractions ranged from 40% to 69%.

Fixed‐ k inference for volatility

We present a new theory for the conduct of nonparametric inference about the latent spot volatility of a semimartingale asset price process. In contrast to existing theories based on the asymptotic notion of an increasing number of observations in local estimation blocks, our theory treats the estimation block size k as fixed. While the resulting spot volatility estimator is no longer consistent, the new theory permits the construction of asymptotically valid and easy‐to‐calculate pointwise confidence intervals for the volatility at any given point in time. Extending the theory to a high‐dimensional inference setting with a growing number of estimation blocks further permits the construction of uniform confidence bands for the volatility path. An empirically realistically calibrated simulation study underscores the practical reliability of the new inference procedures. An empirical application based on intraday data for the S&P 500 equity index reveals highly significant abrupt changes, or jumps, in the market volatility at FOMC news announcement times, validating recent uses of various high‐frequency‐based identification schemes in asset pricing finance and monetary economics.

Investigation on the Performance Characteristics of 2-Stroke Heavy Fuel Light Aeroengine (2SHFLA) with Different Fuel Injection Systems: Modeling and Comparative Simulation

Extensive application of small and medium-sized unmanned aerial vehicles (UAVs) have already made the development of corresponding power system a research hotspot nowadays. Two-stroke heavy fuel light aeroengine (2SHFLA) is selected as the research focus in this paper. The working principle of 2SHFLA with different fuel injection systems is elaborated systematically. By dividing the initial prototype engine into several subsystems, the simulation platform is set up with its key model parameters accurately calibrated against the test data. Simulation platforms of the other two types of engines are subsequently constructed based on the pre-calibrated simulation platform of the initial prototype engine. Afterwards, comparative simulation is performed and the corresponding simulation results include: (1) comparison of performance characteristics of the initial prototype engine fueled with regular gasoline/heavy fuel; (2) comprehensive comparison of the performance characteristics of all the three types of engine.

Experimental Investigation and Simulation of a Boeing 747 Auxiliary Power Unit

Auxiliary power units (APUs) are a major driver of maintenance on civil aircraft. However, experimental data and performance simulations are rarely seen in public domain literature. While there is recourse to aircraft engine experience, this does not address the loading and the failure modes of an APU. This work aims to add to the literature, by experimentally investigating a Boeing 747 APU, collecting data under various power settings and ambient conditions, and using these data to calibrate a simple simulation model. This simulation model will subsequently be used to explore failure modes in the APU and hence what sensors may be needed for health monitoring purposes in future work. In this paper, a Boeing 747 APU rig development process and the testing strategy are presented. The rig is validated through a process that includes uncertainty analysis, repeatability tests, consistency tests, and comparison of the collected data with the calibrated simulation model. The results from the rig's validation indicate that the data collected from the APU is independent of its running time or the order of loading cycles imposed on it, i.e., the results are path independent. Changes in pneumatic and electrical power result in small changes in the rotational speed despite the fact that the rotational speed should remain constant. The rotational speed shows a slightly increasing trend when the extracted power rises, and this affects the APU thermodynamic characteristics. This work has resulted in a calibrated simulation model that will be further used in examining fault mode scenarios, as injecting these directly into the rig is seen as high risk.

Long-term visual quality evaluations correlate with climate-based daylighting metrics in tropical offices – A field study

In this paper, we present a post-occupancy study of 326 participants in 10 daylit office buildings in Singapore and correlate the results with climate-based daylighting metrics and electric lighting simulations using calibrated simulation models of the 10 buildings. For the first time, this study tests the climate-based daylighting metrics which are used in building design against their impact on occupant perception within buildings. We find significant correlations between climate-based daylighting metrics and reported occupant satisfaction with access to daylight, view interest, perception of ‘too low’ lighting levels and visual comfort. Overall, climate-based daylighting metrics which account for lower illuminance thresholds such as continuous daylight autonomy and useful daylight illuminance combined (100–3000 lx) correlate more strongly with subjective results than do electric lighting sufficiency metrics such as daylight autonomy at 300 and 500 lx thresholds. Simple descriptive statistical representations of annual daylight distributions, mean and median annual daylight illuminance values, outperform climate-based daylighting metrics in correlation strength and p-value. Based upon these results, new metrics are proposed for occupant satisfaction with daylight access and views. In addition, increased daylight levels are shown to decrease reporting of lighting levels being ‘often too low’ even when adequate electric lighting is provided, and contrast is likely to be beneficial to space perception at non-glaring thresholds.