Large -eddy simulation of a three-dimensional compressible tornado vortex

Large-Eddy simulation (LES) has become a very useful tool for investigating tornadoes, one of the more spectacular and destructive phenomena of nature. A new three-dimensional, unsteady, compressible model is generated to determine how significant the differences between compressible and incompressible LES simulations may be in some extremely violent tornadoes. In particular, this study seeks to determine how high the Mach number within the tornado may become before significant changes occur due to compressibility, and what the major effects of these changes may be expected to be.;After developing and verifying the compressible LES model, three different patterns of tornadic corner flows cataloged by local swirl ratio are simulated under quasisteady conditions for different Mach numbers. Simulation comparisons have demonstrated that the compressibility effects are different for different corner flow structures. At peak average Mach numbers less than approximately 0.5, the compressibility effects are not very significant and may be accounted for to leading order by an appropriate isentropic transformation applied to the incompressible results. As the maximum Mach number is increased to more than 1.0, the compressibility effects for low-swirl-ratio corner flows are dramatic, with significant increase in peak vertical velocity and the height of the vortex breakdown above the surface. The effects are much weaker for medium swirl conditions, and expected to be still weaker for high swirl corner flow where the effects are essentially limited to influencing the secondary vortices. In general, compressibility effects would not change the basic dynamics of tornadic corner flows even if Mach numbers greater than one are achieved.;This study also shows that during the sharp temporal overshoot in near-surface intensity that can sometimes occur during a tornado\u27s evolution, the maximum pressure drop will tend to be restricted by supersonic velocities, and thus limit the intensification of the overshoot. There are no apparent physical barriers to transonic speeds occurring within real tornadoes on rare occasions, however it is believed that most tornado dynamics are not significantly impacted by Mach number effects. There may be occasions when the maximum velocity within a tornado is limited by sonic conditions for brief periods but it is a soft limit which allows modest supersonic velocities that would be difficult to observe in an actual tornado

Static Entanglement Analysis of Quantum Programs

Quantum entanglement plays a crucial role in quantum computing. Entangling information has important implications for understanding the behavior of quantum programs and avoiding entanglement-induced errors. Entanglement analysis is a static code analysis technique that determines which qubit may entangle with another qubit and establishes an entanglement graph to represent the whole picture of interactions between entangled qubits. This paper presents the first static entanglement analysis method for quantum programs developed in the practical quantum programming language Q\#. Our method first constructs an interprocedural control flow graph (ICFG) for a Q\# program and then calculates the entanglement information not only within each module but also between modules of the program. The analysis results can help improve the reliability and security of quantum programs

Comparative Analysis on Energy Consumption of Commercial Buildings Based on Sub-metered Data

With energy use growing rapidly around the world, building energy conservation is becoming a great concern especially for large commercial buildings. Therefore, it is of great significance to develop appropriate methods for energy use assessment of commercial buildings. In recent years, energy monitoring system (EMS) has been applied in some large-scale commercial buildings, which has laid the foundation for exhaustive and authentic evaluation. However, most of the current studies are only focused on annual or monthly aggregated energy consumption. Though end-use data are monitored in some buildings, only major categories or equipment are included. Little has been done to analyze the energy performance of numerous buildings with detailed hourly end-use data. With the access to hourly sub-metered data of detailed end uses, this study aims to introduce a comparing method to evaluate building energy performance through a case study. Information on selected buildings in the case was introduced. The research intends to compare energy use intensity (EUI) of the 19 malls based on a uniform energy data model, from total energy to detailed end-uses. It was shown that there is a significant discrepancy on the total energy use among these buildings, mainly due to HVAC (Heating, Ventilation and Air Conditioning) and public lighting. Then an in-depth comparative study was conducted on the energy consumption of public lighting and HVAC respectively. An unexpectedly remarkable discrepancy was illustrated on the EUI of public lighting. Thus the daily and hourly energy of public lighting were compared to identify the discrepancy in management mode. The study on HVAC was focused on the comparison of daily and hourly EUI in terms of four subordinate end uses (chillers, chilled water pumps, fans and cooling systems). The result showed that chillers accounts for larger proportions of total energy use, and the daily and hourly data were compared between buildings with similar climate. At last, the methods were summarized and challenges were discussed

Associations of Muscle Mass and Strength with All-Cause Mortality among US Older Adults

INTRODUCTION: Recent studies suggested that muscle mass and muscle strength may independently or synergistically affect aging-related health outcomes in older adults; however, prospective data on mortality in the general population are sparse. METHODS: We aimed to prospectively examine individual and joint associations of low muscle mass and low muscle strength with all-cause mortality in a nationally representative sample. This study included 4449 participants age 50 yr and older from the National Health and Nutrition Examination Survey 1999 to 2002 with public use 2011 linked mortality files. Weighted multivariable logistic regression models were adjusted for age, sex, race, body mass index (BMI), smoking, alcohol use, education, leisure time physical activity, sedentary time, and comorbid diseases. RESULTS: Overall, the prevalence of low muscle mass was 23.1% defined by appendicular lean mass (ALM) and 17.0% defined by ALM/BMI, and the prevalence of low muscle strength was 19.4%. In the joint analyses, all-cause mortality was significantly higher among individuals with low muscle strength, whether they had low muscle mass (odds ratio [OR], 2.03; 95% confidence interval [CI], 1.27-3.24 for ALM; OR, 2.53; 95% CI, 1.64-3.88 for ALM/BMI) or not (OR, 2.66; 95% CI, 1.53-4.62 for ALM; OR, 2.17; 95% CI, 1.29-3.64 for ALM/BMI). In addition, the significant associations between low muscle strength and all-cause mortality persisted across different levels of metabolic syndrome, sedentary time, and LTPA. CONCLUSIONS: Low muscle strength was independently associated with elevated risk of all-cause mortality, regardless of muscle mass, metabolic syndrome, sedentary time, or LTPA among US older adults, indicating the importance of muscle strength in predicting aging-related health outcomes in older adults

A Bayesian Network Based Adaptability Design of Product Structures for Function Evolution

Structure adaptability design is critical for function evolution in product families, in which many structural and functional design factors are intertwined together with manufacturing cost, customer satisfaction, and final market sales. How to achieve a delicate balance among all of these factors to maximize the market performance of the product is too complicated to address based on traditional domain experts’ knowledge or some ad hoc heuristics. Here, we propose a quantitative product evolution design model that is based on Bayesian networks to model the dynamic relationship between customer needs and product structure design. In our model, all of the structural or functional features along with customer satisfaction, manufacturing cost, sale price, market sales, and indirect factors are modeled as random variables denoted as nodes in the Bayesian networks. The structure of the Bayesian model is then determined based on the historical data, which captures the dynamic sophisticated relationship of customer demands of a product, structural design, and market performance. Application of our approach to an electric toothbrush product family evolution design problem shows that our model allows for designers to interrogate with the model and obtain theoretical and decision support for dynamic product feature design process

Renewable Energy in District Heating Systems in China:Status and perspectives

In the fight against climate change, China’s aim is to ensure that the CO2 emissions peak before 2030 and to reach carbon neutrality by 2060. The heating sector is one of the key elements to ensure those targets are reached. Today around 95% of heating is based on coal, natural gas and oil. With energy efficiency and renewable energy changes using district heating and smart energy systems, this transition can be more cost efficient. Currently, district heating has covered approx.85% of the total heating areas in Northern China, however a deeper understanding is required to unlock the full potential of this infrastructure. In this paper we illustrate that a combination of energy refurbishment of buildings, energy efficiency using waste heat, and renewable energy sources from geothermal, bioenergy and solar thermal, can decarbonize the buildings using district heating in China. By using lower temperature 4th generation district heating, thermal energy storage and large-scale heat pumps, such systems can help integrating more renewable energy. In international and Chinese scientific literature there is a lack of research and knowledge within smart energy systems, low temperature district heating and unconventional waste heat sources. Although the sources and main infrastructures needed in the form of district heating pipe network and electricity grids exist, a deeper understanding is needed in response to the challenges regarding the geographical separation between renewable sources and demanding area as well as the potential for deeper renovation of buildings and further expansion of district heating. Such knowledge is required to support the early signs of policies changing towards stronger focuses on energy efficiency and renewable energy

Reconstruction of Curve Networks from Unorganized Spatial Points

Curve network reconstruction from a set of unorganized points is an important problem in reverse engineering and computer graphics. In this paper, we propose an automatic method to extract curve segments and reconstruct curve networks from unorganized spatial points. Our proposed method divides reconstruction of curve networks into two steps: 1) detecting nodes of curve segments and 2) reconstructing curve segments. For detection of nodes of curve segments, we present a principal component analysis-based algorithm to obtain candidate nodes from unorganized spatial points and a Euclidean distance-based iterative algorithm to remove peripheral nodes and find the actual nodes. For reconstruction of curve segments, we propose an extraction algorithm to obtain the points on each of curve segments. We present quite a number of examples which use our proposed method to reconstruct curve networks from unorganized spatial points. The results demonstrate the effectiveness of our proposed method and its advantages of good automation and high reconstruction efficiency

A consensus linkage map of the grass carp (Ctenopharyngodon idella) based on microsatellites and SNPs

<p>Abstract</p> <p>Background</p> <p>Grass carp (<it>Ctenopharyngodon idella</it>) belongs to the family Cyprinidae which includes more than 2000 fish species. It is one of the most important freshwater food fish species in world aquaculture. A linkage map is an essential framework for mapping traits of interest and is often the first step towards understanding genome evolution. The aim of this study is to construct a first generation genetic map of grass carp using microsatellites and SNPs to generate a new resource for mapping QTL for economically important traits and to conduct a comparative mapping analysis to shed new insights into the evolution of fish genomes.</p> <p>Results</p> <p>We constructed a first generation linkage map of grass carp with a mapping panel containing two F1 families including 192 progenies. Sixteen SNPs in genes and 263 microsatellite markers were mapped to twenty-four linkage groups (LGs). The number of LGs was corresponding to the haploid chromosome number of grass carp. The sex-specific map was 1149.4 and 888.8 cM long in females and males respectively whereas the sex-averaged map spanned 1176.1 cM. The average resolution of the map was 4.2 cM/locus. BLAST searches of sequences of mapped markers of grass carp against the whole genome sequence of zebrafish revealed substantial macrosynteny relationship and extensive colinearity of markers between grass carp and zebrafish.</p> <p>Conclusions</p> <p>The linkage map of grass carp presented here is the first linkage map of a food fish species based on co-dominant markers in the family Cyprinidae. This map provides a valuable resource for mapping phenotypic variations and serves as a reference to approach comparative genomics and understand the evolution of fish genomes and could be complementary to grass carp genome sequencing project.</p