scholarly journals Noise-Driven Universal Dynamics towards an Infinite Temperature State

2020 ◽  
Vol 124 (13) ◽  
Author(s):  
Jie Ren ◽  
Qiaoyi Li ◽  
Wei Li ◽  
Zi Cai ◽  
Xiaoqun Wang
Keyword(s):  
Temperature State ◽  
Infinite Temperature

scholarly journals Lieb's Theorem and Maximum Entropy Condensates

Quantum ◽  
2021 ◽  
Vol 5 ◽  
pp. 610
Author(s):  
Joseph Tindall ◽  
Frank Schlawin ◽  
Michael Sentef ◽  
Dieter Jaksch
Keyword(s):  
Quantum System ◽  
Maximum Entropy ◽  
Ground State ◽  
Broad Class ◽  
Optical Manipulation ◽  
Many Body ◽  
Temperature State ◽  
Many Body Systems ◽  
Advantageous Effect ◽  
Infinite Temperature

Coherent driving has established itself as a powerful tool for guiding a many-body quantum system into a desirable, coherent non-equilibrium state. A thermodynamically large system will, however, almost always saturate to a featureless infinite temperature state under continuous driving and so the optical manipulation of many-body systems is considered feasible only if a transient, prethermal regime exists, where heating is suppressed. Here we show that, counterintuitively, in a broad class of lattices Floquet heating can actually be an advantageous effect. Specifically, we prove that the maximum entropy steady states which form upon driving the ground state of the Hubbard model on unbalanced bi-partite lattices possess uniform off-diagonal long-range order which remains finite even in the thermodynamic limit. This creation of a `hot' condensate can occur on any driven unbalanced lattice and provides an understanding of how heating can, at the macroscopic level, expose and alter the order in a quantum system. We discuss implications for recent experiments observing emergent superconductivity in photoexcited materials.

scholarly journals Analysis of long-term temperature monitoring of multiple wind turbines

2021 ◽  
pp. 002029402110130
Author(s):  
Xian Wang ◽  
Qian-cheng Zhao ◽  
Xue-bing Yang ◽  
Bing Zeng
Keyword(s):  
Wind Turbines ◽  
Temperature Rise ◽  
Performance Optimization ◽  
Wind Farm ◽  
Engineering Practice ◽  
Multiple Perspectives ◽  
Temperature State ◽  
Condition Monitoring Systems ◽  
Historical Temperature

The historical temperature data logged in the supervisory control and data acquisition (SCADA) system contains a wealth of information that can assist with the performance optimization of wind turbines (WTs). However, mining and using these long-term data is difficult and time-consuming due to their complexity, volume, etc. In this study, we tracked and analyzed the 5-year trends of major SCADA temperature rise variables in relation to the active power of four WTs in a real wind farm. To uncover useful information, an extended version of the bins method, which calculates the standard deviation (SD) as well as the average, is proposed and adopted. The implications of the analysis for engineering practice are discussed from multiple perspectives. The research results demonstrate a change in the patterns of the main temperature rise variables in a real wind farm, completeness of the monitoring of the WT internal temperature state, influence of wind turbine aging on temperature signals, a correlation between different measurement points, and a correlation between signals from different years. The knowledge gained from this research provides a reference for the development of more practical and comprehensive condition monitoring systems and methods, as well as better operation maintenance strategies.

scholarly journals Simulation of Diffusion Processes in Chemical and Thermal Processing of Machine Parts

Processes ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 698
Author(s):  
Kateryna Kostyk ◽  
Michal Hatala ◽  
Viktoriia Kostyk ◽  
Vitalii Ivanov ◽  
Ivan Pavlenko ◽  
...  
Keyword(s):  
Mathematical Modeling ◽  
Temperature Distribution ◽  
Thermal Treatment ◽  
Diffusion Processes ◽  
Nitrogen Concentration ◽  
The Body ◽  
Functional Dependencies ◽  
Technological Parameters ◽  
Gas Nitriding ◽  
Temperature State

To solve a number of technological issues, it is advisable to use mathematical modeling, which will allow us to obtain the dependences of the influence of the technological parameters of chemical and thermal treatment processes on forming the depth of the diffusion layers of steels and alloys. The paper presents mathematical modeling of diffusion processes based on the existing chemical and thermal treatment of steel parts. Mathematical modeling is considered on the example of 38Cr2MoAl steel after gas nitriding. The gas nitriding technology was carried out at different temperatures for a duration of 20, 50, and 80 h in the SSHAM-12.12/7 electric furnace. When modeling the diffusion processes of surface hardening of parts in general, providing a specifically given distribution of nitrogen concentration over the diffusion layer’s depth from the product’s surface was solved. The model of the diffusion stage is used under the following assumptions: The diffusion coefficient of the saturating element primarily depends on temperature changes; the metal surface is instantly saturated to equilibrium concentrations with the saturating atmosphere; the surface layer and the entire product are heated unevenly, that is, the product temperature is a function of time and coordinates. Having satisfied the limit, initial, and boundary conditions, the temperature distribution equations over the diffusion layer’s depth were obtained. The final determination of the temperature was solved by an iterative method. Mathematical modeling allowed us to get functional dependencies for calculating the temperature distribution over the depth of the layer and studying the influence of various factors on the body’s temperature state of the body.

Development of Laminar Plasma Shielded HF-ERW Process: Advanced Welding Process of HF-ERW 3

2012 ◽  
Author(s):  
Hideki Hamatani ◽  
Funinori Watanabe ◽  
Nobuo Mizuhashi ◽  
Sunao Takeuchi ◽  
Yoshiaki Hirota ◽  
...  
Keyword(s):  
High Temperature ◽  
Welding Process ◽  
Air Entrainment ◽  
Plasma Jets ◽  
Control Technique ◽  
Monitoring Methods ◽  
Line Pipe ◽  
Temperature State ◽  
Weld Area ◽  
Cold Gas

High frequency - electric resistance welded (HF-ERW) pipe has been successfully used for many years for a number of applications. The benefits of HF-ERW pipe are considerable, including a higher dimensional tolerance and lower prices than seamless pipe and UO pipe. The conventional weld seam produced by HF-ERW, however, often has a relatively low toughness. We have developed an automatic heat input control technique based on ERW phenomena that relies on optical and electrical monitoring methods and has been shown to result in a significant improvement in the toughness. Shielding of the weld area must also be considered as a key factor in the formation of a sound weld. It has been shown that an inert cold gas (e.g., at room temperature) shielding technique is effective for maintaining a stable low oxygen state in the weld area that inhibits the formation of penetrator, a pancake oxide inclusions. Compared to the cold gas shielding technique, high temperature gas shielding, due to its higher kinetic viscosity coefficient, should make it easier to sustain a higher laminar flow, thus leading to a rather low air entrainment in the shielding gas. In addition, plasma is a much higher temperature state (∼6000 K), and the dissociated gases can react with the entrained oxygen; plasma jets should, therefore, enhance the overall shielding effects. Moreover, oxides on the strip edges can be expected to melt and/or be reduced by the high temperature plasma jets. Nippon Steel has developed a plasma torch that can generate a long and wide laminar argon – nitrogen – (hydrogen) jet. This paper describes the results obtained from our investigation of the effects of a plasma jet shield on the weld area of high strength line pipe with a yield strength grade of X65. Preliminary attempts in applying this novel shielding technique has been found, as expected, to demonstrate extremely low numbers of weld defects and a good low temperature toughness of the HF-ERW seam.

scholarly journals Multiband transport and nonmetallic low-temperature state of K0.50 Na0.24 Fe1.52 Se2

2014 ◽  
Vol 90 (2) ◽  
Author(s):  
Hyejin Ryu ◽  
F. Wolff-Fabris ◽  
J. B. Warren ◽  
M. Uhlarz ◽  
J. Wosnitza ◽  
...  
Keyword(s):  
Low Temperature ◽  
Temperature State

Characterizing waste disposal sites by using multi-spectral satellite imagery

2021 ◽  
Author(s):  
Gaetana Ganci ◽  
Annalisa Cappello ◽  
Giuseppe Bilotta ◽  
Giuseppe Pollicino ◽  
Luigi Lodato
Keyword(s):  
Soil Moisture ◽  
Surface Temperature ◽  
Waste Disposal ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
The State ◽  
Dump Site ◽  
Temperature State ◽  
Surrounding Areas

<p>The application of remote sensing for monitoring, detecting and analysing the spatial and extents and temporal changes of waste dumping sites and landfills could become a cost-effective and powerful solution. Multi-spectral satellite images, especially in the thermal infrared, can be exploited to characterize the state of activity of a landfill.  Indeed, waste disposal sites, during the period of activity, can show differences in surface temperature (LST, Land Surface Temperature), state of vegetation (estimated through NDVI, Normalized Difference Vegetation Index) or soil moisture (estimated through NDWI, Normalized Difference Water Index) compared to neighboring areas. Landfills with organic waste typically show higher temperatures than surrounding areas due to exothermic decomposition activities. In fact, the biogas, in the absence or in case of inefficiency of the conveying plants, rises through the layers of organic matter and earth (landfill body) until it reaches the surface at a temperature of over 40 ° C. Moreover, in some cases, leachate contamination of the aquifers can be identified by analyzing the soil moisture, through the estimate of the NDWI, and the state of suffering of the vegetation surrounding the site, through the estimate of the NDVI. This latter can also be an indicator of soil contamination due to the presence of toxic and potentially dangerous waste when buried or present nearby. To take into account these facts, we combine the LST, NDVI and NDWI indices of the dump site and surrounding areas in order to characterize waste disposal sites. Preliminary results show how this approach can bring out the area and level of activity of known landfill sites. This could prove particularly useful for the definition of intervention priorities in landfill remediation works.</p>

scholarly journals On the dimorphism and the pressure–temperature state diagram of racemic m-nisoldipine, a dihydropyridine calcium ion antagonist

2018 ◽  
Vol 76 (5) ◽  
pp. 341-347 ◽  
Author(s):  
K. Li ◽  
G. Gbabode ◽  
G. Coquerel ◽  
R. Céolin ◽  
I.B. Rietveld
Keyword(s):  
Calcium Ion ◽  
State Diagram ◽  
Temperature State

scholarly journals Variability and Confidence Intervals for the Mean of Climate Data with Short- and Long-Range Dependence

2018 ◽  
Vol 31 (15) ◽  
pp. 6135-6156 ◽  
Author(s):  
Matthew C. Bowers ◽  
Wen-wen Tung
Keyword(s):  
Confidence Intervals ◽  
Long Range ◽  
Long Memory ◽  
Long Range Dependence ◽  
Climate Data ◽  
Temperature State ◽  
Correlation Structures ◽  
The Mean ◽  
Error Bars ◽  
Mean State

This paper presents an adaptive procedure for estimating the variability and determining error bars as confidence intervals for climate mean states by accounting for both short- and long-range dependence. While the prevailing methods for quantifying the variability of climate means account for short-range dependence, they ignore long memory, which is demonstrated to lead to underestimated variability and hence artificially narrow confidence intervals. To capture both short- and long-range correlation structures, climate data are modeled as fractionally integrated autoregressive moving-average processes. The preferred model can be selected adaptively via an information criterion and a diagnostic visualization, and the estimated variability of the climate mean state can be computed directly from the chosen model. The procedure was demonstrated by determining error bars for four 30-yr means of surface temperatures observed at Potsdam, Germany, from 1896 to 2015. These error bars are roughly twice the width as those obtained using prevailing methods, which disregard long memory, leading to a substantive reinterpretation of differences among mean states of this particular dataset. Despite their increased width, the new error bars still suggest that a significant increase occurred in the mean temperature state of Potsdam from the 1896–1925 period to the most recent period, 1986–2015. The new wider error bars, therefore, communicate greater uncertainty in the mean state yet present even stronger evidence of a significant temperature increase. These results corroborate a need for more meticulous consideration of the correlation structures of climate data—especially of their long-memory properties—in assessing the variability and determining confidence intervals for their mean states.

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