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Relevant bibliographies by topics / Two-temperature model

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Academic literature on the topic 'Two-temperature model'

Author: Grafiati

Published: 4 June 2021

Last updated: 6 September 2023

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Journal articles on the topic "Two-temperature model"

1

Guo, J. H., Y. Li, and H. G. Shan. "A Two-Temperature Model for LBVs." Proceedings of the International Astronomical Union 2004, IAUS226 (September 2004): 506–10. http://dx.doi.org/10.1017/s1743921305001146.

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Kristoffel, N., P. Konsin, and T. Örd. "Two-band model for high-temperature superconductivity." La Rivista Del Nuovo Cimento Series 3 17, no. 9 (September 1994): 1–41. http://dx.doi.org/10.1007/bf02724515.

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Girard, R., J. B. Belhaouari, J. J. Gonzalez, and A. Gleizes. "A two-temperature kinetic model of SF6plasma." Journal of Physics D: Applied Physics 32, no. 22 (November 12, 1999): 2890–901. http://dx.doi.org/10.1088/0022-3727/32/22/311.

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d’Hueppe, A., M. Chandesris, D. Jamet, and B. Goyeau. "Coupling a two-temperature model and a one-temperature model at a fluid-porous interface." International Journal of Heat and Mass Transfer 55, no. 9-10 (April 2012): 2510–23. http://dx.doi.org/10.1016/j.ijheatmasstransfer.2012.01.009.

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Saito, Masao. "Accuracy of Temperature Estimation by Two-dimensional Model." Thermal Medicine(Japanese Journal of Hyperthermic Oncology) 4, no. 3 (1988): 215–19. http://dx.doi.org/10.3191/thermalmedicine.4.215.

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Olynick, David P., and H. A. Hassan. "New two-temperature dissociation model for reacting flows." Journal of Thermophysics and Heat Transfer 7, no. 4 (October 1993): 687–96. http://dx.doi.org/10.2514/3.478.

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Sobolev, S. L. "Two-temperature discrete model for nonlocal heat conduction." Journal de Physique III 3, no. 12 (December 1993): 2261–69. http://dx.doi.org/10.1051/jp3:1993273.

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CAIAFA, C. F., and A. N. PROTO. "TEMPERATURE ESTIMATION IN THE TWO-DIMENSIONAL ISING MODEL." International Journal of Modern Physics C 17, no. 01 (January 2006): 29–38. http://dx.doi.org/10.1142/s0129183106008856.

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We present two new algorithms for the estimation of the temperature from a realization of a 2-D Ising model. The methods here introduced are based in the maximization of pseudo likelihood and on the minimum mean squared error (MSE) fit of the conditional probability function. We derive the analytical expressions of these estimators and also we include computational results comparing these new techniques with the traditional method. A very good performance in terms of the average absolute error and the average standard deviation is demonstrated through simulations in a 100 × 100 lattice in the ferromagnetic and antiferromagnetic cases. Summarizing, we have provided two new useful computational tools that allow us to measure the "virtual" temperature of an Ising like system.

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Layevskii, Yu M., and A. A. Kalinkin. "A two-temperature model of hydrate-bearing rock." Mathematical Models and Computer Simulations 2, no. 6 (November 14, 2010): 753–59. http://dx.doi.org/10.1134/s2070048210060104.

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Wang (王亮堯), Liang-Yao, Hsien Shang (尚賢), Ruben Krasnopolsky, and Tzu-Yang Chiang (江子揚). "A TWO-TEMPERATURE MODEL OF MAGNETIZED PROTOSTELLAR OUTFLOWS." Astrophysical Journal 815, no. 1 (December 7, 2015): 39. http://dx.doi.org/10.1088/0004-637x/815/1/39.

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Dissertations / Theses on the topic "Two-temperature model"

1

Cullen, Peter H. "High-temperature superconductors and the two-dimensional hubbard model." Thesis, Heriot-Watt University, 1996. http://hdl.handle.net/10399/729.

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Mukhopadhyay, S., R. Picard, S. Trostorff, and M. Waurick. "A note on a two-temperature model in linear thermoelasticity." Sage, 2017. https://tud.qucosa.de/id/qucosa%3A35517.

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We discuss the so-called two-temperature model in linear thermoelasticity and provide a Hilbert space framework for proving well-posedness of the equations under consideration. With the abstract perspective of evolutionary equations, the two-temperature model turns out to be a coupled system of the elastic equations and an abstract ordinary differential equation (ODE). Following this line of reasoning, we propose another model which is entirely an abstract ODE.We also highlight an alternative method for a two-temperature model, which might be of independent interest.

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Haid, Benjamin J. (Benjamin John Jerome) 1974. "Two-dimensional quench propagation model for a three-dimensional "high-temperature" superconducting coil." Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/9598.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1998.
Includes bibliographical references (leaves 89-90).
Quenching is a thermal failure mechanism encountered with superconducting magnets. When a section of conductor is driven normal by an external heat input, the magnet transport current flows through a resistance, causing joule dissipation. If heat is not conducted away from the normal region faster than it is dissipated, the normal region will grow and the temperature will increase indefinitely. Growth of the normal region is commonly refereed to as normal zone propagation(NZP). A reliable NZP model is necessary for designing protection systems because a quench may cause irreparable damage if a section of the winding is over-heated. This thesis develops a numerical NZP model for a three dimensional, dry-wound, BSSCO- 2223 superconducting magnet. The test magnet operates under quasi-adiabatic conditions at 20 K and above, in zero background field. It is contained in a stainless steel cryostat and cooled by a Daikin cryocooler. The NZP model is based on the two-dimensional transient heat diffusion equation. Quenches arc simulated by a numerical code using the finite-difference method. Agreement between voltage traces obtained in the test magnet during heater-induced quenching events and those computed by the numerical NZP model is reasonable. The model indicates that thermal contact resistance has a dominant effect on propagation in the azimuthal direction(across layers). The model is also used to simulate quenching in persistent-mode magnets similar in construction with the test magnet. Specifically studied were effects of magnet inductance, for a given set of operating current and temperature, on the maximum temperature reached in one full turn of the conductor located at the magnet outermost layer driven normal with a heater. The simulation demonstrates that there is an operating current limit for a given magnet inductance and operating temperature below which the magnet can be considered self-protecting. The simulation also demonstrates that shunted subdivision lowers the maximum temperature.
by Benjamin J. Haid.
S.M.

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Kjellander, Kalle. "Two Simple Soil Temperature Models: Applied and Tested on Sites in Sweden." Thesis, Uppsala universitet, Institutionen för geovetenskaper, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-255003.

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Bingham, Quinten Glen. "Data Collection and Analysis Methods for Two-Zone Temperature and Solute Model Parameter Estimation and Corroboration." DigitalCommons@USU, 2010. https://digitalcommons.usu.edu/etd/564.

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Water temperature directly affects biological and chemical processes of fresh water ecosystems. Elevated instream temperatures are commonplace in the Virgin River of southwestern Utah during summer due to a hot desert climate and high water demands that result in low stream flows. This is of concern since the Virgin River is home to two endangered species, the Virgin River Chub (Gila seminuda) and Woundfin (Plagopterus argentissimus). Efforts to model instream temperatures within the Virgin River have been undertaken to help mitigate elevated instream temperatures including the development of a two-zone temperature and solute (TZTS) model. This model was developed to approximate the dominant processes that influence instream temperatures and used both temperature and solute data in parameter estimation. Past model applications highlighted two concerns: (1) how to confidently estimate the high number of parameters and (2) whether Rhodamine WT (RhWT) could be used as a conservative solute tracer within the Virgin River. To begin addressing these issues, spatially representative data were collected to facilitate the physical estimation of two previously calibrated parameters: total average channel width (BTOT) and the fraction of channel width associated with dead zones (β). Methods for analyzing multispectral and thermal infrared imagery were developed to provide estimates of these parameters at different resolutions. Three different TZTS model calibration cases were then evaluated to determine how decreasing the calibrated parameters and increasing the resolution and frequency at which these parameters are estimated improved model predictions and/or decreased parameter uncertainty. While temperature predictions did not change significantly in each of the calibrations, parameter uncertainty was reduced. The concern regarding the use of RhWT resulted in a series of studies to quantify the potential losses of RhWT within this system. A batch sorption study resulted in distribution coefficient values lower than those found in literature. A photodegradation study suggested possible photolysis; however, a dual tracer study conducted within the Virgin River comparing Br- (conservative tracer) with RhWT confirmed that there was insignificant RhWT loss within this system.

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O'Hare, Anthony. "The formation of low-temperature superstructures in the two-dimensional Ising model with next-nearest neighbour interactions." Thesis, Loughborough University, 2007. https://dspace.lboro.ac.uk/2134/36011.

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For several decades the formation of different kinds of superstructures in solids has been a topical issue in condensed matter physics. The superstructures (or spatially modulated structures) may be of a different nature: magnetic patterns like spin-density waves, inhomogeneous charge distributions in charge-ordered compounds, dipolar and quadrupolar ordering in ferroelectrics or ferroelastics, regular lattice distortions and related orbital structures, stripe-like arrangements of dopants in alloys, etc. The phase diagrams of such compounds can be rather complicated involving a large number of phases with non-trivial types of ordering. Fortunately, all this wealth of seemingly unrelated phenomena can be often described by rather simple models with a due account taken of a competitive character of the most important interactions. In this thesis I will investigate the Ising model in 2-D with nearest and next-nearest neighbour interactions using several methods including exact diagonalisation of small clusters, transfer matrix technique and Monte Carlo simulation of large lattices.

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Zhang, Wei. "Many-Body Localization in Disordered Quantum Spin Chain and Finite-Temperature Gutzwiller Projection in Two-Dimensional Hubbard Model:." Thesis, Boston College, 2019. http://hdl.handle.net/2345/bc-ir:108695.

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Thesis advisor: Ziqiang . Wang
The transition between many-body localized states and the delocalized thermal states is an eigenstate phase transition at finite energy density outside the scope of conventional quantum statistical mechanics. We apply support vector machine (SVM) to study the phase transition between many-body localized and thermal phases in a disordered quantum Ising chain in a transverse external field. The many-body eigenstate energy E is bounded by a bandwidth W=Eₘₐₓ-Eₘᵢₙ. The transition takes place on a phase diagram spanned by the energy density ϵ=2(Eₘₐₓ-Eₘᵢₙ)/W and the disorder strength ẟJ of the spin interaction uniformly distributed within [-ẟJ, ẟJ], formally parallel to the mobility edge in Anderson localization. In our study we use the labeled probability density of eigenstate wavefunctions belonging to the deeply localized and thermal regimes at two different energy densities (ϵ's) as the training set, i.e., providing labeled data at four corners of the phase diagram. Then we employ the trained SVM to predict the whole phase diagram. The obtained phase boundary qualitatively agrees with previous work using entanglement entropy to characterize these two phases. We further analyze the decision function of the SVM to interpret its physical meaning and find that it is analogous to the inverse participation ratio in configuration space. Our findings demonstrate the ability of the SVM to capture potential quantities that may characterize the many-body localization phase transition. To further investigate the properties of the transition, we study the behavior of the entanglement entropy of a subsystem of size L_A in a system of size L > L_A near the critical regime of the many-body localization transition. The many-body eigenstates are obtained by exact diagonalization of a disordered quantum spin chain under twisted boundary conditions to reduce the finite-size effect. We present a scaling theory based on the assumption that the transition is continuous and use the subsystem size L_A/ξ as the scaling variable, where ξ is the correlation length. We show that this scaling theory provides an effective description of the critical behavior and that the entanglement entropy follows the thermal volume law at the transition point. We extract the critical exponent governing the divergence of ξ upon approaching the transition point. We again study the participation entropy in the spin-basis of the domain wall excitations and show that the transition point and the critical exponent agree with those obtained from finite size scaling of the entanglement entropy. Our findings suggest that the many-body localization transition in this model is continuous and describable as a localization transition in the many-body configuration space. Besides the many-body localization transition driven by disorder, We also study the Coulomb repulsion and temperature driving phase transitions. We apply a finite-temperature Gutzwiller projection to two-dimensional Hubbard model by constructing a "Gutzwiller-type" density matrix operator to approximate the real interacting density matrix, which provides the upper bound of free energy of the system. We firstly investigate half filled Hubbard model without magnetism and obtain the phase diagram. The transition line is of first order at finite temperature, ending at 2 second order points, which shares qualitative agreement with dynamic mean field results. We derive the analytic form of the free energy and therefor the equation of states, which benefits the understanding of the different phases. We later extend our approach to take anti-ferromagnetic order into account. We determine the Neel temperature and explore its interesting behavior when varying the Coulomb repulsion
Thesis (PhD) — Boston College, 2019
Submitted to: Boston College. Graduate School of Arts and Sciences
Discipline: Physics

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Chen, Linchao. "Predictive Modeling of Spatio-Temporal Datasets in High Dimensions." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1429586479.

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Wang, Ningyu. "Melting, Solidification and Sintering/Coalescence of Nanoparticles." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1284476300.

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Skoglund, Emil. "A NUMERICAL MODEL OF HEAT- AND MASS TRANSFER IN POLYMER ELECTROLYTE FUEL CELLS : A two-dimensional 1+1D approach to solve the steady-state temperature- and mass- distributions." Thesis, Mälardalens högskola, Framtidens energi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-55223.

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Methods of solving the steady state characteristics of a node matrix equation system over a polymer electrolyte fuel cell (PEFC) were evaluated. The most suitable method, referred to as the semi-implicit method, was set up in a MATLAB program. The model covers heat transfer due to thermal diffusion throughout the layers and due to thermal advection+diffusion in the gas channels. Included mass transport processes cover only transport of water vapor and consist of the same diffusion/advection schematics as the heat transfer processes. The mass transport processes are hence Fickian diffusion throughout all the layers and diffusion+advection in the gas channels. Data regarding all the relevant properties of the layer materials were gathered to simulate these heat- and mass transfer processes.Comparing the simulated temperature profiles obtained with the model to the temperature profiles of a previous work’s model, showed that the characteristics and behavior of the temperature profile are realistic. There were however differences between the results, but due to the number of unknown parameters in the previous work’s model it was not possible to draw conclusions regarding the accuracy of the model by comparing the results.Comparing the simulated water concentration profiles of the model and measured values, showed that the model produced concentration characteristics that for the most part alignedwell with the measurement data. The part of the fuel cell where the concentration profile did not match the measured data was the cathode side gas diffusion layer (GDL). This comparison was however performed with the assumption that relative humidity corresponds to liquid water concentration, and that this liquid water concentration is in the same range as the measured data. Because of this assumption it was not possible to determine the accuracy of the model.

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Books on the topic "Two-temperature model"

1

Chul, Park. Assessment of two-temperature kinetic model for ionizing air. New York: American Institute of Aeronautics and Astronautics, 1987.

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2

Rathbun, R. E. Application of the two-film model to the volatilization of acetone and t-butyl alcohol from water as a function of temperature. Washington: U.S. G.P.O., 1988.

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Rathbun, R. E. Application of the two-film model to the volatilization of acetone and t-butyl alcohol from water as a function of temperature. Washington, DC: Dept. of the Interior, 1988.

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J, Hanna Gregory, and Hugh L. Dryden Flight Research Center., eds. Thermal modeling and analysis of a cryogenic tank design exposed to extreme heating profiles. Edwards, Calif: National Aeronautics and Space Administration, Dryden Flight Research Facility, 1991.

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J, Hanna Gregory, and Hugh L. Dryden Flight Research Center., eds. Thermal modeling and analysis of a cryogenic tank design exposed to extreme heating profiles. Edwards, Calif: National Aeronautics and Space Administration, Dryden Flight Research Facility, 1991.

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6

Bostick, Kent C. Two-dimensional temperature model for target materials bombarded by ion beams. 1992.

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Bostick, Kent C. Two-dimensional temperature model for target materials bombarded by ion beams. 1992.

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8

Lee, Sunhee, and Yong Joe. Electron Transport in DNA Moledules: Temperature and magnetic fields effects on the electron transport through two-dimensional and four-channel DNA model. LAP Lambert Academic Publishing, 2011.

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Zhang, H. Mesoscopic Structures and Their Effects on High-Tc Superconductivity. Edited by A. V. Narlikar. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780198738169.013.12.

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This article presents the results of model calculations carried out to determine the mesoscopic structural features of high-temperature superconducting (HTS) crystal structures, and especially their characteristic high critical temperature (Tc) and anisotropy. The crystal structure of high-temperature superconductors (HTSc) is unique in having some mesoscopic features. For example, the structures of a majority of cuprite superconductors are comprised of two structural blocks, perovskite and rock salt, stacked along the c-direction. This article calculates the interaction between the perovskite and rock salt blocks in the form of combinative energy in order to elucidate the effects of mesoscopic structures on high-Tc superconductivity. Both X-ray diffraction and Raman spectroscopy show that a ‘fixed triangle’ exists in the samples under investigation. The article also examines the importance of electron–phonon coupling in high-Tc superconductors.

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Busuioc, Aristita, and Alexandru Dumitrescu. Empirical-Statistical Downscaling: Nonlinear Statistical Downscaling. Oxford University Press, 2018. http://dx.doi.org/10.1093/acrefore/9780190228620.013.770.

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This is an advance summary of a forthcoming article in the Oxford Research Encyclopedia of Climate Science. Please check back later for the full article.The concept of statistical downscaling or empirical-statistical downscaling became a distinct and important scientific approach in climate science in recent decades, when the climate change issue and assessment of climate change impact on various social and natural systems have become international challenges. Global climate models are the best tools for estimating future climate conditions. Even if improvements can be made in state-of-the art global climate models, in terms of spatial resolution and their performance in simulation of climate characteristics, they are still skillful only in reproducing large-scale feature of climate variability, such as global mean temperature or various circulation patterns (e.g., the North Atlantic Oscillation). However, these models are not able to provide reliable information on local climate characteristics (mean temperature, total precipitation), especially on extreme weather and climate events. The main reason for this failure is the influence of local geographical features on the local climate, as well as other factors related to surrounding large-scale conditions, the influence of which cannot be correctly taken into consideration by the current dynamical global models.Impact models, such as hydrological and crop models, need high resolution information on various climate parameters on the scale of a river basin or a farm, scales that are not available from the usual global climate models. Downscaling techniques produce regional climate information on finer scale, from global climate change scenarios, based on the assumption that there is a systematic link between the large-scale and local climate. Two types of downscaling approaches are known: a) dynamical downscaling is based on regional climate models nested in a global climate model; and b) statistical downscaling is based on developing statistical relationships between large-scale atmospheric variables (predictors), available from global climate models, and observed local-scale variables of interest (predictands).Various types of empirical-statistical downscaling approaches can be placed approximately in linear and nonlinear groupings. The empirical-statistical downscaling techniques focus more on details related to the nonlinear models—their validation, strengths, and weaknesses—in comparison to linear models or the mixed models combining the linear and nonlinear approaches. Stochastic models can be applied to daily and sub-daily precipitation in Romania, with a comparison to dynamical downscaling. Conditional stochastic models are generally specific for daily or sub-daily precipitation as predictand.A complex validation of the nonlinear statistical downscaling models, selection of the large-scale predictors, model ability to reproduce historical trends, extreme events, and the uncertainty related to future downscaled changes are important issues. A better estimation of the uncertainty related to downscaled climate change projections can be achieved by using ensembles of more global climate models as drivers, including their ability to simulate the input in downscaling models. Comparison between future statistical downscaled climate signals and those derived from dynamical downscaling driven by the same global model, including a complex validation of the regional climate models, gives a measure of the reliability of downscaled regional climate changes.

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Book chapters on the topic "Two-temperature model"

1

Takizawa, M. "A Two-Temperature Model of Intracluster Medium." In Numerical Astrophysics, 49–50. Dordrecht: Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-011-4780-4_12.

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Kireeva, Anastasia. "Two-Layer CA Model for Simulating Catalytic Reaction at Dynamically Varying Temperature." In Lecture Notes in Computer Science, 166–75. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11520-7_18.

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Russell-Buckland, Joshua, P. Kaynezhad, S. Mitra, G. Bale, C. Bauer, I. Lingam, C. Meehan, et al. "Systems Biology Model of Cerebral Oxygen Delivery and Metabolism During Therapeutic Hypothermia: Application to the Piglet Model." In Advances in Experimental Medicine and Biology, 31–38. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-48238-1_5.

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AbstractHypoxic ischaemic encephalopathy (HIE) is a significant cause of death and disability. Therapeutic hypothermia (TH) is the only available standard of treatment, but 45–55% of cases still result in death or neurodevelopmental disability following TH. This work has focussed on developing a new brain tissue physiology and biochemistry systems biology model that includes temperature effects, as well as a Bayesian framework for analysis of model parameter estimation. Through this, we can simulate the effects of temperature on brain tissue oxygen delivery and metabolism, as well as analyse clinical and experimental data to identify mechanisms to explain differing behaviour and outcome. Presented here is an application of the model to data from two piglets treated with TH following hypoxic-ischaemic injury showing different responses and outcome following treatment. We identify the main mechanism for this difference as the Q10 temperature coefficient for metabolic reactions, with the severely injured piglet having a median posterior value of 0.133 as opposed to the mild injury value of 5.48. This work demonstrates the use of systems biology models to investigate underlying mechanisms behind the varying response to hypothermic treatment.

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Ota, Koji, Masahiko Mori, and Naruhiro Irino. "Development of Thermal Displacement Prediction Model and Thermal Deformation Measurement Methods." In Lecture Notes in Production Engineering, 3–14. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-34486-2_1.

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AbstractIn machine tools, it is important to maintain accuracy against heat in the entire machining space. The reduction of thermal displacement is achieved by measuring it accurately and then clarify the relationship between the temperature change and the thermal deformation and then creating the prediction and compensation model or applying the countermeasure to suppress the thermal deformation. To solve this issue, the authors have developed methods to measure thermal deformation in two-dimensional space using a laser tracker and cameras. A laser tracker method achieved higher accuracy and smaller measurement uncertainty. Vision-based methods achieved equivalent measurement accuracy to a laser tracker method at shorter measurement time and lower cost. To compensate thermal displacement, convolutional neural network model was developed. Thermal displacement was predicted from temperature sensors with higher accuracy than conventional models. These methods contribute to the development of higher precision machine tools.

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Verma, Rohit, and Sushil Kumar. "Temperature Distribution in Living Tissue with Two-Dimensional Parabolic Bioheat Model Using Radial Basis Function." In Lecture Notes in Electrical Engineering, 363–74. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-1824-7_24.

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Pu, Xiaoqin, Bin Yuan, Yi Yin, Xuewei Xiang, Hui Li, Weishou Miao, and Yang Liu. "Temperature Rise Calculation of Oil-Cooled In-Wheel PMSM Based on Two-Phase Fluid-Solid Coupling Model." In Lecture Notes in Electrical Engineering, 973–81. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0408-2_105.

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Zhao, Zixiang, Zhongdi Duan, Hongxiang Xue, Yuchao Yuan, and Shiwen Liu. "Effects of Inlet Conditions on the Two-Phase Flow Water Hammer Transients in Elastic Tube." In Springer Proceedings in Physics, 955–72. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1023-6_81.

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AbstractTwo-phase flow water hammer events occur in the pipelines of the nuclear power systems and lead to transient and violent pressure shock to tube structures. For the sake of operation safety, the occurrence and severity of the two-phase water hammer should be carefully assessed. This paper presents a parameter analysis of the inlet conditions on the two-phase flow water hammer transients, with considering the elastic effect of the tube walls. A numerical model is established for the vapor-liquid two-phase flow based on the two-fluid six-equation modelling approach, with incorporating correlations and criterions for two-phase flow regime, interfacial interactions and heat transfer. The governing equations are transformed to matrix form expressed by characteristic variables, and solved using the splitting operator method and the total variation diminishing scheme. The accuracy of the model is verified against the experimental data in open literature. Then, the model is applied to investigate the effect of inlet velocity and inlet water temperature on the two-phase flow water hammer transients. The simulation results show that the increase of inlet velocity increases the pressure peak values and brings forward the onset of water hammer, and the increase of inlet temperature decreases the pressure shock. A comparison of the water hammer results between the elastic tube and rigid tube is further presented, and the effect of the elastic modulus on the water hammer is analyzed. The results also show that the pressure peak is largely affected by the tube diameter.

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Gentilal, Nichal, Ariel Naveh, Tal Marciano, Zeev Bomzon, Yevgeniy Telepinsky, Yoram Wasserman, and Pedro Cavaleiro Miranda. "The Impact of Scalp’s Temperature in the Predicted LMiPD in the Tumor During TTFields Treatment for Glioblastoma Multiforme." In Brain and Human Body Modelling 2021, 3–18. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-15451-5_1.

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AbstractTumor Treating Fields (TTFields) is a cancer treatment technique used for glioblastoma multiforme (GBM). It consists in the application of an electric field (EF) in two perpendicular directions alternately by placing transducer arrays on the patient’s scalp. In-vitro studies showed that the higher the electric field in the tumor, the better are the outcomes of the therapy. Therefore, these arrays are strategically placed in positions that can optimize the EF, based on the results of computational simulations. However, due to the required daily usage of this technique, at least 18 hours per day, the temperature of head tissues increases inevitably. To ensure patient’s safety, the temperature of the scalp is monitored and kept around 39.5 °C by changing the injected current, which consequently changes the EF in the tumor. In this work, we studied the impact that accounting for the temperature of the scalp might have in the choice of which layout should be used during TTFields planning. We used both a simplified and a realistic head model in our studies. We solved Laplace’s equation for the electric potential and Pennes’ equation for the temperature distribution using COMSOL Multiphysics. The electric field in the tumor was evaluated using the local minimum power density (LMiPD) both when the temperature of the scalp was considered in treatment planning and when it was not. We concluded that the values of the LMiPD significantly decrease when the temperature is considered. Furthermore, layouts in which two pairs of different arrays are very close to each other lead to the appearance of a common temperature hotspot, and consequently to the most significant variations in the predicted LMiPD values. In future, TTFields treatment planning studies, considering the temperature of the scalp might be beneficial to improve the predictions of treatment effectiveness.

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Biehl, Michael. "The Statistical Physics of Learning Revisited: Typical Learning Curves in Model Scenarios." In Lecture Notes in Computer Science, 128–42. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-82427-3_10.

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AbstractThe exchange of ideas between computer science and statistical physics has advanced the understanding of machine learning and inference significantly. This interdisciplinary approach is currently regaining momentum due to the revived interest in neural networks and deep learning. Methods borrowed from statistical mechanics complement other approaches to the theory of computational and statistical learning. In this brief review, we outline and illustrate some of the basic concepts. We exemplify the role of the statistical physics approach in terms of a particularly important contribution: the computation of typical learning curves in student teacher scenarios of supervised learning. Two, by now classical examples from the literature illustrate the approach: the learning of a linearly separable rule by a perceptron with continuous and with discrete weights, respectively. We address these prototypical problems in terms of the simplifying limit of stochastic training at high formal temperature and obtain the corresponding learning curves.

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Weng, Z. Y., and C. S. Ting. "Dynamical Spiral State in Two-Dimensional Hubbard Model." In High-Temperature Superconductivity, 541–46. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4615-3338-2_57.

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Conference papers on the topic "Two-temperature model"

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Desgrosseilliers, Louis, Dominic Groulx, and Mary Anne White. "Two-Region Fin Model Adjacent Temperature Profile Interactions." In The 15th International Heat Transfer Conference. Connecticut: Begellhouse, 2014. http://dx.doi.org/10.1615/ihtc15.cnd.008887.

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Lambourn, Brian, and Caroline Handley. "A two-temperature model for shocked porous explosive." In SHOCK COMPRESSION OF CONDENSED MATTER - 2015: Proceedings of the Conference of the American Physical Society Topical Group on Shock Compression of Condensed Matter. Author(s), 2017. http://dx.doi.org/10.1063/1.4971707.

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Furutani, Yoichiro, and Atsushi Fukuyama. "Two-temperature model of atoms in dense plasmas." In Laser interaction and related plasma phenomena: 12th international conference. AIP, 1996. http://dx.doi.org/10.1063/1.50459.

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Furudate, Michiko, Satoshi Nonaka, and Keisuke Sawada. "Behavior of two-temperature model in intermediate hypersonic regime." In 37th Aerospace Sciences Meeting and Exhibit. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1999. http://dx.doi.org/10.2514/6.1999-223.

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Afanasiev, Yuri V. "Extended two-temperature model of laser ablation of metals." In High-Power Laser Ablation III. SPIE, 2000. http://dx.doi.org/10.1117/12.407320.

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Lai, Yong G., and David Mooney. "On a Two-Dimensional Temperature Model: Development and Verification." In World Environmental and Water Resources Congress 2009. Reston, VA: American Society of Civil Engineers, 2009. http://dx.doi.org/10.1061/41036(342)294.

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PARK, CHUL. "Assessment of two-temperature kinetic model for ionizing air." In 22nd Thermophysics Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1987. http://dx.doi.org/10.2514/6.1987-1574.

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OLYNICK, DAVID, and H. HASSAN. "A new two-temperature dissociation model for reacting flows." In 27th Thermophysics Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1992. http://dx.doi.org/10.2514/6.1992-2943.

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Grasser, T., B. Kaczer, W. Goes, Th Aichinger, Ph Hehenberger, and M. Nelhiebel. "A two-stage model for negative bias temperature instability." In 2009 IEEE International Reliability Physics Symposium (IRPS). IEEE, 2009. http://dx.doi.org/10.1109/irps.2009.5173221.

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Park, Chul. "The Limits of Two-Temperature Kinetic Model in Air." In 48th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2010. http://dx.doi.org/10.2514/6.2010-911.

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Reports on the topic "Two-temperature model"

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Stephen B. Margolis and Melvin R. Baer. A Singular-Perturbation Analysis of the Burning-Rate Eigenvalue for a Two-Temperature Model of Deflagrations in Confined Porous Energetic Materials. Office of Scientific and Technical Information (OSTI), November 2000. http://dx.doi.org/10.2172/768286.

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Fuchs, Marcel, Ishaiah Segal, Ehude Dayan, and K. Jordan. Improving Greenhouse Microclimate Control with the Help of Plant Temperature Measurements. United States Department of Agriculture, May 1995. http://dx.doi.org/10.32747/1995.7604930.bard.

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A model of the energy balance of a transpiring crop in a greenhouse was developed in a format suitable for use in climate control algorithms aimed at dissipating excess heat during the warm periods. The model's parameters use external climatic variables as input. It incorporates radiation and convective transfer functions related to the operation of control devices like shading screens, vents, fans and enhanced evaporative cooling devices. The model identified the leaf boundary-layer resistance and the leaf stomatal and cuticular resistance as critical parameters regulating the temperature of the foliage. Special experiments evaluated these variables and established their relation to environmental factors. The research established that for heat load conditions in Mediterranean and arid climates transpiring crops maintained their foliage temperature within the range allowing high productivity. Results specify that a water supply ensuring minimum leaf resistance to remain below 100 s m-1, and a ventilation rate of 30 air exchanges per hour, are the conditions needed to achieve self cooling. Two vegetable crops, tomato and sweet pepper fulfilled maintained their leaf resistance within the prescribed range at maturity, i.e., during the critical warm season. The research evaluates the effects of additional cooling obtained from wet pad systems and spray wetting of foliage.

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Ruosteenoja, Kimmo. Applicability of CMIP6 models for building climate projections for northern Europe. Finnish Meteorological Institute, September 2021. http://dx.doi.org/10.35614/isbn.9789523361416.

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In this report, we have evaluated the performance of nearly 40 global climate models (GCMs) participating in Phase 6 of the Coupled Model Intercomparison Project (CMIP6). The focus is on the northern European area, but the ability to simulate southern European and global climate is discussed as well. Model evaluation was started with a technical control; completely unrealistic values in the GCM output files were identified by seeking the absolute minimum and maximum values. In this stage, one GCM was rejected totally, and furthermore individual output files from two other GCMs. In evaluating the remaining GCMs, the primary tool was the Model Climate Performance Index (MCPI) that combines RMS errors calculated for the different climate variables into one index. The index takes into account both the seasonal and spatial variations in climatological means. Here, MCPI was calculated for the period 1981—2010 by comparing GCM output with the ERA-Interim reanalyses. Climate variables explored in the evaluation were the surface air temperature, precipitation, sea level air pressure and incoming solar radiation at the surface. Besides MCPI, we studied RMS errors in the seasonal course of the spatial means by examining each climate variable separately. Furthermore, the evaluation procedure considered model performance in simulating past trends in the global-mean temperature, the compatibility of future responses to different greenhouse-gas scenarios and the number of available scenario runs. Daily minimum and maximum temperatures were likewise explored in a qualitative sense, but owing to the non-existence of data from multiple GCMs, these variables were not incorporated in the quantitative validation. Four of the 37 GCMs that had passed the initial technical check were regarded as wholly unusable for scenario calculations: in two GCMs the responses to the different greenhouse gas scenarios were contradictory and in two other GCMs data were missing from one of the four key climate variables. Moreover, to reduce inter-GCM dependencies, no more than two variants of any individual GCM were included; this led to an abandonment of one GCM. The remaining 32 GCMs were divided into three quality classes according to the assessed performance. The users of model data can utilize this grading to select a subset of GCMs to be used in elaborating climate projections for Finland or adjacent areas. Annual-mean temperature and precipitation projections for Finland proved to be nearly identical regardless of whether they were derived from the entire ensemble or by ignoring models that had obtained the lowest scores. Solar radiation projections were somewhat more sensitive.

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He, Xihua. PR-015-113601-R02 Validation of Internal Corrosion Threat Models for Dry Natural Gas Pipelines. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), August 2015. http://dx.doi.org/10.55274/r0010914.

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This report documents the verification and validation (of the probabilistic models developed previously to predict internal corrosion (IC) threats in nominally dry natural gas pipelines. Model uncertainty quantification showed that "low temperature, high pressure" posed the greatest IC threat. To validate the model, actual measurements were compared to model-predicted wall loss. The comparison included information from an IC failure, investigated by the National Transportation Safety Board (NTSB), with in-line inspection (ILI) data sets from five pipeline operators. Two of the pipeline operator data sets showed wall loss measurements either evenly distributed at all locations around the circumfer-ence of the pipe or predominantly at the top of the pipe. These measurements agreed with negligible wall loss predicted by the model. Two other operator data sets measured significant wall loss occurring at the bottom of the pipe. These measurements agreed with non-negligible risk of IC also predicted by the mod-el. The 5th operator data set confirmed the analysis of ILI data uncertainty and corroborated the validation results. For the NTSB investigated failure, the model prediction is in good agreement with the post-failure examination because the model predicted a very high IC risk for this pipeline that failed. This validation provides increased confidence that the previously developed models can differentiate between negligible and non-negligible wall loss occurring in a dry natural gas pipeline.

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Bajwa, Abdullah, and Timothy Jacobs. PR-457-17201-R02 Residual Gas Fraction Estimation Based on Measured Engine Parameters. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), February 2019. http://dx.doi.org/10.55274/r0011558.

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Gas exchange processes in two-stroke internal combustion engines, commonly referred to as scavenging, are responsible for removing the exhaust gases in the combustion chamber and preparing the combustible fuel-oxidizer mixture that undergoes combustion and converts the chemical energy of the fuel into mechanical work. Scavenging is a complicated phenomenon because of the simultaneous introduction of fresh gases into the engine cylinder through the intake ports, and the expulsion of combustion products from the previous cycles through the exhaust ports. A non-negligible fraction of the gaseous mixture that is trapped in the cylinder at the conclusion of scavenging is composed of residual gases from the previous cycle. This can cause significant changes to the combustion characteristics of the mixture by changing its composition and temperature, i.e. its thermodynamic state. Thus, it is vital to have accurate knowledge of the thermodynamic state of the post-scavenging mixture to be able to reliably predict and control engine performance, efficiency and emissions. Two tools for estimating the trapped mixture state - a simple scavenging model and empirical correlations - were developed in this study. Unfortunately, it is not practical to directly measure the trapped residual fraction for engines operating in the field. To overcome this handicap, simple scavenging models or correlations, which estimate this fraction based on some economically measurable engine parameters, can be developed. This report summarizes the results of event-II of a multi-event project that aims to develop such mathematical formulations for stationary two-stroke natural gas engines using data from more advanced models and experimentation. In this event, results from a GT-Power based model for an Ajax E-565 single-cylinder engine are used to develop a three-event single zone scavenging model and empirical correlations. Both of these mathematical devices produce accurate estimates of the trapped mixture state. The estimates are compared to GT-Power results. In the next event of the project, these results will be validated using experimental data. Various steps followed in the development of the model have been discussed in this report, and at the end some results and recommendations for the next event of the project have been presented.

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LeWinter, Adam, Elias Deeb, Dominic Filiano, and David Finnegan. Continued investigation of thermal and lidar surveys of building infrastructure : Crary Lab and wet utility corridor, McMurdo Station, Antarctica. Engineer Research and Development Center (U.S.), March 2022. http://dx.doi.org/10.21079/11681/43820.

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We conducted a combined lidar and thermal infrared survey from both ground-based and Unmanned Aerial System (UAS) platforms at McMurdo Station, Antarctica, in February 2020 to assess the building thermal envelope and infrastructure of the Crary Lab and the wet utility corridor (utilidor). These high-accuracy, coregistered data produced a 3-D model with assigned temperature values for measured surfaces, useful in identifying thermal anomalies and areas for potential improvements and for assessing building and utilidor infrastructure by locating and quantifying areas settlement and structural anomalies. The ground-based survey of the Crary Lab was similar to previous work performed by the team at both Palmer (2015) and South Pole (2017) Stations. The UAS platform focused on approximately 10,500 linear-feet of utilidor throughout McMurdo Station. The datasets of the two survey areas overlapped, allowing us to combine them into a single, georeferenced 3-D model of McMurdo Station. Coincident exterior temperature and atmospheric measurements and Global Navigation Satellite System real-time kinematic surveys provided further insights. Finally, we assessed the thermal envelope of the Crary Lab and the structural features of the utilidor. The resulting dataset is available for analysis and quantification.

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King. L52120 Long-Term Environmental Monitoring of Near-Neutral and High-pH SCC Sites. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), January 2005. http://dx.doi.org/10.55274/r0011228.

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The aims of this project were (i) to monitor the seasonal variation of environmental conditions at stress corrosion cracking (SCC) sites and (ii) to develop an improved site-selection model for SCC. Environmental and other relevant data have been collected for a total of nine known, or suspected, SCC sites; seven near-neutral pH SCC and two high-pH SCC.� The presence of SCC was determined, or predicted, based on in-service or hydrotest failures, excavation, industry soils model, or ILI.� Pipe-depth environmental conditions were monitored continuously for periods of up to 2 years using the permanent NOVAProbe, which is capable of measuring the local redox potential, soil resistivity, pH and temperature close to the pipe surface.� Corrosion coupons were also installed at some sites to monitor the CP conditions and native potential.� In addition, various other information was collected for each site, including pipe information; soil, groundwater, coating, and corrosion product samples; topography and land use; precipitation data; soil gas samples; SCADA pressure data; corrosion and SCC ILI information; CIS data; gas temperature (for high-pH SCC sites); and information about the nature of the SCC.� All sites studied were on gas transmission pipelines in Canada.

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Gungor, Osman, Imad Al-Qadi, and Navneet Garg. Pavement Data Analytics for Collected Sensor Data. Illinois Center for Transportation, October 2021. http://dx.doi.org/10.36501/0197-9191/21-034.

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The Federal Aviation Administration instrumented four concrete slabs of a taxiway at the John F. Kennedy International Airport to collect pavement responses under aircraft and environmental loading. The study started with developing preprocessing scripts to organize, structure, and clean the collected data. As a result of the preprocessing step, the data became easier and more intuitive for pavement engineers and researchers to transform and process. After the data were cleaned and organized, they were used to develop two prediction models. The first prediction model employs a Bayesian calibration framework to estimate the unknown material parameters of the concrete pavement. Additionally, the posterior distributions resulting from the calibration process served as a sensitivity analysis by reporting the significance of each parameter for temperature distribution. The second prediction model utilized a machine-learning (ML) algorithm to predict pavement responses under aircraft and environmental loadings. The results demonstrated that ML can predict the responses with high accuracy at a low computational cost. This project highlighted the potential of using ML for future pavement design guidelines as more instrumentation data from future projects are collected to incorporate various material properties and pavement structures.

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Bajwa, Abdullah, and Timothy Jacobs. PR-457-17201-R01 Residual Gas Fraction Estimation Based on Measured In-Cylinder Pressure. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), September 2018. http://dx.doi.org/10.55274/r0011519.

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Developing a reliable means of predicting and controlling engine operation at various operating conditions may be a reasonable pathway for meeting increasingly stringent engine emission regulations. In order to do so, estimates of the mixture composition at the end of the gas exchange process (i.e. at exhaust port closure, or EPC) are helpful for having accurate models of engine combustion. A substantial fraction of the trapped charge mixture is composed of residual gases from previous cycles. This fraction, the trapped residual fraction, changes combustion characteristics of the trapped mixture. Residual gases dilute the fresh charge, thus decreasing the flame speed and temperature. Moreover, because of their spatial inhomogeneity, especially around the spark plug, these gases seem to have implications for engine stability. All these factors likely affect engine performance and emissions. Unfortunately, it is not practical to directly measure the trapped residual fraction for engines operating in the field. To overcome this, computational models can be developed for control applications which estimate this fraction based on some measurable engine parameters e.g. manifold pressures, temperatures, etc. Currently, such models aren't readily available for stationary two-stroke natural-gas engines. This report summarizes the results of phase I of a multi-phase project. In this phase a GT-Power based model was developed for an Ajax E-565 single-cylinder engine to study various factors that influence the removal, or lack thereof, of residual gases from the engine cylinder. The model was used to successfully simulate various engine operating conditions and study the scavenging characteristics of the engine. Various steps followed in the development of the model have been discussed in the report, and at the end some preliminary results and recommendations for the next phase of the project have been presented.

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George and Hawley. PR-015-09605-R01 Extended Low Flow Range Metering. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), December 2010. http://dx.doi.org/10.55274/r0010728.

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Natural gas meters are often used to measure flows below their minimum design flow rate. This can occur because of inaccurate flow projections, widely varying flow rates in the line, a lack of personnel available to change orifice plates, and other causes. The use of meters outside their design ranges can result in significant measurement errors. The objectives of this project were to examine parameters that contribute to measurement error at flow rates below 10% of a meters capacity, determine the expected range of error at these flow rates, and establish methods to reduce measurement error in this range. The project began with a literature search of prior studies of orifice, turbine, and ultrasonic meters for background information on their performance in low flows. Two conditions affecting multiple meter types were identified for study. First, temperature measurement errors in low flows can influence the accuracy of all three meter types, though the effect of a given temperature error can differ among the meter types. Second, thermally stratified flows at low flow rates are known to cause measurement errors in ultrasonic meters that cannot compensate for the resulting flow profiles, and the literature suggested that these flows could also affect orifice plates and turbine meters. Several possible ways to improve temperature measurements in low flows were also identified for further study. Next, an analytical study focused on potential errors due to inaccurate temperature measurements. Numerical tools were used to model a pipeline with different thermowell and RTD geometries. The goals were to estimate temperature measurement errors under different low-flow conditions, and to identify approaches to minimize temperature and flow rate errors. Thermal conduction from the pipe wall to the thermowell caused the largest predicted bias in measured temperature, while stratified temperatures in the flow caused relatively little temperature bias. Thermally isolating the thermowell from the pipe wall, or using a bare RTD, can minimize temperature bias, but are not usually practical approaches. Insulation of the meter run and the use of a finned thermowell design were practical methods predicted to potentially improve measurement accuracy, and were chosen for testing.

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