A creep model for ultra-deep salt rock considering thermal-mechanical damage under triaxial stress conditions

To investigate the specific creep behavior of ultra-deep buried salt during oil and gas exploitation,a set of triaxial creep experiments was conducted at elevated temperatures with constant axial pressure and unloading confining pressure conditions.Experimental results show that the salt sample deforms more significantly with the increase of applied temperature and deviatoric loading.The accelerated creep phase is not occurring until the applied temperature reaches 130℃,and higher temperature is beneficial to the occurrence of accelerated creep.To describe the specific creep behavior,a novel three-dimensional(3D)creep constitutive model is developed that incorporates the thermal and mechanical variables into mechanical elements.Subsequently,the standard particle swarm optimization(SPSO)method is adopted to fit the experimental data,and the sensibility of key model parameters is analyzed to further illustrate the model function.As a result,the model can accurately predict the creep behavior of salt under the coupled thermo-mechanical effect in deep-buried condition.Based on the research results,the creep mechanical behavior of wellbore shrinkage is predicted in deep drilling projects crossing salt layer,which has practical implications for deep rock mechanics problems.

Modification of streamer-to-leader transition model based on radial thermal expansion in the sphere-plane gap discharge at high altitude

Historically,streamer-to-leader transition studies mainly focused on the rod-plane gap and low altitude analysis,with limited attention paid to the sphere-plane gap at high altitude analysis.In this work,sphere-plane gap discharge tests were carried out under the gap distance of 5 m at the Qinghai Ultra High Voltage(UHV)test base at an altitude of 2200 m.The experiments measured the physical parameters such as the discharge current,electric field intensity and instantaneous optical power.The duration of the dark period and the critical charge of streamer-toleader transition were obtained at high altitude.Based on radial thermal expansion of the streamer stem,we established a modified streamer-to-leader transition model of the sphere-plane gap discharge at high altitude,and calculated the stem temperature,stem radii and the duration of streamer-to-leader transition.Compared with the measured duration of sphere-plane electrode discharge at an altitude of 2200 m,the error rate of the modified model was 0.94%,while the classical model was 6.97%,demonstrating the effectiveness of the modified model.From the comparisons and analysis,several suggestions are proposed to improve the numerical model for further quantitative investigations of the leader inception.

Identification of thermal front dynamics in the northern Malacca Strait using ROMS 3D-model

The thermal front in the oceanic system is believed to have a significant effect on biological activity.During an era of climate change,changes in heat regulation between the atmosphere and oceanic interior can alter the characteristics of this important feature.Using the simulation results of the 3D Regional Ocean Modelling System(ROMS),we identified the location of thermal fronts and determined their dynamic variability in the area between the southern Andaman Sea and northern Malacca Strait.The Single Image Edge Detection(SIED)algorithm was used to detect the thermal front from model-derived temperature.Results show that a thermal front occurred every year from 2002 to 2012 with the temperature gradient at the location of the front was 0.3°C/km.Compared to the years affected by El Ni?o and negative Indian Ocean Dipole(IOD),the normal years(e.g.,May 2003)show the presence of the thermal front at every selected depth(10,25,50,and 75 m),whereas El Ni?o and negative IOD during 2010 show the presence of the thermal front only at depth of 75 m due to greater warming,leading to the thermocline deepening and enhanced stratification.During May 2003,the thermal front was separated by cooler SST in the southern Andaman Sea and warmer SST in the northern Malacca Strait.The higher SST in the northern Malacca Strait was believed due to the besieged Malacca Strait,which trapped the heat and make it difficult to release while higher chlorophyll a in Malacca Strait is due to the freshwater conduit from nearby rivers(Klang,Langat,Perak,and Selangor).Furthermore,compared to the southern Andaman Sea,the chlorophyll a in the northern Malacca Strait is easier to reach the surface area due to the shallower thermocline,which allows nutrients in the area to reach the surface faster.

Multi-scale Modeling and Finite Element Analyses of Thermal Conductivity of 3D C/SiC Composites Fabricating by Flexible-Oriented Woven Process

Thermal conductivity is one of the most significant criterion of three-dimensional carbon fiber-reinforced SiC matrix composites(3D C/SiC).Represent volume element(RVE)models of microscale,void/matrix and mesoscale proposed in this work are used to simulate the thermal conductivity behaviors of the 3D C/SiC composites.An entirely new process is introduced to weave the preform with three-dimensional orthogonal architecture.The 3D steady-state analysis step is created for assessing the thermal conductivity behaviors of the composites by applying periodic temperature boundary conditions.Three RVE models of cuboid,hexagonal and fiber random distribution are respectively developed to comparatively study the influence of fiber package pattern on the thermal conductivities at the microscale.Besides,the effect of void morphology on the thermal conductivity of the matrix is analyzed by the void/matrix models.The prediction results at the mesoscale correspond closely to the experimental values.The effect of the porosities and fiber volume fractions on the thermal conductivities is also taken into consideration.The multi-scale models mentioned in this paper can be used to predict the thermal conductivity behaviors of other composites with complex structures.

Theoretical study on the effective thermal conductivity of silica aerogels based on a cross-aligned and cubic pore model

Aerogel nanoporous materials possess high porosity, high specific surface area, and extremely low density due to their unique nanoscale network structure. Moreover, their effective thermal conductivity is very low, making them a new type of lightweight and highly efficient nanoscale super-insulating material. However, prediction of their effective thermal conductivity is challenging due to their uneven pore size distribution. To investigate the internal heat transfer mechanism of aerogel nanoporous materials, this study constructed a cross-aligned and cubic pore model(CACPM) based on the actual pore arrangement of SiO_(2) aerogel. Based on the established CACPM, the effective thermal conductivity expression for the aerogel was derived by simultaneously considering gas-phase heat conduction, solid-phase heat conduction, and radiative heat transfer. The derived expression was then compared with available experimental data and the Wei structure model. The results indicate that, according to the model established in this study for the derived thermal conductivity formula of silica aerogel, for powdery silica aerogel under the conditions of T = 298 K, a_(2)= 0.85, D_(1)= 90 μm, ρ = 128 kg/m^(3), within the pressure range of 0–10^(5)Pa, the average deviation between the calculated values and experimental values is 10.51%. In the pressure range of 10^(3)–10^(4)Pa, the deviation between calculated values and experimental values is within 4%. Under these conditions, the model has certain reference value in engineering verification. This study also makes a certain contribution to the research of aerogel thermal conductivity heat transfer models and calculation formulae.

Lumped-Parameter Thermal Network Model and Experimental Research of Interior PMSM for Electric Vehicle

A 25kW interior permanent magnet synchronous machine(IPMSM)applied to the electric vehicle is introduced in the paper.A lumped-parameter thermal network model is presented for IPMSM temperature rise calculation.Furthermore,a 3D liquid-solid coupling model considering the assembly clearance is compared with the 2D lumped-parameter thermal network model.Finally,a dynamometer platform for temperature rise measurement is established to verify the above-mentioned methods,which obtains the measured efficiency map at rated load case and overload case.At the same time,the measured no-load back electromotive Force(EMF),load line input voltage and load current are gathered.Thermocouple PTC100 is used to measure the temperature of the stator winding and iron core,and the FLUKE infrared thermal imager is applied to measure the surface temperature of PMSM and controller.Testing result shows that the lumped-parameter thermal network have a high accuracy to predict each part temperature.

Novel models for simulating maize growth based on thermal time and photothermal units: Applications under various mulching practices

Maize (Zea mays L.) is one of the three major food crops and an important source of carbohydrates for maintaining food security around the world.Plant height (H),stem diameter (SD),leaf area index (LAI) and dry matter (DM) are important growth parameters that influence maize production.However,the combined effect of temperature and light on maize growth is rarely considered in crop growth models.Ten maize growth models based on the modified logistic growth equation (Mlog) and the Mitscherlich growth equation (Mit) were proposed to simulate the H,SD,LAI and DM of maize under different mulching practices based on experimental data from 2015–2018.Either the accumulative growing degree-days (AGDD),helio thermal units (HTU),photothermal units (PTU) or photoperiod thermal units (PPTU,first proposed here) was used as a single driving factor in the models;or AGDD was combined with either accumulative actual solar hours (ASS),accumulative photoperiod response (APR,first proposed here) or accumulative maximum possible sunshine hours (ADL) as the dual driving factors in the models.The model performances were evaluated using seven statistical indicators and a global performance index.The results showed that the three mulching practices significantly increased the maize growth rates and the maximum values of the growth curves compared with non-mulching.Among the four single factor-driven models,the overall performance of the Mlog_(PTU)Model was the best,followed by the Mlog_(AGDD)Model.The Mlog_(PPTU)Model was better than the Mlog_(AGDD)Model in simulating SD and LAI.Among the 10 models,the overall performance of the Mlog_(AGDD–APR)Model was the best,followed by the Mlog_(AGDD–ASS)Model.Specifically,the Mlog_(AGDD–APR)Model performed the best in simulating H and LAI,while the Mlog_(AGDD–ADL)and Mlog_(AGDD–ASS)models performed the best in simulating SD and DM,respectively.In conclusion,the modified logistic growth equations with AGDD and either APR,ASS or ADL as the dual driving factors outperformed the commonly used modified logistic growth model with AGDD as a single driving factor in simulating maize growth.

Deterioration of equivalent thermal conductivity of granite subjected to heating-cooling treatment

Understanding the thermal conductivity of granite is critical for many geological and deep engineering applications.The heated granite was subjected to air-,water-,and liquid nitrogen(LN2-)coolings in this context.The transient hot-wire technique was used to determine the equivalent thermal conductivity(ETC)of the granite before and after treatment.The deterioration mechanism of ETC is analyzed from the meso-perspective.Finally,the numerical model is used to quantitatively study the impact of cooling rate on the microcrack propagation and heat conduction characteristics of granite.The results show that the ETC of granite is not only related to the heating temperature,but also affected by the cooling rate.The ETC of granite decreases nonlinearly with increasing heating temperature.A faster cooling rate causes a greater decrease in ETC at the same heating temperature.The higher the heating temperature,the stronger the influence of cooling rate on ETC.The main explanation for the decrease in ETC of granite is the increase in porosity and microcrack density produced by the formation and propagation of pore structure and microcracks during heating and cooling.Further analysis displays that the damage of granite at the heating stage is induced by the difference in thermal expansion and elastic properties of mineral particles.At the cooling stage,the faster cooling rate causes a higher temperature gradient,which in turn produces greater thermal stress.As a result,it not only causes new cracks in the granite,but also aggravates the damage at the heating stage,which induces a further decrease in the heat conduction performance of granite,and this scenario is more obvious at higher temperatures.

A Prediction Model of Effective Thermal Conductivity for Metal Powder Bed in Additive Manufacturing

In current research,many researchers propose analytical expressions for calculating the packing structure of spherical particles such as DN Model,Compact Model and NLS criterion et al.However,there is still a question that has not been well explained yet.That is:What is the core factors affecting the thermal conductivity of particles?In this paper,based on the coupled discrete element-finite difference(DE-FD)method and spherical aluminum powder,the relationship between the parameters and the thermal conductivity of the powder(ETC_(p))is studied.It is found that the key factor that can described the change trend of ETC_(p) more accurately is not the materials of the powder but the average contact area between particles(a_(ave))which also have a close nonlinear relationship with the average particle size d_(50).Based on this results,the expression for calculating the ETC_(p) of the sphere metal powder is successfully reduced to only one main parameter d_(50)and an efficient calculation model is proposed which can applicate both in room and high temperature and the corresponding error is less than 20.9%in room temperature.Therefore,in this study,based on the core factors analyzation,a fast calculation model of ETC_(p) is proposed,which has a certain guiding significance in the field of thermal field simulation.

Ensemble Model for Spindle Thermal Displacement Prediction of Machine Tools

Numerous factors affect the increased temperature of a machine tool, including prolonged and high-intensity usage,tool-workpiece interaction, mechanical friction, and elevated ambient temperatures, among others. Consequently,spindle thermal displacement occurs, and machining precision suffers. To prevent the errors caused by thetemperature rise of the Spindle fromaffecting the accuracy during themachining process, typically, the factory willwarm up themachine before themanufacturing process.However, if there is noway to understand the tool spindle’sthermal deformation, the machining quality will be greatly affected. In order to solve the above problem, thisstudy aims to predict the thermal displacement of the machine tool by using intelligent algorithms. In the practicalapplication, only a few temperature sensors are used to input the information into the prediction model for realtimethermal displacement prediction. This approach has greatly improved the quality of tool processing.However,each algorithm has different performances in different environments. In this study, an ensemble model is used tointegrate Long Short-TermMemory (LSTM) with Support VectorMachine (SVM). The experimental results showthat the prediction performance of LSTM-SVM is higher than that of other machine learning algorithms.

Thermo-hydro-mechanical (THM) coupled simulation of the land subsidence due to aquifer thermal energy storage (ATES) system in soft soils

Aquifer thermal energy storage(ATES)system has received attention for heating or cooling buildings.However,it is well known that land subsidence becomes a major environmental concern for ATES projects.Yet,the effect of temperature on land subsidence has received practically no attention in the past.This paper presents a thermo-hydro-mechanical(THM)coupled numerical study on an ATES system in Shanghai,China.Four water wells were installed for seasonal heating and cooling of an agriculture greenhouse.The target aquifer at a depth of 74e104.5 m consisted of alternating layers of sand and silty sand and was covered with clay.Groundwater level,temperature,and land subsidence data from 2015 to 2017 were collected using field monitoring instruments.Constrained by data,we constructed a field scale three-dimensional(3D)model using TOUGH(Transport of Unsaturated Groundwater and Heat)and FLAC3D(Fast Lagrangian Analysis of Continua)equipped with a thermo-elastoplastic constitutive model.The effectiveness of the numerical model was validated by field data.The model was used to reproduce groundwater flow,heat transfer,and mechanical responses in porous media over three years and capture the thermo-and pressure-induced land subsidence.The results show that the maximum thermoinduced land subsidence accounts for about 60%of the total subsidence.The thermo-induced subsidence is slightly greater in winter than that in summer,and more pronounced near the cold well area than the hot well area.This study provides some valuable guidelines for controlling land subsidence caused by ATES systems installed in soft soils.

Entanglement and thermalization in the extended Bose–Hubbard model after a quantum quench: A correlation analysis

Exploring the role of entanglement in quantum nonequilibrium dynamics is important to understand the mechanism of thermalization in an isolated system. We study the relaxation dynamics in a one-dimensional extended Bose–Hubbard model after a global interaction quench by considering several observables: the local Boson numbers, the nonlocal entanglement entropy, and the momentum distribution functions. We calculate the thermalization fidelity for different quench parameters and different sizes of subsystems, and the results show that the degree of thermalization is affected by the distance from the integrable point and the size of the subsystem. We employ the Pearson coefficient as the measurement of the correlation between the entanglement entropy and thermalization fidelity, and a strong correlation is demonstrated for the quenched system.

Establishment and Optimization of Ablation Surrogate Model for Thermal Protection Material

The temperature response calculation of thermal protection materials,especially ablative thermal protection materials,usually adopts the ablation model,which is complicated in process and requires a large amount of calculation.Especially in the process of optimization calculation and parameter identification,the ablation model needs to be called many times,so it is necessary to construct an ablation surrogate model to improve the computational efficiency under the premise of ensuring the accuracy.In this paper,the Gaussian process model method is used to construct a thermal protection material ablation surrogate model,and the prediction accuracy of the surrogate model is improved through optimization.

Thermal Study and Modeling of the Cold Room of a Solar Adsoption Refrigerator

In this work, we are interested in the study of the thermal exchanges which take place at the evaporator of an adsorption refrigerator. Due to the cost of designing experimental devices and the impossibility of studying the influence of certain parameters experimentally, an alternative would be simulation. The aim is to provide a model for predicting the thermal behavior of the various elements in the cold room of an adsorption solar refrigerator. A dynamic modelling of the refrigerator taking into account fluid flow, heat and mass transfer phenomena in the cold room was made. The calculation code obtained using COMSOL 5.1 software makes it possible to analyze and study the influence of the various parameters on the performance of the system. In a second step, the theoretical results obtained were compared with the experimental results in order to validate the model. The analysis of the influence of the physical-thermal properties of the insulating material on the temperature of the chamber makes it possible to conclude that a material having a low density ρ, a low thermal conductivity λ and a low specific heat capacity offers better performance to the cold room. Better thermal insulation also implies having a reasonable insulation thickness.

Modelling of internal ballistics of gun systems:A review

A deep understanding of the internal ballistic process and the factors affecting it is of primary importance to efficiently design a gun system and ensure its safe management. One of the main goals of internal ballistics is to estimate the gas pressure into the combustion chamber and the projectile muzzle velocity in order to use the propellant to its higher efficiency while avoiding over-pressure phenomena. Dealing with the internal ballistic problem is a complex undertaking since it requires handling the interaction between different constituents during a transient time lapse with very steep rise of pressure and temperature. Several approaches have been proposed in the literature, based on different assumptions and techniques. Generally, depending on the used mathematical framework, they can be classified into two categories: computational fluid dynamics-based models and lumped-parameter ones. By focusing on gun systems, this paper offers a review of the main contributions in the field by mentioning their advantages and drawbacks. An insight into the limitations of the currently available modelling strategies is provided,as well as some considerations on the choice of one model over another. Lumped-parameter models, for example, are a good candidate for performing parametric analysis and optimisation processes of gun systems, given their minimum requirements of computer resources. Conversely, CFD-based models have a better capacity to address more sophisticated phenomena like pressure waves and turbulent flow effects. The performed review also reveals that too little attention has been given to small calibre guns since the majority of currently available models are conceived for medium and large calibre gun systems.Similarly, aspects like wear phenomena, bore deformations or projectile-barrel interactions still need to be adequately addressed and our suggestion is to dedicate more effort on it.

Operation optimization of prefabricated light modular radiant heating system:Thermal resistance analysis and numerical study

The utilization of prefabricated light modular radiant heating system has demonstrated significant increases in heat transfer efficiency and energy conservation capabilities.Within prefabricated building construction,this new heating method presents an opportunity for the development of comprehensive facilities.The parameters for evaluating the effectiveness of such a system are the upper surface layer’s heat flux and temperature.In this paper,thermal resistance analysis calculation based on a simplified model for this unique radiant heating system analysis is presented with the heat transfer mechanism’s evaluation.The results obtained from thermal resistance analysis calculation and numerical simulation indicate that the thermal resistance analysis method is highly accurate with temperature discrepancies ranging from 0.44℃ to−0.44℃ and a heat flux discrepancy of less than 7.54%,which can meet the requirements of practical engineering applications,suggesting a foundation for the prefabricated radiant heating system.

LUMPED-PARAMETER MODEL OF MASS TRANSFER IN HEMODIALYZER WITH ULTRAFILTRATION

1 INTRODUCTIONHemodialysis with ultrafiltration,also called hemodiafiltration(HDF),is a main methodof treatment for patients with chronic renal failure.The HDF procedure providesadequate removals of both small and middle molecular weight toxic substamces fromuremic blood,which is not possible by dialysis or ultrafiltration alone.According toclinical experience[1],the HDF procedure is well accepied by the patients,and thetreatment time is reduced by using it.

Radiative heat transfer analysis of a concave porous fin under the local thermal non-equilibrium condition:application of the clique polynomial method and physics-informed neural networks

The heat transfer through a concave permeable fin is analyzed by the local thermal non-equilibrium(LTNE)model.The governing dimensional temperature equations for the solid and fluid phases of the porous extended surface are modeled,and then are nondimensionalized by suitable dimensionless terms.Further,the obtained nondimensional equations are solved by the clique polynomial method(CPM).The effects of several dimensionless parameters on the fin's thermal profiles are shown by graphical illustrations.Additionally,the current study implements deep neural structures to solve physics-governed coupled equations,and the best-suited hyperparameters are attained by comparison with various network combinations.The results of the CPM and physicsinformed neural network(PINN)exhibit good agreement,signifying that both methods effectively solve the thermal modeling problem.

A thermal stress loading technique for large-sized hot dry rock mechanical tests

Testing of large-sized specimens is becoming increasingly important in deep underground rock mechanics and engineering.In traditional mechanical loading,stresses on large-sized specimens are achieved by large host frames and hydraulic pumps,which could lead to great investment.Low-cost testing machines clearly always have great appeal.In this study,a new approach is proposed using thermal expansion stress to load rock specimens,which may be particularly suitable for tests of deep hot dry rock with high temperatures.This is a different technical route from traditional mechanical loading through hydraulic pressure.For the rock mechanics test system of hot dry rock that already has an investment in heating systems,this technology may reduce the cost of the loading subsystem by fully utilizing the temperature changes.This paper presents the basic principle and a typical design of this technical solution.Preliminary feasibility analysis is then conducted based on numerical simulations.Although some technical details still need to be resolved,the feasibility of this loading approach has been preliminarily confirmed.

Numerical Investigation of Thermal Behavior of CNC Machine Tool and Its Effects on Dimensional Accuracy of Machined Parts

The dimensional accuracy of machined parts is strongly influenced by the thermal behavior of machine tools (MT). Minimizing this influence represents a key objective for any modern manufacturing industry. Thermally induced positioning error compensation remains the most effective and practical method in this context. However, the efficiency of the compensation process depends on the quality of the model used to predict the thermal errors. The model should consistently reflect the relationships between temperature distribution in the MT structure and thermally induced positioning errors. A judicious choice of the number and location of temperature sensitive points to represent heat distribution is a key factor for robust thermal error modeling. Therefore, in this paper, the temperature sensitive points are selected following a structured thermomechanical analysis carried out to evaluate the effects of various temperature gradients on MT structure deformation intensity. The MT thermal behavior is first modeled using finite element method and validated by various experimentally measured temperature fields using temperature sensors and thermal imaging. MT Thermal behavior validation shows a maximum error of less than 10% when comparing the numerical estimations with the experimental results even under changing operation conditions. The numerical model is used through several series of simulations carried out using varied working condition to explore possible relationships between temperature distribution and thermal deformation characteristics to select the most appropriate temperature sensitive points that will be considered for building an empirical prediction model for thermal errors as function of MT thermal state. Validation tests achieved using an artificial neural network based simplified model confirmed the efficiency of the proposed temperature sensitive points allowing the prediction of the thermally induced errors with an accuracy greater than 90%.