Physical Modeling Method Research Articles

A hybrid physical modeling and AUKF approach for optimizing low-temperature charging of lithium-ion batteries

A common method for charging lithium-ion batteries at low temperatures involves preheating to mitigate low charging efficiency and safety risks from lithium dendrite growth. However, preheating alone is insufficient for rapid and safe charging. Optimization of low temperature charging requires consideration of the coupling relationship between heating and charging processes, while avoid lithium plating. Therefore, this study first constructs an electrochemical-thermal coupled model suitable for a broad temperature range to access the internal states of battery during low-temperature charging, ensuring lithium plating-free. Then, a hybrid physical modeling and AUKF method is proposed to accurately capture the changing state of charge (SOC) and state of temperature (SOT) during low-temperature charging, which is essential to improve the simulation accuracy of the model. After that, this study proposes a multi-stage heating-charging strategy which is controlled by hybrid physical modeling and AUKF approach to consider charging efficiency and safety. Optimization algorithm is used to obtain the optimal sequence of decisions for charging and heating under different phases to achieve the highest charging efficiency. Compared to One-stage heating-charging strategy, the proposed method offers superior charging efficiency, providing certain convenience for the operation of lithium-ion batteries in low temperature environment.

Frontiers in attributing climate extremes and associated impacts

The field of extreme event attribution (EEA) has rapidly developed over the last two decades. Various methods have been developed and implemented, physical modelling capabilities have generally improved, the field of impact attribution has emerged, and assessments serve as a popular communication tool for conveying how climate change is influencing weather and climate events in the lived experience. However, a number of non-trivial challenges still remain that must be addressed by the community to secure further advancement of the field whilst ensuring scientific rigour and the appropriate use of attribution findings by stakeholders and associated applications. As part of a concept series commissioned by the World Climate Research Programme, this article discusses contemporary developments and challenges over six key domains relevant to EEA, and provides recommendations of where focus in the EEA field should be concentrated over the coming decade. These six domains are: (1) observations in the context of EEA; (2) extreme event definitions; (3) statistical methods; (4) physical modelling methods; (5) impact attribution; and (6) communication. Broadly, recommendations call for increased EEA assessments and capacity building, particularly for more vulnerable regions; contemporary guidelines for assessing the suitability of physical climate models; establishing best-practice methodologies for EEA on compound and record-shattering extremes; co-ordinated interdisciplinary engagement to develop scaffolding for impact attribution assessments and their suitability for use in broader applications; and increased and ongoing investment in EEA communication. To address these recommendations requires significant developments in multiple fields that either underpin (e.g., observations and monitoring; climate modelling) or are closely related to (e.g., compound and record-shattering events; climate impacts) EEA, as well as working consistently with experts outside of attribution and climate science more generally. However, if approached with investment, dedication, and coordination, tackling these challenges over the next decade will ensure robust EEA analysis, with tangible benefits to the broader global community.

Load-bearing behaviors of the composite gravity-type anchorage: Insights from physical model and numerical tests

Gravity-type anchorages (GTAs) have been extensively applied in large-span suspension bridges across the globe, but the load-bearing performance of composite GTA is not yet fully investigated. Here, the comprehensive load-bearing performance of GTA is investigated using a combination of physical modelling and numerical modelling methods, considering the impact of anchorage’s burial depth, notched sill, and pile. Six model tests are first conducted using a self-reversing force loading equipment, including flat bottom anchorage, notched sill anchorage, and notched sill anchorage with pile. Each type of anchorage is tested under two different burial depth conditions. The failure process, anchorage displacement, cable tension force, and the internal strain field of the foundation, were examined during the model tests. Additionally, through the numerical simulations, the evolution characteristics of contact stresses and load sharing ratio associated with various forms of anchorage are discussed. The results indicate that the anchorage’s burial depth and pile significantly impact on anchorage’s bearing capacity. The presence of the notched sill can change the distribution of contact stress between the anchorage and foundation, which can still resist the horizontal force until the foundation before the notched sill occurs shear failure. The failure process of the anchorage-foundation system was divided into four stages: stable bearing, sliding, sliding and overturning, and failure stage. The anchorage starts overturning with the applied load reaching to 3*Tm, except for the flat bottom anchorage of shallow burial depth condition. Under the same conditions, the greater the anchorage’s burial depth, the smaller the load shared by the friction between the anchorage bottom and foundation, the greater the load shared by the notched sill and foundation before the anchorage. In addition, the load shared by pile continuously increasing as the anchorage starts overturning. The findings from this study can provide a theoretical basis and valuable insights for the optimization design of GTA.

Analysis of torsional properties of a rubber rope as a composite material in multilayer winding

Purpose. The main purpose of this study is to analyse the results of a theoretical study on the effect of the longitudinal stiffness of the rope on the mechanism of deformation of the winding body as a composite material on the basis of experimental data. The methods. The methodology is based on the analysis of scientific papers by leading experts in the field of mechanical engineering specialising in the development of hoisting machines with rubber-rope cables. The development of the model of torsional stiffness of the winding body of reel hoists was based on mathematical and physical modelling methods, including methods of planning a multifactorial experiment and statistical processing of experimental data. Findings. When solving the problem of determining the stiffness of the body of a rubber-rope winding, the physical model of its spool body was presented in the form of a rubber-metal hinge. After processing the results of the experiment to determine the parameters of the winding body, an analytical expression was obtained to calculate the torsional stiffness of the winding body of a rubber-rope cable. The originality. The regularities of the influence of the parameters of a rubber rope on the torsional stiffness of its winding body have been established. The stiffness of the winding body depends on its outer diameter quadratically, while the local stiffness is weak. With a small number of turns, the stiffness of the homogeneous body exceeds the local stiffness, but the total pliability is low. The risk of dynamic effects in a spool hoist during braking increases with a large number of turns, when the homogeneous body stiffness is much lower than the local stiffness. The total torsional stiffness of the winding body can be determined by the proposed formula with sufficient accuracy for dynamic analysis. Practical implementation. The developed mathematical model for determining the torsional stiffness of a rubber rope winding makes it possible to find such values of the parameters of a spool hoist that will avoid the danger of dynamic effects during emergency and operational braking of the device caused by the torsional stiffness of the winding body.

Study of rock fracture patterns for obtaining the basis for energy-efficient ore ball milling

The study is conducted using methods of analysis (in proving the possibility of assessing the disintegration of rocks by energy consumption), methods of free vibration theory (to determine the motion of a falling ball over an elastic connection), methods of energy balance, methods of theoretical mechanics and material resistance (to study amplitude characteristics of mechanical systems), methods of rock fracture theory (to determine fracture work), physical modeling (to design test benches) and experimental methods (to find relationships between parameters). The strength of bulk crushed material in the first stages of ore preparation is practically independent of its coarseness and solid form, which allows the estimated volume of disintegrated ore (particle concentration) to be determined by the energy expended, translated into other physical quantities. Results of experimental studies support the theoretical dependences. The proposed approach of automatic stabilisation of solid concentration in the ball mill pulp at the optimum level allows to increase the productivity of ore preparation on the finished grade in the first stages by 10% at reduction of specific power consumption for ore grinding.

ПОРІВНЯЛЬНИЙ АНАЛІЗ МЕТОДІВ МОДЕЛЮВАННЯ МЕТАЛУРГІЙНИХ ПРОЦЕСІВ

In modern conditions, modeling of technological processes is one of the most promising methods of conducting research on industrial facilities, which is characterized by a low cost compared to conducting research on real metallurgical units. Modeling, as a research method, is based on the reproduction of a real technological process in a smaller volume, in comparison with a real technological process while observing the scale of similarity. In the global practice of researching metallurgical processes, the following methods of modeling technological processes are used: mathematical modeling; low-temperature physical modeling; high-temperature physical modeling. When studying the metallurgical processes of the steelmaking direction, the most complete data is provided by high-temperature physical modeling. At the same time, it allows to study both permanent technological processes and innovative ones. As for the methods of low-temperature physical modeling, they are somewhat limited in the context of informativeness, but they differ in their low cost. Mathematical modeling is promising for modeling established technological processes and needs some clarification with practical data. An urgent task for modern metallurgical science is the development of methods for increasing the accuracy of the results of low-temperature modeling and bringing them closer to high-temperature modeling while maintaining an acceptable cost of modeling.

Integrating physical model and image simulations to correct topographic effects on surface reflectance

Topography complicates the illumination distribution over rugged terrains and hinders the applications of surface reflectance data over mountainous areas. Topographic correction is an essential process to remove the topographic effects in surface reflectance data. This study proposed a Physical model and image Simulation-based topographic Correction method (PSC) for atmospherically corrected surface reflectance images. In contrast with traditional methods, the proposed approach explicitly estimates the illumination distribution over rugged terrains based on image information and then corrects the topographic effects following physical laws. The proposed method was validated and compared with existing well-performed topographic correction methods, including path length correction (PLC), sun-canopy-sensor correction with c factor (SCSC), C correction (CC), and statistical empirical correction (SE). Simulated and satellite data obtained at different times and geolocations are used for evaluation and comparison. The results demonstrated that most existing methods face challenges in removing the biases induced by topography in surface reflectance images. The PLC method failed to obtain reasonable results for faint illumination conditions when the sun zenith angle is high. SE showed relatively poor performance in terms of physical consistency and outlier percentage. Besides, all the traditional methods failed in the correction of cast shadow regions. Comparably, our method consistently demonstrated superior performance in physical consistency, cast shadow correction, and outlier percentage across various regions, encompassing different sun zenith angles and illumination conditions. The proposed method offers an effective and physically consistent approach for the topographic correction of surface reflectance images, facilitating multi-temporal applications over mountainous areas.

A novel bilateral stream neural network for melt pool monitoring during laser direct energy deposition

Detection and classification methods for the melt pool state in laser direct energy deposition (L-DED) can significantly help predict defects and mechanical properties of L-DED metal parts. Although traditional machine learning algorithms based on physical modeling methods and convolutional neural networks have recently been introduced into melt pool state identification, these methods rely on complex artificially designed features or cannot simultaneously detect defects in multiple dimensions. In this paper, a novel bilateral stream neural network was designed for melt pool identification, which performs defect identification in two label dimensions simultaneously. Two sets of single-channel experiments were designed to collect the dataset captured by a high-speed camera. By cutting the metal parts and marking them with professional equipment operated by professionals, the dataset was labeled according to the bonding condition and dilution rate criteria. Without an additive model structure, the model achieved 95.2% accuracy in identifying defects in the bonding condition and 92.8% in determining deficiencies in the dilution rate. In order to explain the identification mechanism of the model, the CAM method was utilized for the visual display of the model recognition process, which provides a potential application solution for the online monitoring method of the L-DED.

Моделирование движения обвальной массы горной породы с использованием двухжидкостной математической модели

Introduction. Rock falls are considered to be very dangerous slope processes that can lead to serious consequences. In addition to real observations, numerical (mathematical) or experimental (physical) modeling methods are used to study slope processes. Mathematical modeling is used in the cases where experimental data is insufficient. There are quite a lot of models to describe slope processes. The choice of model to describe a particular slope process lies in the approach on which the model is based. In this work, the debris flow taking into account the fluidization of the collapse mass during its movement along the hillside was described. We used a two-fluid model based on the continuum approach and the kinetic theory of granular gas. The model takes into account the fluidization of the collapse mass, and its implementation does not require the use of powerful computing resources. Purpose of the study. Investigation of the collapse mass motion along a hillside using a two-fluid model based on continuum approach and kinetic theory of granular gas. Estimation of the maximum height of the collapse mass flow layer and the average flow velocity. Materials and methods. The two-fluid model based on the continuum approach and the kinetic theory of granular gas was used for theoretical study of the collapse mass flow. The motion of the collapse mass flow consisting of rock granules (average diameter 7.5 cm) along the hillside (slope angle of 30 degrees) was considered. The 3D simulation results obtained using the two-fluid model were compared with experimental data and calculated data obtained using the discrete element method. The results and discussion. Three-dimensional modeling was applied to study the motion of the collapse mass flow along the hillside using the two-fluid model. The obtained calculations of the maximum height of the flow layer and the average flow velocity are compared with experimental data and calculated data using the discrete element method. The comparison showed that the averaged value (obtained as the arithmetic mean) of the experimental data of the average flow velocity coincides with the result of calculations using the two-fluid model. And the average value of the calculated data using the discrete element method differs slightly from the calculated value using the two-fluid model. The paper proposes a method for calculating the maximum height of the flow layer using graphs of the distribution of the particles volume fraction along the normal to the inclined surface. Using this technique, the maximum value of the layer height was obtained. This value coincides with the maximum value obtained using the discrete element method and differs only slightly from the maximum value obtained in the experiments. Using the two-fluid model, additional calculations were carried out at different values of the slope angle in the range from 20 to 60 degrees. The calculation results of the maximum height of the flow layer and average flow velocity were compared with the calculated data obtained using a model based on the discrete element method. It was found that the calculation results obtained using two different models agree better with each other when the dependence of the average flow velocity on the slope angle is studied. Conclusion. In general, it can be concluded that the results of calculations of the maximum layer height and average flow velocity obtained using the two-fluid model are in fairly good agreement with experimental data and calculated data obtained using the discrete element method. It can also be concluded that the two-fluid model can be used to describe the motion of the flows of the collapse mass with a relatively low liquid content (up to 18 %) and fine inclusions (up to 27 %). Resume. The research results can be useful in estimating the maximum height of the flow layer of the collapse mass and the average flow velocity. The direction of future research is to improve the two-fluid model based on the continuum approach and the kinetic theory of granular gas for describing of real slope processes.

Physics-anchored masked autoencoder for efficient sonogram simulation

We present a technique for efficiently creating sonogram such as LOFAR and DEMON, by combining physical acoustic modeling and data-driven method of masked autoencoder. This technique involves two stages. First, in the given the ocean environment, the physical model accurately calculates a restricted portion of entire sonogram image. Next, the data-driven model based on masked autoencoder creates an image of remaining region. By employing an iterative decoding structure and controlling the weight of the physical loss term, the reconstruction accuracy of masked autoencoder is improved. The results are compared with those of a pure physical model, a hybrid model with original masked autoencoder, and a hybrid model with traditional PCA technique. We will discuss the practicality of the proposed technique in terms of accuracy and calculation performance, as well as the applicablity of real data using Deepship dataset. [Work supported by the Korea Research Institute for Defense Technology Planning and Advancement (KRIT) grant funded by the Korea government (Defense Acquisition Program Administration (DAPA)) (No. KRIT-CT-22-052, Physics-guided Intelligent Sonar Signal Detection Research Laboratory).]

A review on physics-informed data-driven remaining useful life prediction: Challenges and opportunities

Remaining useful life (RUL) prediction, known as ‘prognostics’, has long been recognized as one of the key technologies in prognostics and health management (PHM) to maintain the safety and reliability of the system, and reduce the operating and management costs. Particularly, thanks to great advances in sensing and condition monitoring techniques, data-driven RUL prediction has attracted much attention and various data-driven RUL prediction methods have been reported. Despite the extensive studies on data-driven RUL prediction methods, the successful applications of such methods depend heavily on the volume and quality of the data, and purely data-driven methods possibly generate physically infeasible/inconsistent RUL prediction results and have the limited generalizability and interpretability. It is noted that there is an increasing consensus that embedding the physics or the domain knowledge into the data-driven methods and developing physics-informed data-driven methods will hold promise to improve the interpretability and efficiency of the RUL prediction results and lower the requirement of the volume and quality of the data. In this context, physics-informed data-driven RUL prediction has become an emerging topic in the prognostics field. However, there has not been a systematic review particularly focused on this emerging topic. To fill this gap, this paper reviews recent developments of physics-informed data-driven RUL prediction methods. In this review, current methods fallen into this type are broadly divided into three categories, i.e. physical model and data fusion methods, stochastic degradation model based methods, and physics-informed machine learning (PIML) based methods. Particularly, this review is centered on the PIML based methods since the fast development of such methods have been witnessed in the past five years. Through discussing the pros and cons of existing methods, we provide discussions on challenges and possible opportunities to steer the future development of physics-informed data-driven RUL prediction methods.

Interpretable Lost Circulation Analysis: Labeled, Identified, and Analyzed Lost Circulation in Drilling Operations

Summary Lost circulation (LC) is a serious problem in drilling operations, as it increases nonproductive time and costs. It can occur due to various complex factors, such as geological parameters, drilling fluid properties, and operational drilling parameters, either individually or in combination. Therefore, studying the types, influencing factors, and causes of LC is crucial for effectively improving prevention and plugging techniques. Currently, the expert diagnosis of LC types relies heavily on the experience and judgment of experts, which may lead to inconsistencies and biases. Additionally, difficulties in obtaining data or missing important data can affect the efficiency and timeliness of diagnosis. Traditional physical modeling methods struggle to analyze complex factor correlations, and conventional machine learning techniques have limited interpretability. In this paper, we propose an interpretable lost circulation analysis (ILCA) framework that provides a new method for analyzing LC. First, we use Gaussian mixture model (GMM) clustering to analyze the LC characteristics of regional case data, efficiently and accurately labeling 296 LC events. Second, we establish the relationship between geological features, drilling fluid properties, operational drilling parameters, and LC types using the XGBoost algorithm. This enables timely identification of LC types during drilling operations using real-time data, with a precision greater than 85%. Finally, we use interpretable machine learning techniques to conduct a comprehensive quantitative analysis of influencing factors based on the established XGBoost model, providing a clear explanation for the identification model. This enables drilling engineers to gain deeper insights into the factors influencing LC events. In summary, the proposed ILCA framework is capable of efficiently labeling LC types based on regional case data, identifying LC types in a timely manner using real-time data, and conducting quantitative analysis of the factors and causes of LC. This approach addresses the limitations of traditional methods and offers valuable insights for drilling engineers.

Настройка функции временной регулировки чувствительности ультразвуковой аппаратуры по боковому цилиндрическому отражателю при диагностировании деталей подвижного состава

To increase the efficiency of the use of rolling stock, methods and means of technical diagnostics have been developed, which are used during maintenance and repairs, as well as an independent technological process. Diagnosis makes it possible to increase the availability coefficient, the probability of trouble-free operation, repair and control suitability of rolling stock, reduce the cost of its operation and the complexity of technological processes. The complex of test diagnostic measures includes operations of ultrasonic non-destructive testing of railway rolling stock parts and assemblies for the absence of internal unacceptable irregularities. Pulse-echo method, which refers to reflection methods, has become the most wide-spread among ultrasonic control methods. One of the most important operations in the process of ultrasonic testing is to adjust the sensitivity of ultrasonic equipment. The article focuses on the results of a study on the development of a non-etalon method for adjusting the function of temporary sensitivity ultrasonic equipment setting when diagnosing rolling stock parts, taking into account the attenuation of ultrasound along a lateral cylindrical reflector. To implement the method, a new mathematical apparatus has been developed, which is based on the key laws of physical acoustics, as well as the methods of mathematical and physical modeling. The non-standard adjustment of the temporary sensitivity setting function allows to get rid of the disadvantages when using tuning samples with artificial reflectors. A program NDTRT TSA SCR F-BCR has been developed to automate calculations when diagnosing railway rolling stock parts using the ultrasonic method and taking into account the attenuation of the ultrasonic wave along a lateral cylindrical reflector.

Physical modeling of the effect of refilling the melt into an ingot knock-off head on solidification and structure formation

The paper presents the results of a laboratory study of the effect of refilling the ingot knock-off head with melt in a certain time interval after pouring the ingot body on solidification and structure formation of the model ingot. The research was carried out by the method of physical (cold) modeling for which a laboratory installation (casting form-mold) was developed and manufactured. It allows visually studying the processes occurring during solidification and structure formation on a 19.6-ton model ingot. We used sodium sulfuric acid (crystalline hyposulfite) as a modeling solution. Correspondence of the processes occurring on the model and in real conditions of industrial ingots casting was evaluated using similarity criteria obtained on the basis of dimension theory with analysis of physico-chemical processes occurring during casting and crystallization of the ingot. Casting of the melt into the casting form-mold was downhill. In order to assess changes in the temperature field during casting and crystallization of the ingot in the entire solidification time, we performed thermometry of the mold model surface. Analysis of the conducted studies results showed that refilling the melt before 40 min leads to stimulation of early settling of crystals (“rain of crystals”), which contributes to an increase in the crystallization directivity in vertical direction. It was established that in a conventional ingot up to 40 min solidification proceeds by a sequential mechanism, and after that the crystals begin to settle (“rain of crystals”) and the solidification of the ingot passes through a volume-sequential mechanism. Refilling the ingot knock-off head with melt 40 min after pouring the ingot body contributed to the continuation of the sequential mechanism of ingot solidification, which led to the formation of a monolithic defect-free structure in the ingot body and the least development of shrinkage shell in the knock-off head. The results obtained make it possible to develop a technology for differentiated ingots casting when filling their knock-off heads with melt in a certain time interval after pouring the ingot body, which will affect the process of metal structure formation and reduce defective zones.

Experimental studies of the stability of wave-damping slopes to protect bridge supports from wave action

This article presents the results of experimental studies of the stability of wave-damping slopes to protect bridge supports from wave action. The object of the study is the construction of protective wave-damping slopes constructed to protect the supports of bridges designed and operated under wave action conditions (such as the bridge to Russian Island in Vladivostok, etc.) on the shores of the seas. The purpose of the work is to select the optimal design solutions for protective slopes that ensure reliable and safe operation of the bridge crossing during sea storms of rare frequency. The research was carried out by the method of physical modeling in a wave pool. Various variants of structural solutions of protective slopes are considered: from a stone outline and from gabions, as well as combined structures. According to the results of research on a physical model in the wave basin, the structures of the protective slopes of bridge supports that are most resistant to the effects of sea storm waves of rare frequency have been obtained. The results of the research are intended to select optimal design solutions for protecting bridge supports from wave action and can also be used to protect other transport structures, for example, the roadbed of railways designed on sea coasts. These results were used by the author in the development of the regulatory framework for the design and monitoring of engineering structures for the protection of transport structures from wave action.

An adaptive nonlinear simulation method for member buckling in lattice towers

To accurately simulate the force-deformation relationship of lattice tower members, this paper proposes an adaptive nonlinear simulation (ANS) method of member buckling behavior based on the physical model method. The proposed ANS method uses a combined buckling model (CBM) to simulate the plastic deformation behavior of tower members by integrating tension-compression and rotation springs, which has the advantages of clear physical meaning. Furthermore, to reduce the degrees of freedom of the entire structure significantly, an adaptive spring mechanism is introduced to adaptively add springs during the process of analysis based on the member stress state. Since the strong nonlinearity of the structure in the collapse process will lead to calculation instability, an adaptive implicit-explicit sequential solution scheme is incorporated into the framework of the proposed ANS method, which can ensure the calculation stability of the proposed method with higher efficiency. The proposed ANS method has been compared with ANSYS software and three full-scale tests of the lattice towers. The results show that the proposed ANS method can accurately predict the structural response, including the ultimate bearing capacity, failure location, and collapse process.

Mathematical model of the supporting structure of a finely-dispersing sprinkler installation

BACKGROUND: The paper considers the issue of creating a reliable system for protecting fruit plantations from adverse atmospheric phenomena, diseases, pests in mountain terrain, which can be solved with the use of artificial irrigation. To solve this issue, it is necessary to develop a supporting structure for a finely-dispersing sprinkler installation with sprayers attached to it, which make it possible to process fruit plantations from all sides simultaneously. At the same time, the design and technological parameters of the operation of the finely-dispersing sprinkler installation depend on ensuring the strength and stability of the supporting structure.
 AIMS: Development of the mathematical model of the supporting structure of the finely-dispersing sprinkler installation.
 METHODS: The methods of physical and mathematical modeling, the method of task-oriented enumeration of parameters (the Gemerling’s method) were used. The research object is the supporting structure of the finely-dispersing sprinkler installation. The verification of the operability of the supporting structure according to the criteria of strength and stability was carried out with a computer using the MATLAB software.
 RESULTS: An optimization problem has been solved for 4 variants of the layout of the supporting structure of the finely-dispersing sprinkler installation.
 CONCLUSIONS: Various options for the layout of the supporting structure of the finely-dispersing sprinkler installation have been obtained, ensuring the fulfillment of the conditions of stability and strength; technological requirements for the total length of the pipeline, for its internal diameter and for the number of nozzles; the requirements of the standard for the material and outer diameter of the pipeline.

Behavior of skirted foundations under vertical load by numerical and physical modeling methods

Behavior of skirted foundations under vertical load by numerical and physical modeling methods

Characterization of Tight Gas Sandstone Properties Based on Rock Physical Modeling and Seismic Inversion Methods

Tight sandstones produce an increasing amount of natural gas worldwide. Apart from identifying the gas enrichment, the predictions of lithology and permeable zones are crucial for the prediction of tight gas sandstones. In the present study, a seismic inversion method is developed based on rock physical modeling, by which it is possible to directly predict the lithology and pore structure in tight formations. The double-porosity model is used as a modeling tool in considering complex pore structures. Based on the model, the microfracture porosity is then predicted using logging data, which are used as a factor to estimate microfractures. Parameters representing the lithology and pore structure are proposed and estimated using logging data analyses and rock physical modeling based on the framework of the Poisson impedance. Thereafter, a new AVO equation is established and extended to the form of an elastic impedance for a direct prediction of the lithology and pore structure parameters. Real data applications show that the indicators of lithology and permeable zones are consistent with the production status. They agree with the petrophysical properties measured in wellbores, thereby proving the applicability of the proposed method for the effective characterization of tight gas sandstones.

Research on a Method for Online Damage Evaluation of Turbine Blades in a Gas Turbine Based on Operating Conditions

Performing online damage evaluation of blades subjected to complex cyclic loads based on the operating state of a gas turbine enables real-time reflection of a blade’s damage condition. This, in turn, facilitates the achievement of predictive maintenance objectives, enhancing the economic and operational stability of gas turbine operations. This study establishes a hybrid model for online damage evaluation of gas turbine blades based on their operational state. The model comprises a gas turbine performance model based on thermodynamic simulation, a component load calculation model based on a surrogate model, an updated cycle counting method based on four-point rainflow, and an improved damage mechanism evaluation model. In the new model, the use of a surrogate model for the estimation of blade loading information based on gas turbine operating parameters replaces the conventional physical modeling methods. This substitution enhances the accuracy of blade loading calculations while ensuring real-time performance. Additionally, the new model introduces an updated cycle counting method based on four-point rainflow and an improved damage mechanism evaluation model. In the temperature counting part, a characteristic stress that represents the stress information during the cyclic process is proposed. This inclusion allows for the consideration of the impact of stress fluctuations on creep damage, thereby enhancing the accuracy of the fatigue damage assessment. In the stress counting part, the model incorporates time information associated with each cycle. This concept is subsequently applied in determining the identified cyclic strain information, thereby improving the accuracy of the fatigue damage evaluation. Finally, this study applies the new model to an online damage evaluation of a turbine stationary blade using actual operating data from a micro gas turbine. The results obtained from the new model are compared with the EOH recommended by the OEM, validating the accuracy and applicability of the new model.