A method for establishing a bearing residual life prediction model for process enhancement equipment based on rotor imbalance response analysis

A rotating packed bed is a typical chemical process enhancement equipment that can strengthen micromixing and mass transfer.During the operation of the rotating packed bed,the nonreactants and products irregularly adhere to the wire mesh packing in the rotor,thus resulting in an imbalance in the vibration of the rotor,which may cause serious damage to the bearing and material leakage.This study proposes a model prediction for estimating the bearing residual life of a rotating packed bed based on rotor imbalance response analysis.This method is used to determine the influence of the mass on the imbalance in the vibration of the rotor on bearing damage.The major influence on rotor vibration was found to be exerted by the imbalanced mass and its distribution radius,as revealed by the results of orthogonal experiments.Through implementing finite element analysis,the imbalance response curve for the rotating packed bed rotor was obtained,and a correlation among rotor imbalance mass,distribution radius of imbalance mass,and bearing residue life was established via data fitting.The predicted value of the bearing life can be used as the reference basis for an early safety warning of a rotating packed bed to effectively avoid accidents.

Economic Stress, Precariousness and Risk of High Blood Pressure: A Descriptive Survey of Life Models within Households of the Central Region of Cameroon

Context/Objective: High blood pressure (HBP) currently represents the most widespread chronic non-communicable disease in Cameroon. The increase in its prevalence in the country is the result of multiple factors including economic stress imposed by precariousness, poor living conditions, sources of anxiety, anguish, depression and other behavioral disorders. Economic stress is a globalizing concept that integrates into a purely hermeneutic approach, a particular functioning of the nervous system of an individual who faces employment problems and precarious remuneration conditions. The non-satisfaction by an individual of his basic needs due to insufficient financial means can cause him to become irritable, aggressive, and socially and symbolically isolated, thereby increasing the desire to resort to morbid life models such as excessive consumption of narcotics and other psychoactive substances often associated with high blood pressure. The fight against the emergence of BPH is a complex, multifaceted and multifactorial reality that requires taking into account economic stress. The main objective of this survey is to describe the situation of economic stress within the Cameroonian population, which imposes precariousness and life models at risk of high blood pressure. Specifically, we determined the level of household income and the sources of income. Methods: A cross-sectional survey with a descriptive aim among five hundred households in the Central Region of Cameroon was conducted. A probabilistic technique called simple randomness was used. The number of households to be surveyed was determined indirectly using the Cochrane formula. Data collection in face-to-face mode using a physical questionnaire took place from July 1 to August 31, 2023, after obtaining ethical clearance from the Regional Health Research Ethics Committee, Human from the Center and an administrative authorization for data collection. Regarding their processing, the data was grouped during processing in Excel sheets. Normality and reliability tests of the collected data were carried out. For this, the Chi-square test was used for data with a qualitative value and that of Kolmogorov-Sminorf for data with a quantitative value. Descriptive analysis was possible using R software version 3.2, SPSS version 25.0, XLSTAT 2016, PAST and EXCEL programs from Microsoft Office 2013. Results: The main results highlight economic stress, with 45.60% of households surveyed earning less than US$154 per month;55% of household heads were women in single-parent families;14% of household heads were unemployed, 22% worked in the private sector and 19% were self-employed. This general economic situation leads to precarious living conditions, thereby increasing the risk of high blood pressure among the Cameroonian population.

A Building Information Modeling-Life Cycle Cost Analysis Integrated Model to Enhance Decisions Related to the Selection of Construction Methods at the Conceptual Design Stage of Buildings

Life Cycle Cost Analysis (LCCA) provides a systematic approach to assess the total cost associated with owning, operating, and maintaining assets throughout their entire life. BIM empowers architects and designers to perform real-time evaluations to explore various design options. However, when integrated with LCCA, BIM provides a comprehensive economic perspective that helps stakeholders understand the long-term financial implications of design decisions. This study presents a methodology for developing a model that seamlessly integrates BIM and LCCA during the conceptual design stage of buildings. This integration allows for a comprehensive evaluation and analysis of the design process, ensuring that the development aligns with the principles of low carbon emissions by employing modular construction, 3D concrete printing methods, and different building design alternatives. The model considers the initial construction costs in addition to all the long-term operational, maintenance, and salvage values. It combines various tools and data through different modules, including energy analysis, Life Cycle Assessment (LCA), and Life Cycle Cost Analysis (LCCA) to execute a comprehensive assessment of the financial implications of a specific design option throughout the lifecycle of building projects. The development of the said model and its implementation involves the creation of a new plug-in for the BIM tool (i.e., Autodesk Revit) to enhance its functionalities and capabilities in forecasting the life-cycle costs of buildings in addition to generating associated cash flows, creating scenarios, and sensitivity analyses in an automatic manner. This model empowers designers to evaluate and justify their initial investments while designing and selecting potential construction methods for buildings, and enabling stakeholders to make informed decisions by assessing different design alternatives based on long-term financial considerations during the early stages of design.

Analysis of the Effect of Integrated Extended Care Model in Improving the Quality of Life of Elderly Patients with Type 2 Diabetes Mellitus

Objective: To analyze the impact of an integrated extended care model on improving the quality of life of elderly patients with Type 2 Diabetes Mellitus (T2DM). Methods: A total of 176 patients admitted to the hospital from March 2015 to February 2018 were selected and randomly assigned to an observation group and a control group, with 88 patients each. The control group implemented conventional nursing interventions, and the observation group carried out an integrated extended-care model. The level of glycemic control, quality of life, and daily medication adherence between both groups were compared. Results: The observation group showed significant improvement in the level of glycemic control, and their fasting blood glucose, 2-hour postprandial blood glucose, and glycated hemoglobin levels were significantly lower as compared with those in the study group (P < 0.05). The quality of life of the patients in the observation group was higher than that of the control group (P < 0.05). The observation group had a higher compliance score (95.48 ± 7.45) than the control group (81.31 ± 8.72) (t = 8.909, P < 0.05). Conclusion: The integrated extended care model allows patients to receive comprehensive and individualized nursing services after discharge, which improves the effect of drug therapy and the quality of life of patients.

Remaining Useful Life Model and Assessment of Mechanical Products: A Brief Review and a Note on the State Space Model Method

The remaining useful life(RUL) prediction of mechanical products has been widely studied for online system performance reliability, device remanufacturing, and product safety(safety awareness and safety improvement). These studies incorporated many di erent models, algorithms, and techniques for modeling and assessment. In this paper, methods of RUL assessment are summarized and expounded upon using two major methods: physics model based and data driven based methods. The advantages and disadvantages of each of these methods are deliberated and compared as well. Due to the intricacy of failure mechanism in system, and di culty in physics degradation observation, RUL assessment based on observations of performance variables turns into a science in evaluating the degradation. A modeling method from control systems, the state space model(SSM), as a first order hidden Markov, is presented. In the context of non-linear and non-Gaussian systems, the SSM methodology is capable of performing remaining life assessment by using Bayesian estimation(sequential Monte Carlo). Being e ective for non-linear and non-Gaussian dynamics, the methodology can perform the assessment recursively online for applications in CBM(condition based maintenance), PHM(prognostics and health management), remanufacturing, and system performance reliability. Finally, the discussion raises concerns regarding online sensing data for SSM modeling and assessment of RUL.

Reliability estimation and remaining useful lifetime prediction for bearing based on proportional hazard model

As the central component of rotating machine,the performance reliability assessment and remaining useful lifetime prediction of bearing are of crucial importance in condition-based maintenance to reduce the maintenance cost and improve the reliability.A prognostic algorithm to assess the reliability and forecast the remaining useful lifetime(RUL) of bearings was proposed,consisting of three phases.Online vibration and temperature signals of bearings in normal state were measured during the manufacturing process and the most useful time-dependent features of vibration signals were extracted based on correlation analysis(feature selection step).Time series analysis based on neural network,as an identification model,was used to predict the features of bearing vibration signals at any horizons(feature prediction step).Furthermore,according to the features,degradation factor was defined.The proportional hazard model was generated to estimate the survival function and forecast the RUL of the bearing(RUL prediction step).The positive results show that the plausibility and effectiveness of the proposed approach can facilitate bearing reliability estimation and RUL prediction.

Grain size based low cycle fatigue life prediction model for nickel-based superalloy

Nickel-based superalloys are easy to produce low cycle fatigue(LCF)damage when they are subjected to high temperature and mechanical stresses.Fatigue life prediction of nickel-based superalloys is of great importance for their reliable practical application.To investigate the effects of total strain and grain size on LCF behavior,the high temperature LCF tests were carried out for a nickel-based superalloy.The results show that the fatigue lives decreased with the increase of strain amplitude and grain size.A new LCF life prediction model was established considering the effect of grain size on fatigue life.Error analyses indicate that the prediction accuracy of the new LCF life model is higher than those of Manson-Coffin relationship and Ostergren energy method.

Study on Strength and Life of Anisotropic Single Crystal Blade - Part I: Crystallographic Constitutive Models and Applications

The single crystal blade is one of the key technologies for improving the performance, durability and reliability of aero-engines and ground gas-turbine engines. However, the anisotropic mechanical properties of the single crystal material makes a great deal of difficulties on the development and the application of the single crystal blade, which is a challenge for the engineering application of the single crystal superalloy and the theoretic bases of the application. Some researches on the strength analysis and the life prediction of the anisotropic single crystal blade were carried out by the authors' research team. They are as follows. The crystallographic constitutive models for the plastic and the creep behaviors and the method of the rupture life prediction were established and verified. The tensile or the creep experiments for DD3 single crystal alloy with different orientations under different temperatures and different tensile rates or under different temperatures and different stress levels were carried out. The experimental data and the anisotropic properties at intermediate and high temperatures revealed by the experiments are significant for the application of the single crystal alloy. In addition, the experimental research for a kind of single crystal blade was also made. As the application of the researches the strength analysis and the life prediction were carried out for the single crystal blade of a certain aero-engine. In this part, the constitutive models and their applications are described, and the experimental research work will be described in part II.

Life Distribution Transformation Model of Planetary Gear System

Planetary gear systems have been widely used in transportation, construction, metallurgy, petroleum, aviation and other industrial fields. Under the same condition of power transmission, they have a more compact structure than ordinary gear train. However, some critical parts, such as sun gear, planet gear and ring gear often suffer from fatigue and wear under the conditions of high speed and heavy load. For reliability research, in order to predict the fatigue probability life of planetary gear system, detailed kinematic and mechanical analysis for a planetary gear system is firstly completed. Meanwhile, a gear bending fatigue test is carried out at a stress level to obtain the strength information of specific gears. Then, a life distribution transformation model is established according to the order statistics theory. Transformation process is that, the life distribution of test gear is transformed to that of single tooth, and then the life distribution of single tooth can be effectively transformed to that of the planetary gear system. In addition, the effectiveness of the transformation model is finally verified by a processing method with random censoring data.

Optimum design of equivalent accelerated life testing plans based on proportional hazards-proportional odds model

The optimum design of equivalent accelerated life testing plan based on proportional hazards-proportional odds model using D-optimality is presented. The defined equivalent test plan is the test plan that has the same value of the determinant of Fisher information matrix. The equivalent test plan of step stress accelerated life testing （SSALT） to a baseline optimum constant stress accelerated life testing （CSALT） plan is obtained by adjusting the censoring time of SSALT and solving the optimization problem for each case to achieve the same value of the determinant of Fisher information matrix as in the baseline optimum CSALT plan. Numer- ical examples are given finally which demonstrate the equivalent SSALT plan to the baseline optimum CSALT plan reduces almost half of the test time while achieving approximately the same estimation errors of model parameters.

Using hybrid modeling for life cycle assessment of motor bike and electric bike

Life-cycle assessment (LCA) is environmental evaluation of products, materials, and processes over their life cycle. Truncation uncertainty and corresponding uncertainty are main problems occurred in process life cycle assessment (PLCA) modeling and economic input-output life cycle assessment (EIOLCA) modeling. Through combination of these two modelings in different life cycle stage and use of an uncertainty reduction strategy, a hybrid life cycle assessment modeling method was proposed in this study. Case studies were presented on gasoline-powered motorbikes (M-bike) and electricity-powered electric bike (E-bike). Web-based software was developed to analyze process environmental impacts. Results show that the largest part of life cycle energy (LCE) is consumed at use stage. Less energy is consumed in life cycle of E-bike than that of M-bike. GWP (Global Warming Potential), CO (Carbon Monoxide), PM10 (particulate matter) emission of M-bike are higher than that of E-bike, especially at use stage, AP (acidification Potential) emission of E-bike is higher than that of M-bike. Comprehensively, E-bike is energy efficient and less emitting, and better choice for urban private transportation.

Improving rehabilitation and quality of life after percutaneous transhepatic cholangiography drainage with a rapid rehabilitation model

BACKGROUND Percutaneous transhepatic cholangiography drainage(PTCD)effectively treats biliary obstruction.However,patients must maintain the drainage tube after hospital discharge,which may interfere with daily life and work,potentially causing psychological distress.Postoperative rehabilitation is crucial,and strengthened nursing interventions can shorten recovery time.AIM The aim was to evaluate an inpatient model to shorten rehabilitation duration and improve quality of life after PTCD.METHODS A total of 118 patients with malignant obstructive jaundice who were admitted to our hospital between May 2018 and January 2021 were included and divided into observational(with therapy)and control(no therapy)groups of 59 each.RESULTS The observational group had fewer hospitalization days than the control group.The complication,the PTCD fixed-tube prolapse,and tube-related admission rates within 3 mo after PTCD were significantly lower in the observation group than in the control group(P<0.05).The fatigue,pain,nausea,vomiting,pruritus,emaciation,and fever scores after PTCD decreased in both groups compared with the scores before PTCD(P<0.05).The quality of life scores after the intervention were higher in the observation than in the control group(P<0.05).CONCLUSION The model promoted rehabilitation after PTCD,reduced post-PTCD complications,and the tube-related admissions in the 3 mo after the procedure,and improved the quality of life.

A new model for life prediction of GH4133 under TMF conditions

Thermal mechanical cyclic strain tests were carried out under in-phase andout-of-phase conditions on a Nickel-base Superalloy GH4133 in the temperature range of 571-823 degC. Based on analyzing the present models of TMF (thermal mechanical fatigue) life prediction, a newmodel for predicting nickel-base superalloy TMF lifetime was proposed. TMF life of superalloy GH4133was calculated accurately based on the new model. Experimental TMF life has been compared with thecalculated results and all results fall in the scatter band of 1.5. The calculating results showthat the new model is not only simple, but also precise. This model will play great roles as lifeprediction of the metal materials and the engineering components subjected to non-isothermal serviceconditions.

Path Classification and Estimation Model Based Prognosis of Pneumatic Cylinder Lifetime

Prognosis is a key technology to improve reliability,safety and maintainability of products,a lot of researchers have been devoted to this technology.But to improve the predict accuracy of remaining life of products has been difficult.To predict the lifetime specification of pneumatic cylinders with high reliability and long lifetime and small specimen,this paper put forward the prognosis algorithm based on the path classification and estimation（PACE） model.PACE model is based entirely on failure data instead of failure threshold.Pneumatic cylinders normally characterize with failure mechanism wear and tear.Since the minimum working pressure increases with the number of working cycles,the minimum working pressure is chosen as degradation signal.PACE model is fundamentally composed of two operations：path classification and remaining useful life（RUL） estimation.Path classification is to classify a current degradation path as belonging to one or more of previously collected exemplary degradation paths.RUL estimation is to use the resulting memberships to estimate the remaining useful life.In order for verification and validation of PACE prognostic method,six pneumatic cylinders are tested.The test data is analyzed by PACE prognostics.It is found that the PACE based prognosis method has higher prediction accuracy and smaller variance and PACE model is significantly outperform population based prognostics especially for small specimen condition.PACE model based method solved the problem of prediction accuracy for small specimen pneumatic cylinders＇ prognosis.

Estimation of Building’s Life Cycle Carbon Emissions Based on Life Cycle Assessment and Building Information Modeling: A Case Study of a Hospital Building in China

Throughout the life cycle, the buildings emit a great deal of carbon dioxide into the atmosphere, which directly leads to aggravation in the greenhouse effect and becomes a severe threat to the environment and humans. Researchers have made numerous efforts to accurately calculate emissions to reduce the life cycle carbon emissions of residential buildings. Nevertheless, there are still difficulties in quickly estimating carbon emissions in the design stage without specific data. To fill this gap, the study, based on Life Cycle Assessment (LCA) and Building Information Modeling (BIM), proposed a quick method for estimating Building’s Life Cycle Carbon Emissions (BLCCE). Taking a hospital building in Chuzhou City, Anhui Province, China as an example, it tested its possibility to estimate BLCCE. The results manifested that: 1) the BLCCE of the project is 40,083.56 tCO2-eq, and the carbon emissions per square meter per year are 119.91 kgCO2-eq/(m2·y);2) the stage of construction, operational and demolition account for 7.90%, 91.31%, and 0.79% of BLCCE, respectively;3) the annual carbon emissions per square meter of hospital are apparently higher than that of villa, residence, and office building, due to larger service population, longer daily operation time, and stricter patient comfort requirements. Considering the lack of BLCCE research in Chinese hospitals, this case study will provide a valuable reference for the estimated BLCCE of hospital building.

Analysis of Fatigue Strain, Fatigue Modulus and Fatigue Damage for the Model Formulation of Concrete Based on Strain Life Approach

Analysis of fatigue strain, fatigue modulus and fatigue damage for the modeling of concrete plays a vital role in the evolution material behaviour which is heterogeneous and anisotropic in nature. The Level-S nonlinear fatigue strain curve, fatigue modulus curve, residual strain curve of concrete in compression, tension, flexure and torsional fatigue loading were proposed using strain life approach. The parameters such as physical meaning, the ranges, and the impact on the shape of the curve were discussed. Then, the evolution model of fatigue modulus was established based on the fatigue strain, fatigue modulus, residual strain and secondary strain evolution model. The hypothesis of fatigue modulus is inversely related with the fatigue strain amplitude. The fatigue evolution of concrete damages the bond between material grains, changed the orientation of structure of molecules and affects the elastic properties resulting in the reduction of material stiffness and modulus by formation of microcracking, macro cracking, cracking and finally damage. This paper presents the fatigue strain life model and analysis of fatigue strain, fatigue modulus and damage parameters of concrete which is capable of predicting stiffness degradation, inelastic deformation, and strength reduction under fatigue loading and experimental results were employed for the validation of the theoretical model.

Remaining useful life prediction based on nonlinear random coefficient regression model with fusing failure time data

Remaining useful life(RUL) prediction is one of the most crucial elements in prognostics and health management(PHM). Aiming at the imperfect prior information, this paper proposes an RUL prediction method based on a nonlinear random coefficient regression(RCR) model with fusing failure time data.Firstly, some interesting natures of parameters estimation based on the nonlinear RCR model are given. Based on these natures,the failure time data can be fused as the prior information reasonably. Specifically, the fixed parameters are calculated by the field degradation data of the evaluated equipment and the prior information of random coefficient is estimated with fusing the failure time data of congeneric equipment. Then, the prior information of the random coefficient is updated online under the Bayesian framework, the probability density function(PDF) of the RUL with considering the limitation of the failure threshold is performed. Finally, two case studies are used for experimental verification. Compared with the traditional Bayesian method, the proposed method can effectively reduce the influence of imperfect prior information and improve the accuracy of RUL prediction.

Stochastic Modelling of Vulnerability Life Cycle and Security Risk Evaluation

The objective of the present study is to propose a risk evaluation statistical model for a given vulnerability by examining the Vulnerability Life Cycle and the CVSS score. Having a better understanding of the behavior of vulnerability with respect to time will give us a great advantage. Such understanding will help us to avoid exploitations and introduce patches for a particular vulnerability before the attacker takes the advantage. Utilizing the proposed model one can identify the risk factor of a specific vulnerability being exploited as a function of time. Measuring of the risk factor of a given vulnerability will also help to improve the security level of software and to make appropriate decisions to patch the vulnerability before an exploitation takes place.

Bi-variable damage model for fatigue life prediction of metal components

Based on the theory of continuum damage mechanics,a bi-variable damage mechanics model is developed,which,according to thermodynamics,is accessible to derivation of damage driving force,damage evolution equation and damage evolution criteria. Furthermore,damage evolution equations of time rate are established by the generalized Drucker＇s postulate. The damage evolution equation of cycle rate is obtained by integrating the time damage evolution equations,and the fatigue life prediction method for smooth specimens under repeated loading with constant strain amplitude is constructed. Likewise,for notched specimens under the repeated loading with constant strain amplitude,the fatigue life prediction method is obtained on the ground of the theory of conservative integral in damage mechanics. Thus,the material parameters in the damage evolution equation can be obtained by reference to the fatigue test results of standard specimens with stress concentration factor equal to 1,2 and 3.

Feature Based Machining Process Planning Modeling and Integration for Life Cycle Engineering

Machining process data is the core of computer aided process planning application systems.It is also provides essen- tial content for product life cycle engineering.The character of CAPP that supports product LCE and virtual manufacturing is an- alyzed.The structure and content of machining process data concerning green manufacturing is also examined.A logic model of Machining Process Data has been built based on an object oriented approach,using UML technology and a physical model of machin- ing process data that utilizes XML technology.To realize the integration of design and process,an approach based on graph-based volume decomposition was apposed.Instead,to solve the problem of generation in the machining process,case-based reasoning and rule-based reasoning have been applied synthetically.Finally,the integration framework and interface that deal with the CAPP integration with CAD,CAM,PDM,and ERP are discussed.