Method For Simulation Of Processes Research Articles

Bridging length and time scales in predictive simulations of thermo-mechanical processes

Abstract This work introduces a theoretical formulation and develops numerical methods for finite element implementation of the formulation so as to extend the concurrent atomistic-continuum (CAC) method for modeling and simulation of finite-temperature materials processes. With significantly reduced degrees of freedom, the CAC simulations are shown to reproduce the results of atomically resolved molecular dynamics simulations for phonon density of states, velocity distributions, equilibrium temperature field of the underlying atomistic model, and also the density, type, and structure of dislocations formed during the kinetic processes of heteroepitaxy. This work also demonstrates the need of a mesoscale tool for simulations of heteroepitaxy, as well as the unique advantage of the CAC method in simulation of the defect formation processes during heteroepitaxy.

The advancement of EVA polymerization kinetics and development of high-performance EVOH polymerization process

Ethylene-vinyl alcohol copolymer (EVOH) is a material with excellent barrier properties, produced via the radical copolymerization of ethylene and vinyl acetate in solution, followed by alcoholysis in methanol with NaOH as a catalyst. It is widely used in packaging and medical materials. However, balancing the barrier properties and processability remains challenging. Currently, multi-scale research methods using density functional theory (DFT) to explore polymerization mechanisms and obtain kinetic data, combined with process simulation methods to develop high-performance EVOH polymerization process, are gaining attention. Therefore, this study employs DFT and transition state theory (TST) methods to study the kinetics of chain growth and chain transfer reactions of radicals at first, yielding the average chain growth and chain transfer rate constants for copolymerization reactions. Then, based on these rate constants, process simulations were used to model the ethylene–vinyl acetate solution copolymerization reactor, developing polymerization process for EVOH with high barrier properties as well as EVOH with both high barrier properties and good processability. These findings provide suggestions and guidance for EVOH production and application.

An energetic approach to the statistical analysis and optimization of friction welding processes applied to an aluminum-steel-joint

The present publication deals with an energy-oriented approach to the statistical analysis of rotational friction welding processes. To illustrate the methodological approach, it is applied to investigate the effects of energy flow on material flow behavior and joint quality during friction welding of an AA6060 alloy with a low-alloy 16MnCr5 filler steel. The influences of the setting parameters on the energetic states are first analyzed by means of an initial screening. The evaluation using process simulation and statistical methods enables the generation of regressive response surfaces for the friction power, the friction time and the resulting induced friction energy. Based on these findings, a second experimental field is formed and evaluated, which considers the interaction between the energy input of the frictioning stage and the workpiece forging. This new approach results in the functional separation of the frictioning and forging stage, which eliminates the usual statistical interaction effects and thus facilitates analysis and optimization. The qualitative result variable required for the purpose of interpreting the results is the ultimate tensile strength of the friction-welded joint. Additionally determined hardness curves provide information about the properties of the thermally influenced zone and strength-relevant process sequences. The result is that, in addition to the amount of energy induced, the frictional power with which the former is induced also has a considerable influence on the joint strength, as it influences the material flow and the properties of the joining zone.

Influence of Ground Motion Non-Gaussianity on Seismic Performance of Buildings

The non-Gaussian feature of seismic ground motion has been reported in some works. However, there remains a lack of research on the influence of the ground motion non-Gaussianity on the seismic performance of buildings, which motivates this study. By employing a non-Gaussian non-stationary random process simulation method previously proposed by the authors, 40,000 ground motion acceleration signals are efficiently generated, including 20,000 Gaussian and 20,000 non-Gaussian records. As computational examples, a four-story frame building and a three-tower super-tall building are selected. The generated acceleration signals serve as external excitations for the two buildings, allowing for a comparison of the differences in seismic structural responses caused by the Gaussian and non-Gaussian earthquake groups. Probability analysis is performed using top-layer displacement and maximum inter-story drift ratio as damage indicators. The results show that the structural responses induced by both Gaussian and non-Gaussian earthquake groups have identical first- and second-order moments but different higher-order moments. The responses from non-Gaussian earthquakes display distinct non-Gaussian traits, with their distribution of extreme values exhibiting a longer tail compared to the Gaussian counterparts. This leads to a notably larger value of non-Gaussian responses under high crossing probabilities, with an amplification that can surpass 18%.

Effective FE simulation methods for fillet welding process by continuous distributed heat input and element combination

This study proposed effective finite element methods for simulating the fillet welding process on T-shaped joints. The T-shaped fillet welded joints were fabricated, and the process was simulated by a Continuous Distributed heat input method (CD method) and combining shell and solid elements. This study compared the models by the Discontinuous Uniform heat input method (DU method) and the CD method. The results showed that the CD method not only simplified the modeling process but also reduced the calculation time compared to the DU method. Furthermore, combining solid and shell elements reduced the number of nodal points in the models. The calculation time of the models by the element combination was significantly reduced. By comparing with experiments, it was shown that the CD heat input method and the combination of solid and shell elements could save calculation time while keeping the analysis accuracy.

Comprehensive Composite Mould Filling Pattern Dataset for Process Modelling and Prediction

The Resin Transfer Moulding process receives great attention from both academia and industry, owing to its superior manufacturing rate and product quality. Particularly, the progression of its mould filling stage is crucial to ensure a complete reinforcement saturation. Contemporary process simulation methods focus primarily on physics-based approaches to model the complex resin permeation phenomenon, which are computationally expensive to solve. Thus, the application of machine learning and data-driven modelling approaches is of great interest to minimise the cost of process simulation. In this study, a comprehensive dataset consisting of mould filling patterns of the Resin Transfer Moulding process at different injection locations for a composite dashboard panel case study is presented. The problem description and significance of the dataset are outlined. The distribution of this comprehensive dataset aims to lower the barriers to entry for researching machine learning approaches in composite moulding applications, while concurrently providing a standardised baseline for evaluating newly developed algorithms and models in future research works.

SynBPS: a parametric simulation framework for the generation of event-log data

In the pursuit of ecological validity, current business process simulation methods are calibrated to data from existing processes. This is important for realistic what-if analysis in the context of these processes. However, this is not always the “right tool for the job.” To test hypotheses in the area of predictive process monitoring, it can be more helpful to simulate event-log data from a theoretical process, where all aspects can be manipulated. One example is when assessing the influence of process complexity or variability on the performance of a new prediction method. In this case, the ability to include control variables and systematically change process characteristics is a key to fully understanding their influence. Calibrating a simulation model from observed data alone can in these cases be limiting. This paper proposes a simulation framework, Synthetic Business Process Simulation (SynBPS), a Python library for the generation of event-log data from synthetic processes. Aspects such as process complexity, stability, trace distribution, duration distribution, and case arrivals can be fully controlled by the user. The overall architecture is described in detail, and a demonstration of the framework is presented.

Review of the research status on the transmission and diffusion characteristics of indoor viral aerosol particles.

This study reviews the generation and diffusion characteristics of indoor viral aerosol particles, numerical simulation methods for the diffusion process of viral aerosols, and related research on the impact mechanism of different ventilation methods on the diffusion process of viral aerosols. Research has shown that the selection of initial conditions such as exhalation mode, initial airflow velocity, particle size, turbulence model, and calculation method for the generation of aerosol particles by the human body is of great significance for the numerical simulation of the diffusion process of viral aerosol particles. At the same time, on the basis of selecting appropriate ventilation methods, the reasonable setting of ventilation parameters (temperature, speed, height, etc.) can effectively suppress the spread of viral aerosols. This study can provide a theoretical basis for the study of related respiratory diseases, as well as technical and theoretical support for the selection of indoor ventilation methods to reduce the risk of human exposure caused by viral aerosols in the construction field. It also provides guidance and reference for aerosol transport and environmental protection in indoor atmospheric environments.

Evaluation and Comparison of Reanalysis Data for Runoff Simulation in the Data-Scarce Watersheds of Alpine Regions

Reanalysis datasets provide a reliable reanalysis of climate input data for hydrological models in regions characterized by limited weather station coverage. In this paper, the accuracy of precipitation, the maximum and minimum temperatures of four reanalysis datasets, the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS), time-expanded climate forecast system reanalysis (CFSR+), the European Centre for Medium-Range Weather Forecast Reanalysis (ERA). and the China Meteorological Forcing Dataset (CMFD), were evaluated by using data from 28 ground-based observations (OBs) in the Source of the Yangtze and Yellow Rivers (SYYR) region and were used as input data for the SWAT model for runoff simulation and performance evaluation, respectively. And, finally, the CMADS was optimized using Integrated Calibrated Multi-Satellite Retrievals for Global Precipitation Measurement (AIMERG) data. The results show that CMFD is the most representative reanalysis data for precipitation characteristics in the SYYR region among the four reanalysis datasets evaluated in this paper, followed by ERA5 and CFSR, while CMADS performs satisfactorily for temperature simulations in this region, but underestimates precipitation. And we contend that the accuracy of runoff simulations is notably contingent upon the precision of daily precipitation within the reanalysis dataset. The runoff simulations in this region do not effectively capture the extreme runoff characteristics of the Yellow River and Yangtze River sources. The refinement of CMADS through the integration of AIMERG satellite precipitation data emerges as a potent strategy for enhancing the precision of runoff simulations. This research can provide a reference for selecting meteorological data products and optimization methods for hydrological process simulation in areas with few meteorological stations.

A time variant uncertainty propagation method for high-dimensional dynamic structural system via K-L expansion and Bayesian deep neural network.

In this paper, a time variant uncertainty propagation (TUP) method for dynamic structural system with high-dimensional input variables is proposed. Firstly, an arbitrary stochastic process simulation (ASPS) method based on Karhunen-Loève (K-L) expansion and numerical integration is developed, expressing the stochastic process as the combination of its marginal distributions and eigen functions at several discrete time points. Secondly, the iterative sorting method is implemented to the statistic samples of marginal distributions for matching the constraints of covariance function. Since marginal distributions are directly used to express the stochastic process, the proposed ASPS is suitable for stationary or non-stationary stochastic processes with arbitrary marginal distributions. Thirdly, the high-dimensional TUP problem is converted into several high-dimensional static uncertainty propagation (UP) problems after implementing ASPS. Then, the Bayesian deep neural network based UP method is used to compute the marginal distributions as well as the eigen functions of dynamic system response, the high-dimensional TUP problem can thus be solved. Finally, several numerical examples are used to validate the effectiveness of the proposed method. This article is part of the theme issue 'Physics-informed machine learning and its structural integrity applications (Part 1)'.

Influence of the Mg/MoO<sub>3</sub> additive to diesel fuel on heat output

BACKGROUND: The study results of influence of the Mg/MoO3 composite nanoadditive on the combustion process in the 4Ch10.5/12 diesel engine are given. It is shown that the heat output process in diesel engines divides into two phases: kinetic and diffusive combustion. The review of simulation methods for the heat output process in a diesel engine considering kinetic and diffusive combustion based on the I.I. Vibes method is presented. The review of methods of indicator diagram processing helping to obtain parameters of the Vibes heat output law for the two-phase combustion for the sake of following simulation and working process analysis is made. The heat output analysis of the 4Ch10.5/12 diesel engine indicator diagram processing using the Mg/MoO3 composite nanoadditive is made.
 AIMS: Research of the influence of the Mg/MoO3 composite nanoadditive to fuel on the heat output process in a diesel engine.
 METHODS: The 4Ch10.5/12 air-cooled diesel engine with factory-built fuel supply system was tested at the engine test rig. During the research, influence of the Mg/MoO3 composite nanoadditive to fuel on the heat output process was studied.
 RESULTS: It is found that using the nanoadditive leads to decreasing hardness of combustion process, reduction of self-ignition time delay, increasing the maximal temperature of working body in a combustion chamber, reduction of amount of heat output at the kinetic combustion. Working body temperature increase and simultaneous maximal cycle pressure decrease testify the growth of pre-expansion degree. Parameters of diffusive combustion remain almost stable no matter of mass fraction of the nanoadditive in diesel fuel.
 CONCLUSIONS: It was revealed that nanoparticles of the Mg/MoO3 additive serve as a homogenizer helping to destroy drops of the sprayed fuel and to intensify the evaporation process. Moreover, the nanoparticles serve as self-ignition centers at early stages of the combustion process.

Experimental study on the dew point corrosion behavior in atmospheric tower system

Atmospheric towers are large pieces of equipment used in the petroleum refining process. Hydrochloric acid dew point corrosion often occurs at low-temperatures in the tower. In order to study the dew point corrosion problem of atmospheric tower in a petrochemical enterprise, the process simulation method was used to determine the logistics parameters in the high risk area of dew point corrosion of atmospheric tower system. Based on this, the experimental conditions were set up to closely integrate laboratory research with engineering practice. In view of this special and complex corrosion process, a dew point corrosion experiment was designed to realize the dew point condensation process. The influence of concentration and temperature on the dew point corrosion rate was explored by an electrochemical test and a corrosion weight loss method. The results show that the initial dew point temperature of the tower is 89 ℃, and the risk area of dew point corrosion is located at the top of the tower and in the position of the volatile line, which is consistent with the actual corrosion area of the equipment. In this logistics environment, the dew point corrosion rate of Q345R steel increases with the increase in HCl concentration and temperature in the atmospheric tower system.

Modeling and optimal design of liquid cooling system of electronic module

Formulation of the problem. Optimal design of avionics (avionics) structures is impossible without the development of new complex methods for modeling thermal processes in their designs and verification based on the results of a full-scale experiment, as well as the creation of methods for the justified use of existing and creation of new mathematical algorithms for optimization procedures. When designing modern RES, it is important to provide a temperature regime for the functioning of power elements of the equipment, in our case, we will consider an electronic module. To ensure normal thermal conditions, cooling systems are used, most often heat sinks (radiator) are used, but in some cases it is not possible to install it. To solve this problem, it is proposed to develop a liquid and air cooling system for the electronic module using an expanded set of elements of cooling systems, including a submersible cooling system. Purpose. Develop a comprehensive methodology for modeling and optimal design of a liquid cooling system for an electronic module, the reliability of which is confirmed by the results of analytical calculations and experimental data. Results. On the basis of the developed 3D model of the electronic module, the procedures for multivariate analysis of the laboratory stand unit were implemented using modern computer-aided design tools. A mathematical formulation was formed and procedures for optimizing the thermal regime were performed: modeling and optimization of the coolant; block topology optimization; optimization by body material and coolant type. Graphs and tables of simulation results are presented, on the basis of which it is possible to draw conclusions about the influence of a particular parameter on the distribution of heat fluxes. All the difficulties that the authors encountered in the course of design optimization in the modeling environment are described in detail, as well as ways to solve them. Practical significance. The results obtained make it possible to apply the proposed method for numerical simulation of thermal processes in REM designs, verification based on the results of a full-scale experiment, as well as the creation of methods for the justified application of existing and the development of new mathematical algorithms for optimization procedures.

Efficient ground motion conditional simulation method for nonstationary multivariate processes based on Kriging method and orthogonal discrete wavelet transform

Conditional ground motion simulation methods preserve more physical features of actual ground motions than unconditional methods by including actual earthquake records. This study developed a conditional multivariate nonstationary process simulation method based on the combination of the Kriging method and the orthogonal discrete wavelet transform (DWT). The Kriging method is used to ensure the spectral coherences between simulations as prescribed and is extended to nonstationary random processes by applying it to the average power spectral density (APSD) of ground motions. The ground motions' DWT wavelet coefficients are assumed to be uniformly time-modulated stationary processes whose time-modulating functions are the envelopes of the seed record's wavelet coefficients. The APSD and the envelopes together outline the energy distribution of the random field in both the time and frequency domain features. The power spectral densities of the stationary random processes' DWT coefficients are derived and used to estimate the APSD of the ground motions' DWT coefficients. Approaches to realizing uniformly time-modulated stationary processes with prescribed APSDs and envelope functions are developed. Monte Carlo simulations were conducted to verify the new method's effectiveness. Results show that both the target APSD and coherences can be well approximated, but precise approximation cannot always be realized in the high-frequency range. The new approach possesses a simple structure, involves simple algorithms, and applies to time-independent spectral coherence models, making it an efficient method compared with existing methods.

Palm oil cluster resilience to enhance indigenous welfare by innovative ability to address land conflicts: Evidence of disaster hierarchy

Abstract Recently, capacity building has been named the government’s target in evaluating strengthening land function cycle collaboration in reducing disaster conflicts due to palm oil expansion. Disaster conflicts over palm oil plantations are the main cause of the fundamental transition of environmental culture and customs, especially concerning the welfare capacity of indigenous people in Jambi Province, Indonesia. This article aims to combine information on decision hierarchies and Geographical Information System (GIS) imaging applications to assess complaints of disaster risk in the development of palm oil clusters on indigenous welfare factors due to the palm oil boom in eight Rokan hamlets, Jambi. The combination of the Analytical Hierarchy Process simulation and GIS method in the GeoDa density test is used synergistically to analyze the following criteria for disaster causes: land disputes, water pollution, habitat scarcity, drought/forest fires, floods, and crop failure. The results of the disaster hierarchy show that the priority criteria are land disputes followed by drought/forest fires and floods. Meanwhile, the answer to alternative stakeholder decisions is the regional government according to predictions from the findings of the frequency of resolution of conflicts that have occurred in the past. In addition, the GIS density results detected six Rokan hamlets in Jambi having very high and high conflicts, but two hamlets had no disaster conflict incidents. A capacity building approach in the social, economic, and environmental fields is one of the solutions in minimizing land conflicts caused by palm oil expansion.

Effect of Piping Configuration on Determining Alarm Response Time in HP Scrubber Using Dynamic Simulation

The HP scrubber is an equipment used to separate liquid from gas in the oil and gas industry. The low liquid level in the vessel is one of the abnormal conditions in the HP scrubber, a blowby gas event will happen because of a low level. So, the controller level indicator is required to prevent system damage and workplace accidents. The alarm response time is calculated in order to avoid an accident. To determine the alarm response time for a HP scrubber, a dynamic process simulation method can be used using Aspen HYSYS version 12. In a process simulation modeling also requires a process description that can describe real-world conditions, one of which is the condition of the existing piping in the system. Failure scenarios caused a process to have abnormal conditions, allowing the alarm response time to be calculated, and it can be modelled by using the event scheduler facility In Aspen HYSYS. The HP scrubber's maximum alarm response time without pipe segments and with the addition of 16 m pipe segments are 2.42 minutes and 2.56 minutes. Meanwhile, the time from alarm to failure on the HP Scrubber without and with the addition of 16 m pipe are 13.60 minutes and 28.70 minutes, respectively. So, the length of segment pipes added to the pipe configuration does not really affect the alarm response time. However, it can affect the time until a process failure occurs.

Mechanical–thermal–chemical coupled modeling techniques and numerical simulation methods for the firearm igniting process

AbstractThe firing and ignition of firearms is a complex process involving the coupled effects of mechanical, thermal, and chemical mechanisms. The theoretical modeling and numerical simulation methods for primer mixture impact and ignition process are investigated to reveal the response patterns of characteristic variables, such as primer output pressure and the crater on the primer cup that forms when the firing pin strikes the primer to ignite the primer mixture. Theoretical models such as the elastoplastic mechanical response of the primer mixture, the pore collapse hot spot model, and the Lee‐Tarver ignition and growth model are established by studying the impact response, the initiation mechanism, the hot spot formation mechanism, and the energy release mechanism of the primer mixture. Constitutive models of the primer mixture and the primer cup material are established based on a dynamic compression test of the primer mixture under passive confining pressure and a quasi‐static tensile test of the primer cup material. A numerical model of the primer mixture impact and ignition performance is constructed by using ANSYS LS‐DYNA software. The simulation parameters are serially simulated and calibrated through the 3D total Lagrange algorithm. The firing and ignition response process of a small‐caliber firearm is simulated with the 3D Activation Likelihood Estimation (ALE) algorithm. The relative error between the simulated results and the test results is below 15 %, which validates the feasibility of the numerical simulation methods for the firing and ignition performances of firearms.

Additive manufacturing of cellular structures: Multiscale simulation and optimization

This paper introduces a multiscale and multi-purpose simulation framework to investigate selective beam melting processes for metallic cellular structures along the complete process chain, up to the topology optimization of components made of cellular materials. Process simulation methods on various length scales are introduced to analyze the relation of process strategies and resulting properties of the cellular materials, as e. g. warpage, residual stresses, material grain structure and surface roughness. Numerical homogenization methods are applied to investigate the influence of the grain structure and the topology of the cellular materials on their mechanical properties. Based on these process-dependent mechanical properties, a two-scale optimization of components made of cellular material is performed, aiming in particular on optimizing the buckling resistance of the structures. The interfaces between the different simulation tools are specified and illustrate the flexibility of the numerical framework. It is shown that consistent simulations of additive manufacturing of cellular materials – from the manufacturing process to the optimized component – provide important insights into process–structure interactions and enable tailored additive manufacturing processes.

Theory, framework, and methodology for physical lifespan prediction of hazardous waste landfills

Landfill is a predominant method for hazardous waste disposal in both developed and emerging economies due to simple disposal technology and wide applicability. The prediction of landfill lifespan during the design stage provides support for environmental management of hazardous waste landfill (HWL) and technical support for the implementation of national standards. It also provides guidance for necessary responses after the lifespan expires. At present, research on the degradation of main components or materials of HWLs has been paid much attention, however, how to predict the lifespan of HWLs is a big issue for researchers. In this study, the HWL was selected as research subject, and literature research, theoretical analysis, and model calculation, were used to establish a HWL lifespan prediction framework for the first time. Firstly, the HWL life was defined based on the functional characteristics; secondly, according to comprehensively analyzing the functional requirements, system composition, and structural characteristics of HWLs, the indicators of life termination and the thresholds were confirmed. Then, according to Failure Mode, Mechanism, and Effect Analysis (FMMEA), the failure modes of the core components affecting the lifespan of the HWLs were identified. Finally, a process simulation method (Hydrologic Evaluation of Landfill Performance, HELP) was proposed to simulate the performance degradation of the HWL, combined with the core performance parameters variation caused by the deterioration of the main functional unit. The life prediction framework was developed to increase the prediction accuracy of the performance degradation of HWLs and to provide a methodology for further research on HWL life prediction.

An enriched phase-field method for the efficient simulation of fracture processes

The efficient simulation of complex fracture processes is still a challenging task. In this contribution, an enriched phase-field method for the simulation of 2D fracture processes is presented. It has the potential to drastically reduce computational cost compared to the classical phase-field method (PFM). The method is based on the combination of a phase-field approach with an ansatz transformation for the simulation of fracture processes and an enrichment technique for the displacement field as it is used in the extended finite element method (XFEM) or generalised finite element method (GFEM). This combination allows for the application of significantly coarser meshes than it is possible in PFM while still obtaining accurate solutions. In contrast to classical XFEM / GFEM, the presented method does not require level set techniques or explicit representations of crack geometries, considerably simplifying the simulation of crack initiation, propagation, and coalescence. The efficiency and accuracy of this new method is shown in 2D simulations.