Method For Simulation Of Processes Research Articles

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.

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.

An assembly process simulation method in immersive virtual reality environment

An assembly process simulation method in immersive virtual reality environment

Artificial neural network prediction models for nanofluid properties and their applications with heat exchanger design and rating simulation

Energy is arguably driving society toward a prolific future in the current century. Energy demand has been increasing due to the continuous rise in the global population and basic needs. Energy integration is one of the promising ideas for alleviating energy shortages. Energy integration is performed by using the equipment and recirculating the heat back to the system via heat exchange between the heat source and the coolant. Conventional coolants have limited potential due to their low thermal conductivities. Nanoparticles, nanometer-sized solids with relatively high thermal conductivity, have been used to enhance the thermal properties of coolants, and the mixtures are called nanofluids.Nevertheless, the experiment consumes a lot of cost and time; using an Artificial Neural Network (ANN), a non-linear statistical data correlation model builder, is now considered acceptable and appropriate for correlating the complex relationship between inputs and outputs. This study describes a novel combination of ANN and conventional process simulation for heat transfer using nanofluid in a heat exchanger. In addition, the sensitivity of parameters for heat exchanger design and rating were investigated. The ANN development includes 2723 datasets with various nanofluid types and properties. The predictions of the new ANN nanofluid predictive model are closer to reality than other numerical methods, as shown in the simulation. The maximum error from the result was only 4.1%. The work reproduces the conventional simulation for better adaptability and great performance with acceptable error. Finally, the study combines ANN and conventional process simulation methods that effectively examine nanofluid enhancement's performance on heat exchangers. The parameter sensitivity test is discussed based on a plate heat exchanger, including an increase in heat transfer coefficient (around 7%), maintained pressure drop, and performance efficiency coefficient.

Numerical Study on Welding Residual Stress Distribution of Corrugated Steel Webs

Residual stresses are an inevitable result of the welded fabrication process of corrugated steel webs (CSWs), resulting in structures with high and unpredictable stress fields, causing unexpected failures. The residual stress field is affected by structural parameters and the welding path of CSWs. This study proposes the welding process simulation method for CSWs with element birth and death technology. The optimization design method of heat source parameters is proposed. The feasibility of the simulation method is verified by comparing the numerical results with the experimental results of relevant literature. As a part of the study, a comparison of residual stress fields upon cooling welded CSWs with bending angles of 30, 45, and 60 degrees is presented. Thereafter, the effect of two types of single-sided welding paths and double-sided welding construction processes on residual stress distribution is discussed. Generally, the study results have shown that the equivalent residual stress near the weld reaches the maximum 344 MPa, which is very close to the Q345 steel yield strength. The size of the bending angle has no major effect on the residual stress distribution pattern, but it influences the residual stress value at the bending position. The residual stress at the bending position increases with the bending angle of CSWs. Different welding paths significantly impact the residual stress of the weld toe, and selecting a reasonable welding path can effectively reduce the residual stress value by 20 to 40 MPa.

Modelling and optimization of liquid air energy storage systems with different liquefaction cycles

Liquid air energy storage (LAES) is one of the large-scale mechanical energy storage technologies which are expected to solve the issue of renewable energy power storage and peak shaving. As the main energy loss of a standalone LAES occurs in the liquefaction process, this paper focused on the thermodynamic analysis of LAES systems with different liquefaction cycles. Six liquefaction cycles were considered. To obtain a higher system efficiency and fair comparative analysis of the performance of different LAES systems, authors used a combined genetic algorithm (GA) and HYSYS process simulation method to perform the multi-parameters global optimization. Subsequently, energy and exergy analyses were conducted on the optimized LAES systems. The results show that the system efficiency of the LAES based on turbo-expander refrigeration (i.e., the Claude cycle, Kapitza cycle, and Heylandt cycle) increases with an increase in the split ratio. The LAES with Kapitza liquefaction cycle shows the most competitive system performance compared with the other liquefaction cycles based-LAES systems. The LAES with Kapitza liquefaction cycle exhibits the lowest optimal charging pressure of 10.73 MPa and achieves the highest round-trip efficiency, system storage exergy efficiency, and system recovery exergy efficiency of 60.02 %, 86.41 %, and 84.98 %, respectively. The obtained GA optimization and thermodynamic analysis results of LAES systems with different liquefaction configurations can provide significant theoretical guidance for further industrial applications of LAES.

Simulation Study and Sensitivity Analysis of Gamma-Valerolactone Production from Ethyl Levulinate

Gamma-valerolactone (GVL) is emerging as a promising renewable fuel because it can be produced from renewable materials such as biomass. This article presents a conceptual design and simulation of the conversion of ethyl levulinate into GVL biofuel by hydrogenation process using ChemCAD 7.1.2 software. The process simulation method involves selecting a thermodynamic model, defining component chemicals, selecting suitable operating units and identifying operating conditions. The NRTL thermodynamic model was used for the liquid phase modeling and SRK for the vapor phase fugacity calculation. The binary interaction parameter of NRTL thermodynamic model was regressed from experimental vapor-liquid equilibrium (VLE) data. A sensitivity analysis of the effect of feed temperature on the GVL purification distillation column was carried out to obtain the optimum value for the distillation column configuration.