Proposed Simulation Methodology Research Articles

Analysis of condensation phenomena according to the type of energy recovery ventilator—Simulation and experiments

Ventilation plays a crucial role in maintaining indoor air quality. Energy recovery ventilators (ERVs) have emerged as a solution to balance ventilation needs and energy consumption in buildings. However, ERVs can encounter condensation issues in extreme outdoor conditions, impacting their performance and indoor air quality. In this study, we investigate occurrence conditions and ratios of condensation in ERVs through dynamic simulations and experimental tests using different heat exchanger types: plastic-based plate, membrane-based plate, and rotary. The simulation results show that condensation ratios vary depending on the heat exchanger type and seasonal conditions, with higher latent effectiveness playing a significant role in reducing condensation. Notably, we demonstrate that rotary ERVs rarely exhibit the generation of condensation. The simulation results are validated through experimental tests, ensuring reliable condensation predictions in ERVs. Our findings underline the importance of selecting appropriate type of ERV to mitigate condensation and enhance indoor comfort while promoting energy efficiency. The proposed simulation methodology will provide valuable insights into estimating condensation ratios in ERVs under diverse climatic conditions.

Optimizing raw material composition to increase sustainability in porcelain tile production: A simulation‐based approach

AbstractReducing the environmental impact of porcelain tile production while maintaining cost‐effectiveness is challenging. This work introduced a novel modeling approach for optimizing a standard composition range comprising kaolinite (15–38 wt.%), illite (0–20 wt.%), quartz (20–40 wt.%), and feldspar (20–45 wt.%) to establish a robust composition interval for porcelain stoneware tiles. The proposed study considers several factors, such as composition impact on the manufacturing sequence, production costs, and CO2 emission. A flowsheet simulation database was generated by coupling the Dyssol framework with MATLAB. This study investigated the influence of raw material composition within the process sequence, the total CO2 emissions, and production costs within the contexts of Spain and Brazil, two of the top five global producers. Granules with a higher proportion of talc and illite exhibit reduced moisture content after spray drying, and these combinations have lower green body porosity after compaction. The addition of talc allowed for decreased porosity content after compaction reduced firing temperature, and lowered costs and CO2 emissions despite the higher prices associated with talc. The proposed simulation methodology offers a powerful decision‐making tool for optimizing raw material composition to minimize cost and CO2 emissions in the porcelain tile production. This methodology represents an early stride toward integrating digital twin methodologies within the ceramic tile sector, facilitating improved process regulation, and promoting the adoption of digital technologies.

Microscale DEM simulation of spray-dried porcelain granules under uniaxial compaction

The microscale modeling of spray-dried granules for porcelain tile manufacturing with different moisture contents under uniaxial compaction is investigated in this paper. The Discrete Element Method (DEM) and the Bonded Particle Model (BPM) were applied for the investigation. To describe the mechanical behavior of granules during compression, an elastic-plastic bonded model was implemented, in which the moisture content is linked to the properties of the bonds. A good agreement was reached between experiments and simulations for the second and third stages of compaction. Herein, we obtained a mathematical model that links moisture, bond behavior during rupture, and porosity after compression. Different experimental studies have validated the model with high-achieving correspondence between the experiments and simulations. Thus, the proposed simulation methodology proved effective in predicting the porosity of the particles' bulk after uniaxial compaction.

Physics-informed reduced-order learning from the first principles for simulation of quantum nanostructures

Multi-dimensional direct numerical simulation (DNS) of the Schrödinger equation is needed for design and analysis of quantum nanostructures that offer numerous applications in biology, medicine, materials, electronic/photonic devices, etc. In large-scale nanostructures, extensive computational effort needed in DNS may become prohibitive due to the high degrees of freedom (DoF). This study employs a physics-based reduced-order learning algorithm, enabled by the first principles, for simulation of the Schrödinger equation to achieve high accuracy and efficiency. The proposed simulation methodology is applied to investigate two quantum-dot structures; one operates under external electric field, and the other is influenced by internal potential variation with periodic boundary conditions. The former is similar to typical operations of nanoelectronic devices, and the latter is of interest to simulation and design of nanostructures and materials, such as applications of density functional theory. In each structure, cases within and beyond training conditions are examined. Using the proposed methodology, a very accurate prediction can be realized with a reduction in the DoF by more than 3 orders of magnitude and in the computational time by 2 orders, compared to DNS. An accurate prediction beyond the training conditions, including higher external field and larger internal potential in untrained quantum states, is also achieved. Comparison is also carried out between the physics-based learning and Fourier-based plane-wave approaches for a periodic case.

Warpage Estimation and Demonstration of Panel-Level Fan-Out Packaging With Cu Pillars Applied on a Highly Integrated Architecture

Fan-out panel-level packaging (FO-PLP) has become a critical forward-looking technology because it can meet the demands for small size, high input/output counts, and multi-chip functions. Moreover, a three-dimensional stacked architecture called packaging-on-packaging can be achieved using the interconnects of Cu pillars. However, the serious warpage issue of FO-PLP during the manufacturing process causes many problems, such as assembly difficulty, low device reliability, and poor product yield. To address these problems, this study presents a process-oriented finite element analysis method to estimate the variation of the whole warpage resulting from the mismatch among the coefficients of thermal expansion of dissimilar materials during the fabrication procedures. Notably, the model construction of the complex redistribution layer in the proposed FO-PLP encounters a serious challenge when the simulated estimation is performed. Consequently, an equivalent mechanical characteristic extracted through simulation is adopted to redefine the material properties of RDL and Cu pillars separately. Moreover, modified Timoshenko bi-layered theory is employed with the process-oriented FEA of FO-PLP to clarify the stress-free temperature of the equivalent RDL. An actual FO-PLP vehicle with Cu pillars is fabricated and measured to demonstrate the reliability of the proposed simulation methodology. An average deviation of less than 10% is obtained between the simulated prediction and experiments. The results of factorial design indicate that the mechanical properties of dielectrics and RDL are the dominant factors and have an interactive effect on the warpage magnitude of FO-PLP.

Geometric and Material Modelling Aspects for Strength Prediction of Riveted Joints

The aim of this study is to develop a methodology for static strength and failure mode simulation of hot-driven riveted joints. The purpose is to be able to accurately estimate a rivet joint’s static strength behaviour and its failure mode without relying on experiments, to save both time and resources during the design of joints. The non-linear finite element analysis modelling framework considered the rivet joint configurations and geometry, the material properties of the plate and rivet as well as the clamping force of the hot-driven rivet. A ductile damage model was also implemented to capture the stress softening of the materials and the failure modes of the joints. Using experimental data from literature, the modelling framework is validated, and it is shown that it is able to capture the strength behaviour and failure modes of different configurations of rivet joints markedly well. The effect of the rivet pre-load on the mechanical response of the joint is also studied and it is shown that the strength of the joint increased with the increase in rivet pre-load. The modelling framework is then applied to an industrial component. The modelling framework is used to compare welding and riveting as joining methods in a component built in two grades of high-strength steel. It is found that the welded joint possessed greater strength compared to the proposed riveted joint. However, using the proposed simulation methodology developed, a riveted joint with matching strength to the welded joint could be designed.

Application of Flowsheet Simulation Methodology to Improve Productivity and Sustainability of Porcelain Tile Manufacturing

Porcelain tile manufacturing is an energy-intensive industry that is in dire need of increasing productivity, minimizing costs, and reducing CO2 emissions, while keeping the product quality intact to remain competitive in today’s environment. In this contribution, alternative processing parameters for the porcelain tile production sequence were proposed based on simulation-based process optimization. Flowsheet simulations in the Dyssol framework were used to study the impact of the milling and firing process parameters on the electrical and thermal energy consumption, final product quality, and productivity of the entire processing sequence. For this purpose, a new model of gas flow consumption in the sintering stage was proposed and implemented. During optimization, the primary condition was to maintain the product quality by keeping the final open porosity of the tile within the specified industrial range. The proposed simulation methodology proved to be effective in predicting the influence of the processing parameters on the intermediate and final products of the manufacturing sequence, as well as in estimating the production costs for the Brazilian and Spanish economic conditions. This approach has shown great potential to promote digitalization and establish digital twins in ceramic tile manufacturing for further in-line process control.

Extended Assessment of Sprinkler Irrigation Uniformity in Greenhouses Using GIS and Hydraulic Modeling

Traditionally, distribution uniformity has been obtained by using rain gauges, which makes it a very expensive process. This paper sought to create a simulation strategy using QGIS and EPANET, both free software, that allowed the simulation of the water application results of all the emitters of an irrigation installation. In this way, it was possible to obtain the geospatial representation of the applied water and finally to know the distribution uniformity in the whole installation. The simulation finally fulfilled its objective and was compared with a study of distribution uniformity with rain gauges. The biggest difference between the measured and simulated data was a difference of 5.76% among the sectors. The simulated uniformity was very similar to the measured uniformity, which allowed us to affirm that the proposed simulation methodology was adequate. We believe that the methodology proposed in this article could be very useful in improving the management of sprinkler irrigation systems, particularly those in which distribution uniformity is of special importance. These improvements in management can also result in savings in water and other inputs, which are becoming increasingly important in the current context of climate change and the reduction in the impact of agriculture on the environment. Finally, similar studies could be carried out with the same tools for other pressurized irrigation systems, such as sprinkler irrigation outside greenhouses and drip irrigation.

Soft-Tissue Simulation for Computational Planning of Orthognathic Surgery.

Simulation technologies offer interesting opportunities for computer planning of orthognathic surgery. However, the methods used to date require tedious set up of simulation meshes based on patient imaging data, and they rely on complex simulation models that require long computations. In this work, we propose a modeling and simulation methodology that addresses model set up and runtime simulation in a holistic manner. We pay special attention to modeling the coupling of rigid-bone and soft-tissue components of the facial model, such that the resulting model is computationally simple yet accurate. The proposed simulation methodology has been evaluated on a cohort of 10 patients of orthognathic surgery, comparing quantitatively simulation results to post-operative scans. The results suggest that the proposed simulation methods admit the use of coarse simulation meshes, with planning computation times of less than 10 seconds in most cases, and with clinically viable accuracy.

Discrete-event simulations for metro train operation under emergencies: A multi-agent based model with parallel computing

Emergencies of metro systems have become more frequent in rush hours, which have significant consequences for metro planning, designing, operating, and even the passengers’ daily travel. The motivation of this paper is to establish a hybrid metro simulation method with high efficiency and sufficient precision. To this end, a discrete-event simulation method based on a multi-agent model with parallel computing is proposed to estimate the effects of emergencies efficiently. Firstly, the trains’ motion algorithms are developed to compute the train speed profile for normal operation and metro emergency operation, respectively. Moreover, three types of agents (passenger, station, and train agents) are classified for rescheduling calculation, and six types of events are defined to discretize the emergency simulation process. Furthermore, a parallel computing method is proposed to accelerate the simulation process. Finally, a case study of the Yizhuang Line in Beijing metro is conducted to verify the effectiveness of the proposed simulation methodology. The results have proved the effectiveness and practicality of the proposed simulation method and the influence of the positions where emergencies occur and the emergency durations upon delays of trains and passengers.

Simulation of cellular structures with a coupled FEM-FCM approach based on CT data

The application of cellular structural materials provide new light-weight capabilities in many engineering fields. But the microstructure significantly influences the strength, the fatigue and fracture behavior as well as the life span of a structure made from cellular materials. The current paper illustrates the general idea how to take into account the cellular microstructure in the stress and strain analysis. The detailed geometry, including all discontinuities in the microstructure is available, for instance from measurements provided by the computed tomography (CT). The proposed simulation methodology is a combination of the finite element method (FEM) and the finite cell method (FCM). The FCM approach is applied in regions where discontinuities occur, avoiding a body-fitted mesh. As basis of the FEM-FCM coupling the commercial FEA package Abaqus is used. The theoretical background and the overall simulation workflow along with specific implementation details are discussed. Finally, academic benchmark problems are used to verify the developed coupling method.

Volumetric and Rheological Properties of Vitrimers: A Hybrid Molecular Dynamics and Monte Carlo Simulation Study

Contrary to thermosets, vitrimers adjust their topology upon heating without loss of network integrity. Here, the proposed simulation methodology utilizes coarse-grained molecular dynamics in conju...

Failure analysis of fretting fracture in frame rails of heavy duty trucks – Case study

This paper analyzed fatigue fracture of a frame rail during accelerated endurance test of a heavy duty truck. This fracture was noted in an area of high shear stresses where contact and fretting fatigue was suspected. A cross section through the fracture initiation site showed areas of surface contact wear in the microstructure. Fretting wear resulted in crack initiation and propagated to form a through crack under reverse bending fatigue crack growth mechanism. A combination of crack growth simulation tool (FRANC3D) and finite element analysis solver (MSC NASTRAN) was used and automated to handle multiple crack growth iterations. The simulation results obtained showed good correlation to failure crack path and cycles to failure. These simulation results were also used to understand the root cause of failure, identify critical parameters causing failure and recommend design modifications to prevent fretting fatigue in frame of heavy duty trucks. A modified design using the proposed simulation methodology was identified and was shown to provide improved frame durability.

Prediction of surface variation field in face milling via finite element model updating with considering force-deformation coupling

Effective prediction of surface variation is of great helpf for developing and controlling machining process to maintain surface quality during face milling of large-scale component with discontinuous surface. However, the simulation ranges of machined surface error in traditional finite element analyses are far less than those needed in characterization of large-scale face milling with multi-tooth cutter in order to maintain efficiency. To address this issue, this paper attempts to develop a numerical methodology to estimate the field data of machined surface error based on iterative finite element analysis integrated with cutting trajectory reconfiguration. Finite element model updating (FEMU) method is applied to analysis the cutting deformation in each cutting instant while considering both the cutting force variation in face milling and the locally geometrical differences of component. A flexible model is established to predict the residual cutting material in each cutting instant with considering the coupling effect between instantaneous cutting force and cutting deformation. And then a sub-iteration scheme is proposed to calculate the equilibrium deflection and the real residual material of flexible cutting system with a modified Newton-Raphson method. The proposed simulation methodology can be generally applied for predicting surface variation field in face milling of large-scale component with multi-holed surface, especially for flexible component.

Performance Evaluation and Interference Characterization of Wireless Sensor Networks for Complex High-Node Density Scenarios.

The uncontainable future development of smart regions, as a set of smart cities’ networks assembled, is directly associated with a growing demand of full interactive and connected ubiquitous smart environments. To achieve this global connection goal, large numbers of transceivers and multiple wireless systems will be involved to provide user services and applications anytime and anyplace, regardless the devices, networks, or systems they use. Adequate, efficient and effective radio wave propagation tools, methodologies, and analyses in complex indoor and outdoor environments are crucially required to prevent communication limitations such as coverage, capacity, speed, or channel interferences due to high-node density or channel restrictions. In this work, radio wave propagation characterization in an urban indoor and outdoor wireless sensor network environment has been assessed, at ISM 2.4 GHz and 5 GHz frequency bands. The selected scenario is an auditorium placed in an open free city area surrounded by inhomogeneous vegetation. User density within the scenario, in terms of inherent transceivers density, poses challenges in overall system operation, given by multiple node operation which increases overall interference levels. By means of an in-house developed 3D ray launching (3D-RL) algorithm with hybrid code operation, the impact of variable density wireless sensor network operation is presented, providing coverage/capacity estimations, interference estimation, device level performance and precise characterization of multipath propagation components in terms of received power levels and time domain characteristics. This analysis and the proposed simulation methodology, can lead in an adequate interference characterization extensible to a wide range of scenarios, considering conventional transceivers as well as wearables, which provide suitable information for the overall network performance in crowded indoor and outdoor complex heterogeneous environments.

Computer-Aided Material Design for Crash Boxes Made of High Manganese Steels

During the last decades, high manganese steels (HMnS) were considered as promising materials for crash-relevant automobile components due to their extraordinary energy absorption capability in tensile tests. However, in the case of a crash, the specific energy, absorbed by folding of a crash box, is lower for HMnS as compared to the dual phase steel DP800. This behavior is related to the fact that the crash box hardly takes advantage of the high plastic formability of a recrystallized HMnS during deformation. It was revealed that with the help of an alternative heat treatment after cold rolling, the strength of HMnS could be increased for low strains to achieve a crash behavior comparable to DP800. In this work, a multi-scale finite element simulation approach was used to analyze the crash behavior of different material conditions of an HMnS. The crash behavior was evaluated under consideration of material efficiency and passenger safety criteria to identify the ideal material condition and sheet thickness for crash absorption by folding. The proposed simulation methodology reduces the experimental time and effort for crash box design. As a result of increasing material strength, the simulation exhibits a possible weight reduction of the crash box, due to thickness reduction, up to 35%.

Particles aggregation and fragmentation — A Monte Carlo study

Molecular simulation of particles aggregation is a time-intensive computation. In this study, we have developed a computational methodology to simulate the aggregation and fragmentation of particles. Scaling relations are developed that can be used to decrease the number of primary particles towards minimization of the computation time. The developed methodology is applied to reproduce the experimental data of particles aggregation and fragmentation. Results show the capability of the proposed methodology to represent the experimental data. Then, the model is applied to predict the onset of precipitation, the amount of precipitated particles, and their particles size distribution. The simulation results are in agreement with the experimental data. The proposed simulation methodology and the scaling relations find applications in simulation of particles aggregation and fragmentation.

Simulating Crop-Water Production Functions Using Crop Growth Models to Support Water Policy Assessments

Crop-water production functions are important tools for quantifying effects of water scarcity and climate change on agricultural production, and are also widely used within hydro-economic models to support design of inter-sectoral water management policies. Here, we introduce a new methodology for simulating crop-water production functions using process-based crop growth models, which captures explicitly the interacting effects of farmers' intraseasonal irrigation decision-making, stochastic weather conditions, and physical and socio-economic water supply constraints on seasonal crop yield response to water. Through a case study application for groundwater irrigated corn production in the Texas High Plains, we demonstrate that constraints to irrigation scheduling caused by aquifer depletion, combined with farmers' limited foresight of future weather conditions, have significant impacts on estimated seasonal crop-water production functions. Our results highlight that the failure to account for these factors fully in previous simulation approaches will lead to errors in estimates of the impacts of groundwater depletion on farmers' future resilience to drought and climate change. Our proposed simulation methodology is generalizable to different production systems or crop growth models, and provides a tool for assessing how economic benefits derived from irrigation vary spatially and temporally due to heterogeneity in biophysical conditions and irrigation practices.

Simulation methodology and performance analysis of network coding based transport protocol in wireless big data networks

The Multi-Path, Multi-Hop (MPMH) communications have been extensively used in wireless network. It is especially suitable to big data transmissions due to its high throughput. To provide congestion and end-to-end reliability control, two types of transport layer protocols have been proposed in the literature: the TCP-based protocols and the rateless coding based protocols. However, the former is too conservative to explore the capacity of the MPMH networks, and the latter is too aggressive in filling up the communication capacity and performs poorly when dealing with congestions. To overcome their drawbacks, a novel network coding scheme, namely, Adjustable Batching Coding (ABC), was proposed by us, which uses redundancy coding to overcome random loss and uses retransmissions and window size shrink to relieve congestion. The stratified congestion control strategy makes the ABC scheme especially suitable for big data transmissions. However, there is no simulation platform built so far that can accurately test the performance of the network coding based transport protocols. We have built a modular, easy-to-customize simulation system based on an event-based programming method, which can simulate the ABC-based MPMH transport layer behaviors. Using the proposed simulator, the optimal parameters of the protocol can be fine-tuned, and the performance is superior to other transport layer protocols under the same settings. Furthermore, the proposed simulation methodology can be easily extended to other variants of MPMH communication systems by adjusting the ABC parameters.

Stochastic Modeling of FinFET Degradation Based on a Resistor Network Embedded Metropolis Monte Carlo Method

This paper presents a comprehensive stochastic simulation approach combining resistor network embedded metropolis Monte Carlo method and the finite-element method for modeling FinFET oxide degradation. The geometrical impact of the 3-D structure is linked with the stochastic model, and the simulation method can evaluate the degradation behavior of FinFET structures accounting for geometrical variations and multiphysics coupling effects. The leakage current, electric field, current density, and temperature distribution are simulated and show good agreement with electrical stress test data. The simulation results also indicate the need for a bimodal clustering model to best describe FinFET degradation and dielectric breakdown lifetime statistics. The proposed simulation methodology is generic enough to be fine-tuned for reliability modeling of other logic and nonvolatile memory devices in the future.