Validation Of Simulation Model Research Articles

Simulation of local metastable microstructural states in large tools: construction and validation of the model

This study presents the development and experimental verification of a simulation model for estimating the local microstructure of a tool geometry after heat treatment. The experiment involved subjecting a metallic block of dimensions 40 × 50 × 50 mm, made of the ledeburitic cold work steel DIN EN 1.2379 (X153CrMoV12; AISI D2), to a heat treatment in a laboratory furnace at 1000 °C for 20 min. Thermocouples were strategically placed to record time-temperature profiles at different locations within the block. Following the heat treatment, the local microstructure was determined through quantitative image analysis, and the local hardness was measured as a function of the distance from the block’s edge to its core. These measurements were then correlated with the corresponding time-temperature curves obtained from the thermocouples. To replicate the local time-temperature profiles, the thermophysical properties of the steel were experimentally determined and incorporated into a finite element analysis heat transfer simulation using Abaqus FEA® software. This simulation approach, combined with the MatCalc software, facilitated the calculation of various local microstructural characteristics such as carbide content, carbide type, carbide distribution, and chemical composition of the matrix. Furthermore, the content fractions of the microconstituents of the matrix, including martensite and retained austenite, were determined based on the simulated martensite start temperature, employing an optimized function fitted to experimental data. The developed simulation model offers potential applications in two important areas. Firstly, it can be used to adapt heat treatment processes for tools of different sizes in production, optimizing their mechanical properties. Secondly, it enables efficient optimization of heat treatment routes by considering changing initial states, leading to high process quality in terms of mechanical properties. Overall, this study provides valuable insights into the estimation and control of local microstructure in tool geometries through the use of a validated simulation model.

Validation of Models for Net Deployment and Capture Simulation with Experimental Data

This work validates lumped-parameter models and cable-based models for nets against data from a parabolic flight experiment. The capabilities of a simulator based in Vortex Studio, a multibody dynamics simulation framework, are expanded by introducing i) a lumped-parameter model of the net with lumped masses placed along the threads and ii) a flexible-cable-based model, both of which enable collision detection with thin bodies. An experimental scenario is recreated in simulation, and the deployment and capture phases are analyzed. Good agreement with experiments is observed in both phases, although with differences primarily due to imperfect knowledge of experimental initial conditions. It is demonstrated that both a lumped-parameter model with inner nodes and a cable-based model can enable the detection of collisions between the net and thin geometries of the target. While both models improve notably capture realism compared to a lumped parameter model with no inner nodes, the cable-based model is found to be most computationally efficient. The effect of modeling thread-to-thread collisions (i.e., collisions among parts of the net) is analyzed and determined to be negligible during deployment and initial target wrapping. The results of this work validate the models and increase the confidence in the practicality of this simulator as a tool for research on net-based capture of debris. A cable-based model is validated for the first time in the literature.

Simulation of vertical dispersion and pollution impact of artificial light at night in urban environment

The use of artificial light at night (ALAN) enables social and commercial activities for urban living. However, the excessive usage of lighting causes nuisance and waste of energy. Light is provided to illuminate target areas on the street level where activities take place, yet light can also cause trespass to residents at the floors above. While regulations are beginning to cover light design, simulation tools for the outdoor environment have also become more popular for assessing the design condition. Simulation tools allow visualisation of the impact of the selected light sources on those who are affected. However, this cause-and-effect relationship is not easy to determine in the complex urban environment. The current work offers a simple methodology that takes site survey results and correlates them with the simulation model to determine lighting impact on the investigated area in 3D. Four buildings in two mixed commercial and residential streets in Hong Kong were studied. Data collection from each residential building requires lengthy work and permission from each household. Therefore, a valid lighting simulation model could help determine the light pollution impact in the area. A light model using DIALux is developed and calibrated by correlating the simulated data with the actual measured data. The correlation value R2 achieved ranged from 0.95 to 0.99, verifying the accuracy of this model and matched from 340 lx to 46 lx for the lower to higher floors of one building and 10 lx to 4 lx for floors of another building. This model can also be applied to human health research, by providing light-level data on residential windows in an area or determining the environmental impact of a development project.

Validation of inductively coupled plasma simulation model by laser Thomson scattering experiment

To comprehensively study the physical properties of inductively coupled plasma (ICP), a finite element method (FEM) simulation model of ICP is developed using the well-established COMSOL software. To benchmark the validation of the FEM model, two key physical parameters, the electron density and the electron temperature of the ICP plasma, are precisely measured by the state-of-the-art laser Thomson scattering diagnostic approach. For low-pressure plasma such as ICP, the local pressure in the generator tube is difficult to measure directly. The local gas pressure in the ICP tube has been calibrated by comparing the experimental and simulation results of the maximum electron density. And on this basis, the electron density and electron temperature of ICP under the same gas pressure and absorbed power have been compared by experiments and simulations. The good agreement between the experimental and simulation data of these two key physical parameters fully verifies the validity of the ICP FEM simulation model. The experimental verification of the ICP FEM simulation model lays a foundation for further study of the distribution of various physical quantities and their variation with pressure and absorption power, which is beneficial for improving the level of ICP-related processes.

Experimental and numerical investigation of the deep rolling process focussing on 34CrNiMo6 railway axles

Deep rolling is a powerful tool to increase the service life or reduce the weight of railway axles. Three fatigue-resistant increasing effects are achieved in one treatment: lower surface roughness, strain hardening and compressive residual stresses near the surface. In this work, all measurable changes introduced by the deep rolling process are investigated. A partly deep-rolled railway axle made of high strength steel material 34CrNiMo6 is investigated experimentally. Microstructure analyses, hardness-, roughness-, FWHM- and residual stress measurements are performed. By the microstructure analyses a very local grain distortion, in the range < 5 µm, is proven in the deep rolled section. Stable hardness values, but increased strain hardening is detected by means of FWHM and the surface roughness is significantly reduced by the process application. Residual stresses were measured using the XRD and HD methods. Similar surface values are proven, but the determined depth profiles deviate. Residual stress measurements have generally limitations when measuring in depth, but especially their distribution is significant for increasing the durability of steel materials. Therefore, a numerical deep rolling simulation model is additionally built. Based on uniaxial tensile and cyclic test results, examined on specimen machined from the edge layer of the railway axle, an elastic–plastic Chaboche material model is parameterised. The material model is added to the simulation model and so the introduced residual stresses can be simulated. The comparison of the simulated residual stress in-depth profile, considering the electrochemical removal, shows good agreement to the measurement results. The so validated simulation model is able to determine the prevailing residual stress state near the surface after deep rolling the railway axle. Maximum compressive residual stresses up to about -1,000 MPa near the surface are achieved. The change from the induced compressive to the compensating tensile residual stress range occurs at a depth of 3.5 mm and maximum tensile residual stresses of + 100 MPa at a depth of 4 mm are introduced. In summary, the presented experimental and numerical results demonstrate the modifications induced by the deep rolling process application on a railway axle and lay the foundation for a further optimisation of the deep rolling process.

Experimental study on the collapse response of flat slab structures with drop panels under gravity loading condition

This paper presents the results of an experimental study on the collapse behavior of two reinforced concrete flat slab assemblies with drop panel connections subjected to uniformly distributed loads applied through 24 loading points. The two tests, named MC and PC, simulated local failures at mid-span columns and penultimate columns, respectively. Both assemblies exhibited elastic behavior until cracking values were reached, followed by degradation of stiffness due to crack development beyond the elastic zone and a long plateau near collapse. The main differences between the assemblies were the higher collapse load of the MC assembly, attributed to slab additional slab extension surrounding two test panels, and the load redistribution pattern. Both assemblies showed ductile behavior in the inelastic region, with large deformation capacity allowing tensile membrane action to mobilize. The collapse modes observed were the failure of the outer compressive ring and the tearing out of tension slab reinforcement from the concrete. The traditional yield-line method may not be suitable for quantifying the collapse resistance of this type of structure, and numerical simulations are suggested for this purpose. The experimental data from these tests, as well as previous tests, could be valuable for validating simulation models.

Characterizing fatigue damage behaviors of concrete beam specimens in varying amplitude load

In this paper, the random and nonlinear mechanical characteristics of the composition distribution of concrete in each phase are investigated to solve the difficulty of fatigue damage test of concrete beam specimens under variable amplitude loading. A three-dimensional (3D) concrete composite random aggregate meso-model of concrete beam specimens is built with Digimat as a composite modeling tool. Subsequently, the bending-tensile strength and fatigue life of the model under four-point bending loading is analyzed and calculated using Abaqus finite element analysis model based on the concrete elastic-plastic damage criterion. The mechanical behaviors of concrete materials under static load failure, multistage fatigue loading, and random fatigue loading are studied. Finally, compared with the test results, the following conclusions are obtained. The random aggregate model and elastoplastic damage mechanics model of concrete composite constructed by concrete in Abaqus and Digimat can better describe the geometric and distribution characteristics of composite structure and aggregate in concrete beams and the mechanical behavior of fatigue and static load failure. The difference is 4.08 % with the experimental results, which verifies the validity and reliability of the numerical simulation model, and the fatigue life of concrete beams under random loading Sra and Srb is 1622 and 164 times, respectively. The research results have certain guiding significance and reference value for accurate calculation of bending and tensile strength of concrete beams under specified raw material and mix ratio and prediction of fatigue damage cracking in airport cement concrete pavement structure.

Development, Calibration, and Validation of a Large-Scale Traffic Simulation Model: Belgium Road Network

Development of large-scale traffic simulation models have always been challenging for transportation researchers. One of the essential steps in developing traffic simulation models, which needs lots of resources, is travel demand modeling. Therefore, proposing travel demand models that require less data than classical travel demand models is highly important, especially in large-scale networks. This paper first presents a travel demand model named as probabilistic travel demand model, then it reports the process of development, calibration and validation of Belgium traffic simulation model. The probabilistic travel demand model takes cities' population, distances between the cities, yearly vehicle-kilometer traveled, and yearly truck trips as inputs. The extracted origin-destination matrices are imported into the SUMO traffic simulator. Mesoscopic traffic simulation and the dynamic user equilibrium traffic assignment are used to build the base case model. This base case model is calibrated using the traffic count data. Al-so, the validation of the model is performed by comparing the real (extracted from Google Map API) and simulated travel times between the cities. The validation results ensure that the model is a superior representation of reality with a high level of accuracy. The model will be helpful for road authorities, planners, and decision-makers to test different scenarios, such as the im-pact of abnormal conditions or the impact of connected and autonomous vehicles on the Belgium road network.

Influence of the interfacial thermal resistance of a gadolinium/copper bimetal composite on solid-state magnetic refrigeration

The low heat transfer efficiency caused by a magnetocaloric material (MCM) with low thermal conductivity is the bottleneck that limits the performance of magnetic refrigeration (MR). Previous studies have shown that a bimetal composite of a high thermal conductivity material and an MCM is effective in improving the heat transfer rate. However, the bimetal composite structure causes extra interfacial thermal resistance (ITR). Therefore, this study investigates the processing of gadolinium/copper bimetal composites by fusion casting and experimentally determines the ITR. To evaluate the structural heat transfer capability, the equivalent thermal conductivity (keq) is proposed, which is calculated based on the ITR result and simulation. The influence of the ITR and keq on the cooling performance of a fully solid-state MR is carefully investigated using a validated simulation model. The results show that the smallest ITR of 3.74 × 10−5 m2 K W−1 is obtained with a copper pouring temperature of 1200 °C owing to the thinnest bonding interfacial layer. The topology-optimized structure, using the ITR obtained by fusion casting, has an keq of 159.8 W m−1K−1, with an increase of 39% compared to the structure assembled with thermal grease. As a result, the maximum specific cooling power (SCPmax) range and corresponding optimal operating range are significantly expanded to 45.6–209.3 W kg−1 and 0.23–0.61 rpm, respectively, with an average SCPmax increase of 35.5%. The combination of using topology optimization design to reduce the structural thermal resistance and using a suitable forming process to reduce the ITR can be more beneficial to the performance improvement of solid-state MR.

Experimental Research with Computer Simulation (Case Study Of Urban Cool Island)

This research will describe experimental research methodology using computer simulation with the case study of urban cool island research. The urban cool island is one of the urban heat island mitigation technology strategies. This technology uses a geometric and material intervention process that forms an urban cool island in an area with high urban heat island intensity. The urban cool island will expand and reduce the temperature of the hot islands so that the urban heat island gets smaller. In the research process, a series of experimental methodologies were carried out. Experimental methodology is carried out on a regional scale will be difficult and expensive. So a computer simulation is needed to facilitate urban cool island experiments in the area. The stages of experimental research with computer simulations use two process stages (1) Quasi-measurement experiments and field observations in the UCI area, (2) Validation of field measurements versus simulation models, (3) Experiments with computer simulations by creating test models and comparison models. The scope of research on the scale of urban areas with experimental methodology becomes efficient with the help of computer simulations. In Urban Cool Island, several countries have also used this methodology. Computer simulation used: ENVI-MET, CFD-Ansys, and others. Before starting the research, a clear frame or research design is needed, determining variables, replicating the real conditions, mastering the use of simulations, and always paying attention to the results, which are continuously controlled and validated to produce simulations that are close to the real conditions.

SAT-537 - Validation of a discrete event simulation model evaluating the cost-effectiveness of long-term albumin administration in real-world UK patients with recurrent ascites

SAT-537 - Validation of a discrete event simulation model evaluating the cost-effectiveness of long-term albumin administration in real-world UK patients with recurrent ascites

ANALYSIS OF PEDESTRIAN-TRAM COLLISION PHENOMENA: POSSIBILITIES OF SIMULATION MODELS VALIDATION

The article deals with the validation of the pedestrian simulation model as the initial study for future virtual testing of the tram front-end. The vision of virtual modeling approval is the main motivation of the study. The biofidelity of existing models was the subject of volunteer tests. The data are utilized for assessment of both adapted real anthropomorphic test device and presented simulation models created by means of commercial computer systems LS-DYNA and RADIOSS. Two basic tram front-end geometry were used in the pedestrian collision simulations. The resulting physical data are presented. The article demonstrates the complexity of the problem under study [Margaritis 2007] and confirms the correctness of the segment testing used in the automotive area.

Numerical Investigation of the Magnetic Alignment of Fe-Co-Coated Single Reinforcement Fibers

Fiber-reinforced composites are progressively more used in a variety of industrial applications. In recent years, carbon fiber-reinforced plastics have become increasingly popular, particularly in the aerospace sector because they offer outstanding mechanical properties combined with low weight. However, the orientation and distribution of the fibers have a significant effect on the mechanical and physical properties of the composite materials. Using conventional manufacturing technologies, it is not always technologically possible to adjust the fiber orientation to the load direction. One possible approach to targeted fiber alignment is the combination of classical manufacturing processes with a superimposed alignment mechanism so that the fibers can be oriented according to the load during component manufacturing. In this context, the orientation and distribution of short and long fibers through an external magnetic field seem to be well-suited to be integrated into the conventional manufacturing process of fiber-reinforced composites. Therefore, the generally non-magnetic reinforcement fibers, e.g. carbon or glass fibers, need to be modified or coated with magnetic materials. In this paper, carbon fibers coated with an iron-cobalt alloy are prepared by electrodeposition for the validation of simulation models developed in previous studies. Furthermore, numerical studies are presented in regard to the orientation of such fibers in polymeric matrices. Thus, simulative investigations of the orientability of coated carbon fibers in polymeric materials are shown and the works provide an important reference for future studies of fiber orientation and alignment using magnetic fields.

Numerical simulation of condensation heat transfer characteristics of R134a at high vapor velocity under different angles

Heat pipe is widely used as an efficient built-in heat exchanger for thermal management of high pulse and heat flux power supplies. Enhanced heat dissipation at the condensing side is an important issue in heat pipe research, where vapor velocity is an essential factor affecting the condensing heat transfer characteristics. This study adopted the CFD method to numerically simulate the condensation heat transfer of R134a flowing in a smooth pipe. The flow condensation heat transfer characteristics, such as film thickness and heat transfer coefficient (HTC), were investigated under vapor velocities v = 20–100 m/s and tube inclinations β =-90–90° Geometric and numerical heat transfer modeling is established in high vapor velocity flow condensation. The error of numerical simulation results and model validation is 10%. The HTC increases rapidly with the change in vapor velocity under 60 m/s, increasing the rate to 0.4. When the vapor velocity exceeds 60 m/s, the growth trend slows to 0.15, 37.5% of the original increase. At high vapor velocities above 60 m/s, the effect of pipe inclination on condensation heat transfer coefficient can be almost negligible. A modified empirical correlation suitable for high vapor velocities is proposed, which has higher predictive accuracy when the vapor velocity exceeds 80 m/s.

Digital Twin simulation models: a validation method based on machine learning and control charts

The adoption of simulation models as Digital Twins (DTs) has been standing out in recent years and represents a revolution in decision-making. In this context, we note increasingly faster and more efficient decisions by mirroring the behaviour of physical systems. On the other hand, we highlight the challenges to ensure the simulation models validity over time since traditional validation approaches have limitations when we consider the periodic update of the model. Thus, the present work proposes an approach based on the constant assessment of these models through Machine Learning and control charts. To this end, we suggest a monitoring tool using the K-Nearest Neighbors (K-NN) classifier, combined with a p-control chart, to periodically assess the validity of DT simulation models. The proposed approach was tested in several theoretical cases and also implemented in a real case study. The findings suggest that the proposed tool can monitor the DT functioning and identify possible special causes that could compromise its results. Finally, we highlight the wide applicability of the proposed tool, which can be used in different DT models, including near/real-time models with different characteristics regarding connection, integration, and complexity.

Numerically efficient two-step CFD simulation model of flow regime and heat transfer for hot water shower sterilizers

This work was carried out to create a numerically efficient validated simulation model for Hot Water Shower (SWS) sterilizers. The goal of the work was to achieve a more homogeneous temperature and water distribution inside the sterilizers developed in the future. A lab-scale test bench of an SWS sterilizer with a configurable water volume flow rate and temperature was designed to validate the Computational Fluid Dynamics (CFD) model that was created. The heating and cooling phases at water volume flow rates of 20 and 40m3/h per m2 spraying surface were analyzed. Additionally, the flow and film regime were studied. The CFD model was split into two simulation steps to significantly improve the numerical efficiency. The novel two-step approach developed is computationally 1800 times faster as compared with a complete sterilization cycle than a state-of-the-art approach. The simulated temperature of the test load was in good accordance with the experimental measurements. The flow regime was largely accurately replicated. Overall, the created validated CFD model is suitable for upscaling to an industry-sized SWS sterilizer due to its numerical efficiency.

Crashworthiness optimization for cutting energy-absorbing structures based on the multiobjective G-CBW method

The energy absorption structure of a train is an important part of passive safety protection during train collisions and is the last line of defense to protect both passengers and trains. In the design process of a train energy absorption structure, improved stability and greater energy absorption capacity is required. A cutting anti-climbing energy absorption structure offers good stability and energy absorption in a collision, but it can easily generate considerable heat in the energy absorption process. Therefore, it is important to conduct thermal–solid coupling simulations and crashworthiness optimization for cutting energy absorption structures. To improve the passive safety protection capability of high-speed trains, this paper experimentally and numerically explored the crashworthiness of a cutting-type energy-absorbing structure composed of an anti-creeper device, an energy-absorbing tube, cutting knives and knife-supporting tools. By adopting the Johnson–Cook material model, a finite element model was developed to study its energy absorption characteristics in a coupled heat–solid state. The effects of cutting depth (D), cutting knife front angle (A) and cutting width (W) on energy absorption (EA), cutting platform force (Fmean) and peak cutting force (PCF) were analyzed based on the validated simulation model. The results showed that EA, Fmean and PCF increase with increasing D and W, while EA, Fmean and PCF decrease with increasing A. The GRSM was employed as the optimization algorithm, and a gain matrix–cloud model optimal worst method (G-CBW) multiobjective decision algorithm was proposed to obtain the most satisfactory configurations from the Pareto front solution. The relative errors from the optimal and finite element results of EA, Fmean and PCF were 3.5%, 2.1% and 2.2%, respectively. All the crashworthiness indicators were improved considerably.

Hygrothermal performance optimization of lightweight steel-framed wall assemblies in hot–humid regions using orthogonal experimental design and a validated simulation model

As a layered construction, lightweight steel-framed (LSF) wall assemblies are applicable to different climates and used worldwide. Due to ill-informed construction and material designs, moisture-related durability problems occur, especially in hot–humid areas. Here, a hygrothermal simulation model of typical LSF wall assemblies was validated, and the influences of six construction layers (each with three sets of parameters) on the overall properties and performance were investigated via orthogonal experimental design (OED). Each layer exhibited various impact trends and contribution ratios at different positions. To reduce moisture risks, LSF wall assemblies should generally prevent the infiltration of outdoor moisture as much as possible while strengthening the inward drying capacity. The optimal configuration should comprise multiple water and vapour barriers with a ventilated layer, external insulation, permeable cavity insulation and interior sheathing board with a finish. Finally, this optimization method comprising the hygrothermal simulation and OED techniques could be applied to the hygrothermal performance of LSF wall assemblies under certain climatic conditions.

Sequential Likelihood-Free Inference with Neural Proposal

Bayesian inference without the likelihood evaluation, or likelihood-free inference, has been a key research topic in simulation studies for gaining quantitatively validated simulation models on real-world datasets. As the likelihood evaluation is inaccessible, previous papers train the amortized neural network to estimate the ground-truth posterior for the simulation of interest. Training the network and accumulating the dataset alternatively in a sequential manner could save the total simulation budget by orders of magnitude. In the data accumulation phase, the new simulation inputs are chosen within a portion of the total simulation budget to accumulate upon the collected dataset so far. This newly accumulated data degenerates because the set of simulation inputs is hardly mixed, and this degenerated data collection process ruins the posterior inference. This paper introduces a new sampling approach, called Neural Proposal (NP), of the simulation input that resolves the biased data collection as it guarantees the i.i.d. sampling. The experiments show the improved performance of our sampler, especially for the simulations with multi-modal posteriors.

In-situ flow visualization with Geo-Positron-Emission-Tomography in a granite fracture from Soultz-sous-Forêts, France

We investigate the fluid flow field in a fractured granite core sample. Sequential imaging with Positron-Emission-Tomography (PET) allows direct reconstruction of flow streamlines, thus providing a unique insight into the fluid dynamics of complex fractured crystalline materials. Pulse migration experiments using the positron-emitting radionuclide 18F− as tracer were conducted on a fractured granitic drill core, originating from a depth of 1958 m of the Enhanced Geothermal System (EGS) reference site at Soultz-sous-Forêts, France. The flow field was analyzed as a function of in- and outlet positions across the fracture, as well as applied flow rates. Different flow path characteristics were identified. Both the fracture aperture variation and the topography of the fracture surface affect the flow field with consequences on flow channeling and preferential flow paths. Furthermore, pulse migration experiments were also numerically simulated with a 2.5D model using COMSOL Multiphysics®.While the higher flow rate experiments show wider and higher dispersion of the flow path, lower velocity results in more localized flow and channeling behavior. This type of study thus yields enhanced experimental insights into the hydrodynamics of fracture flow and its relation to the rough structure of a single fracture, compared to input-output experiments. It can help to validate model simulations and experimentally determine hydrodynamic parameters needed for reactive transport modeling that are otherwise estimated with a high degree of uncertainty.