Simple Modeling Approach Research Articles

Analysis of PMSM NVH performance in electric propulsion systems using FE models

The stator of the PMSM is the main transfer path for the Electro Magnetic (EM) force from stator teeth to the drive unit (DU) through its mounting ears. First, a FE model of full winding stator model along with connection ring is analyzed for modal behaviors. Time domain EM force excitations are converted into frequency domain and applied at the stator teeth. This enables stator mounting forces analysis at all critical NVH orders. Next, the detailed FE modelling approach is compared with response calculated form a simplified modelling approach, with stator end windings modelled as lumped mass and inertia to reduce computational time. The comparison study of two approaches clearly shows the benefits of using simplified FE models for studying motor whine with reduced modelling and computational costs. Furthermore, the frequency-dependent stator damping measured from modal test is applied in electric DU analysis to evaluate NVH performance excited by motor EM force excitations using simplified stator model. The sound power level radiated from the DU and the mount vibration response show negligible influence of stator damping at DU unit level NVH response in the low frequency range. Analysis and test results correlate reasonably well at the dominant motor whine orders for the DU, which validates the proposed method.

On the influence of tool contact stress on tensile instabilities in plane strain stretching and bending of sheet metals

It is well known that the widely used forming limit curve (FLC) based upon in-plane stretching fails to account for the delay in plastic instability in the presence of appreciable bending and tool contact pressure. The recently proposed General Incremental Stability Criterion (GISC) – a generalization of the Modified Maximum Force Criterion (MMFC) to triaxial loading – revealed the dependence of the boundary conditions on the formation of tensile instabilities. Nevertheless, it remains unclear how the combined effect of radial bending stresses and tool contact pressure affects the formation of an acute neck. It is shown in this study that a compressive normal stress causes a shift of the strain state from initial plane strain tension to positive minor strains for material layers within the cross-section. The convex (outer) layer remains in a state of plane strain-plane stress. Accounting for the shift in the strain state is key to capture the dependence of the contact pressure on necking. A simplified modelling approach, which enforces plane strain tension of the cross-section, was able to capture the formability gain due to bending but failed to account for the delay in plastic instability due to the contact pressure. An incremental multi-layer model was required to account for non-monotonic loading due to bending over the punch and the biaxial shift in the strain path caused by the contact pressure. The models were then applied to the experimental forming limits of a 3rd Gen 1180 advanced high strength steel to demonstrate the formability gains under triaxial loading due to the contact pressure.

A simplified modeling approach for optimization of urban river systems

Effective strategies for operating gates and pumping stations can help urban river systems to better control flooding. However, the computing cost of optimizing urban river systems prevents their application to large-scale problems. We propose a new simplified approach to urban river system optimization that allows a portion of the river network to be simulated, while the remainder is represented by a simplified model consisting of multiple surrogate models. The surrogate model reflects changes at the boundaries of the region of interest at prediction points within the system. To verify the accuracy of the simplified model, a numerical model based on storm water management model (SWMM) is established. The accuracy of the numerical model, the surrogate model and the simplified model were tested by multiple precipitation events. The average simulation time has been reduced by 574 times, demonstrating that the simplified model has effectively replaced the urban river network. This method is used to optimize multi-objective flood control in coastal cities. By adjusting the opening and closing state of 28 gates and pumping stations, the water level of 4 observation sections is controlled. The results show that 60% of the flood volume and 84% of the flood duration of the observed section are reduced, indicating that this method can better control the flooding process of the section. Compared with the numerical model, the calculation time is reduced by 184 times, indicating that the proposed method can solve the problem of long calculation time for urban river system optimization. This approach will reduce the risk of flooding in cities.

A simplified numerical method for modelling the wind flow and ventilation at urban-scale street network

Street networks serve as the main open corridors for wind flow within urban areas, so understanding their ventilation performance and capacity of removing pollutants helps improve urban air quality. However, conventional modelling methods using an exact building model (EBM) are hard-pressed to simulate urban-scale areas, due to their extremely high computing load. To reduce time and cost of numerical simulations, and accurately predict the flow field and ventilation within the street network, a simplified modelling approach (i.e., EBM&PMM) is proposed, in which only the first row of buildings flanking the street is modelled by EBM and the rest of the urban buildings are modelled by a porous media model (PMM). The performance of EBM&PMM is evaluated by three common modelling approaches, i.e., EBM, PMM, and sealed concrete model (SCM) in which the building complexes with gaps are treated as an enclosed entity. A typical crossing street network flanked by four communities (building arrays) is used for this study. The age of air (τP) and ventilation flux (Q) obtained from the four modelling methods are compared. The results show that EBM&PMM predicts τP and Q well, and the flow pattern by this model agrees well with EBM. PMM significantly underestimates τP but exaggerates Q in street networks, and it fails to give the detailed flow patterns. SCM over-predicts τP, and Q between the community and street is zero. Furthermore, the first row of buildings facing the street plays a decisive role in flow pattern and ventilation effectiveness of the street network.

Modeling Soil Organic Carbon Dynamics of Arable Land across Scales: A Simplified Assessment of Alternative Management Practices on the Level of Administrative Units

Regional assessments of soil organic carbon (SOC) trends and the carbon sequestration potential of alternative management practices (AMP) are highly relevant for developing climate change mitigation strategies for the agricultural sector. Such studies could benefit from simplified SOC modeling approaches on the scale of administrative units as this often corresponds to the level of policy-making and data availability. However, there is a risk of systematic errors in such scaling operations. To overcome this problem, we performed a scaling experiment where we simulated the SOC dynamics of the arable soils of the State of Saxony (Germany) across a series of scales using the CANDY Carbon Balance (CCB) model. Specifically, we developed model set-ups on four different administrative levels (NUTS1, NUTS2, NUTS3, and LAU) and evaluated the simulation results of the upscaled models against a 500 m grid-based reference model. Furthermore, we quantified the carbon sequestration potential of selected AMP scenarios (addressing field grass, cover crops, and conservation tillage) across all scales. The upscaled model set-ups adequately simulated the SOC trends of Saxon arable land compared to the grid-based reference simulation (scaling error: 0.8–3.8%), while providing significant benefits for model application, data availability and runtime. The carbon sequestration potential of the AMP scenarios (1.33 Mt C until 2050) was slightly overestimated (+0.07–0.09 Mt C) by the upscaled model set-ups. Regardless of the scale of model set-up, we showed that the use of aggregated statistical input data could lead to a systematic underestimation of SOC trends. LAU and NUTS3 levels were shown to be a suitable compromise for effectively quantifying SOC dynamics and allowed for an acceptable spatial prioritization of AMPs. Such simplified, scale-adapted assessments are valuable for cross-regional comparisons and for communication to and among decision-makers, and might provide a quantitative basis for discussions on the effectiveness of AMPs in various stakeholder processes.

Modeling of shear-lap tests of flat and curved masonry specimens strengthened by FRCM

Nowadays Fiber Reinforced Cementitious Matrix (FRCM) systems play a relevant role in the context of innovative interventions for the seismic rehabilitation of masonry structures. Their capacity in improving the strength of masonry components is comparable with the one observed in case of Fiber Reinforce Polymer (FRP) systems, but with additional advantages (lower costs, environmental compatibility, removability, etc.). Nevertheless, although a relevant number of applications concerns curved structures (arches, vaults, domes, etc.), the majority of studies available in literature provide a contribution mainly concerning the specific case of applications on flat masonry substrates. The present paper is part of a research activity carried out by the Authors with the main goal to provide a contribution toward the study of the bond behavior of FRCM systems externally applied to curved masonry elements. In particular, the results of numerical analyses carried out by means of a simple modeling approach proposed by the Authors are here carried out by considering as case studies specimens object of a recent experimental investigation. Specific aspects influencing the local bond behavior of FRCM systems applied on curved masonry substrates are then analyzed by opportunely introducing them into the numerical model. The obtained results allow for understanding the effect of important features, experimentally observed in terms of global response, and here assessed in terms of local bond behavior, by particularly emphasizing the role of the curvature and the strengthening position.

Calibration of FEM models of historic masonry structures and its application on a local historic structure

Masonry structures may be of different kinds, including stone, brick and other masonry blocks assembled in different ways using mortar. For study of such structures, modelling them is necessary which can be done in two ways, either by modelling large classes of masonry as single units (Simple Model) or by regular arrangement of blocks and the interaction between blocks and mortar (Refined Model). Simple Model approach takes crude material assumptions and produces results affected by large approximations, while the second approach is sophisticated and close to reality. The present research deals with the creation of a method for modelling of Finite Element Models of masonry buildings through their fast regenerative modelling in an environment offered by Rhinoceros 3D and Grasshopper. Since exact modelling of such structures is complicated and time-consuming, macro modelling of such structures is carried out by simplistic assumptions of the structural system as load bearing walls. Simple architectural plans of each storey may be imported from AutoCAD to Rhinoceros 3D, scaled according to the dimensions. These can then be assigned as geometry in Grasshopper and extruded in Z-direction (according to storey height) to get the basic volume of the curves. The plan of each storey can then be placed on top of one another by maintaining a distance equal to the storey height and the whole 3D model may be created. These models are user friendly and consume very less time, if definitions for extrusion and openings etc. are created beforehand in Grasshopper, and can be used for multiple structures. Such macro models are then used for simple static analysis by using a similar script in Grasshopper or may be imported to other Finite Element Analysis (FEA) softwares.

OutSingle: a novel method of detecting and injecting outliers in RNA-Seq count data using the optimal hard threshold for singular values.

Finding outliers in RNA-sequencing (RNA-Seq) gene expression (GE) can help in identifying genes that are aberrant and cause Mendelian disorders. Recently developed models for this task rely on modeling RNA-Seq GE data using the negative binomial distribution (NBD). However, some of those models either rely on procedures for inferring NBD's parameters in a nonbiased way that are computationally demanding and thus make confounder control challenging, while others rely on less computationally demanding but biased procedures and convoluted confounder control approaches that hinder interpretability. In this article, we present OutSingle (Outlier detection using Singular Value Decomposition), an almost instantaneous way of detecting outliers in RNA-Seq GE data. It uses a simple log-normal approach for count modeling. For confounder control, it uses the recently discovered optimal hard threshold (OHT) method for noise detection, which itself is based on singular value decomposition (SVD). Due to its SVD/OHT utilization, OutSingle's model is straightforward to understand and interpret. We then show that our novel method, when used on RNA-Seq GE data with real biological outliers masked by confounders, outcompetes the previous state-of-the-art model based on an ad hoc denoising autoencoder. Additionally, OutSingle can be used to inject artificial outliers masked by confounders, which is difficult to achieve with previous approaches. We describe a way of using OutSingle for outlier injection and proceed to show how OutSingle outperforms its competition on 16 out of 18 datasets that were generated from three real datasets using OutSingle's injection procedure with different outlier types and magnitudes. Our methods are applicable to other types of similar problems involving finding outliers in matrices under the presence of confounders. The code for OutSingle is available at https://github.com/esalkovic/outsingle.

Analysis of radionuclide retention by the cement hydrate phase portlandite: A novel modelling approach

Cement is a widely used material for conditioning and confining radioactive waste; thus, the analysis of its sorption properties as well as of those of its main hydration products is crucial to assess radionuclide migration under disposal conditions.In this study, the sorption of radioisotopes with different chemical properties (137Cs, 133Ba, 109Cd, 152Eu, 238Pu, 75Se and 36Cl) in portlandite suspended in 20 mM Ca(OH)2 (pH = 12.5 ± 0.2) was analyzed by means of batch sorption isotherms. In the range of the concentrations investigated, all the radionuclides showed a linear adsorption isotherm. Almost quantitative adsorption was observed for Eu, Pu and Cd, with a very high logarithm of the distribution coefficient, Kd [g·mL−1] (log(Kd) > 5). The adsorption of the cations Cs and Ba was significantly smaller, with a log(Kd) of approximately 2 and 0.3 respectively. The two anionic species analyzed were Cl− and SeO32−: whereas Cl did not show any retention, selenite showed a Log(Kd) of approximately 1.8. The precipitation of Se is observed for aqueous concentrations higher than 1·10−4 M, being the precipitation of CaSeO3(s) predicted by thermodynamic calculations.The electrokinetic surface potential of portlandite was analyzed as a function of pH (10–13.5) and with and without the presence of alkalis (0.2 M Na) to gather the basic information needed for understanding radionuclide/solid interactions and sorption modelling. The portlandite charging behaviour could be explained assuming calcium as the main ion determining the potential. This is the first time that a surface model for portlandite is proposed.A simplified double layer modelling approach was proposed to describe experimental data, identifying the most probable sorbing species under the geochemical conditions generated by portlandite, and all the adsorption isotherms could be satisfactorily reproduced the model.

Addressing misclassification bias in vaccine effectiveness studies with an application to Covid-19

Safe and effective vaccines are crucial for the control of Covid-19 and to protect individuals at higher risk of severe disease. The test-negative design is a popular option for evaluating the effectiveness of Covid-19 vaccines. However, the findings could be biased by several factors, including imperfect sensitivity and/or specificity of the test used for diagnosing the SARS-Cov-2 infection. We propose a simple Bayesian modeling approach for estimating vaccine effectiveness that is robust even when the diagnostic test is imperfect. We use simulation studies to demonstrate the robustness of our method to misclassification bias and illustrate the utility of our approach using real-world examples.

Multi-layer modelling of masonry structures strengthened through textile-reinforced mortar.

Background Textile-reinforced mortar (TRM) is an innovative strategy for the reduction of the seismic vulnerability of existing masonry buildings consisting in the application on the masonry surface, of a mortar coating with fiber-based grids or textiles embedded. The paper presents the calibration and application of a simplified modelling approach, based on multi-layered elements, for the simulation of existing masonry elements and structures strengthened through TRM. Methods The strengthened masonry is modelled by using 20-nodes brick elements formed by a stacking sequence of layers representing the different material components (the masonry, the mortar coating and the embedded reinforcement). The nonlinear behavior of the materials is considered and calibrated on the basis of experimental characterization tests on individual components available in the literature. The simplified assumption of perfect bond among layers is considered. Results Non-linear static analyses are performed on samples of increasing complexity: elementary panels, structural elements (piers and spandrels) and a pilot building. The results of some tests on TRM strengthened masonry, available in the literature, are considered to assess the model reliability in terms of capacity curves and collapse mode. The model is capable of detecting the typical failure mechanism of both unstrengthened and TRM strengthened masonry, namely the diagonal cracking, the in-plane bending and the out-of-plane bending and is able to detect the activation also of mixed failure modes, that often occur in actual configurations. Conclusions Given the coarse mesh size and the smear plasticization assumption, the model is not suitable for the rigorous reproduction of individual cracks but represents a good compromise between the goal to grasp the structural performances at the wide scale, including failure modes, and the analysis optimization.

Using On-Site Measurements to Identify and Adjust PV Single-Diode Model Parameters for Real Operating Conditions

Photovoltaic (PV) module manufacturers specify their products’ performance under the standard test condition. However, such a condition is hardly found outdoors, that is, during actual operation of photovoltaic systems. Despite that, many modeling methods proposed in the literature rely on standard test condition data for parametric identification. This paper presents an experimental study concerning different modeling approaches for photovoltaic modules, focusing on assessing model performance in different scenarios. The goal is to assess the influence of the data used for the model parametric adjustment when predicting the maximum power point of two photovoltaic modules, allowing the most advantageous methods to be identified. By using an experimental outdoor photovoltaic platform, over 30,000 I-V curves referring to two photovoltaic modules were measured for 16 months. Different models were applied for cases where their parameters were identified using field measurements. It was found that using measurements obtained under real operating conditions to adjust the model parameters provides significantly better prediction of the maximum power in comparison to cases employing data sheet-extracted information. For the all methods and cases studied, using in-field measurements to adjust the model parameters provided average root-mean-square error of 3.4% for power predictions, whereas the average error level found when using data sheet information was 8.8%. An error level as low as 2.83% was reached by adopting the most complex model, although using a significantly simpler modeling approach provided error of 3.25%. Therefore, using field-measured data to adjust model parameters produced the best results, but increasing method complexity did not increase performance in the same scale.

Of clockwork and catastrophes: advances in spatiotemporal dynamics of forest Lepidoptera.

We applied a systematic global literature survey from the last 2.5 years on spatiotemporal population dynamics - broadly defined - of Lepidopteran forest pests. Articles were summarized according to domain-specific (planetary ecology - remote sensing,evolutionary ecology - genetics and genomics,and theoretical ecology - modeling) contributions to contemporary investigation of the above theme. 'Model systems' dominating our literature survey were native Choristoneura fumiferana and invasive Lymantria dispar. These systems represent opposing ends of a more general equilibrium-disequilibrium gradient, with implications for less-studied taxa. Thedynamics of Lepidopteran systems defy simple modeling approaches. Technologies and insights emerging from 'slower' science domains are informing more complex theory, including predictions of spread, impacts, or both posed by more recent invasions and the disrupting effects of climate change.

As simple as possible but not simpler?: the case of irrigation modeling at catchment scale in southwestern France

The estimation of irrigation water requirements (IWR) amount and timing is crucial for designing water management strategies at the regional scale. Irrigation requirements can be estimated with different types of models: very complex and detailed crop models, agent-based models, or simplified modeling approaches. Because simplified approaches are often preferred, in this study, we evaluate the consequences of using simplified approaches for IWR assessment at a catchment scale and the consequences of various modeling choices, providing information on the uncertainties. To this end, different simple modeling approaches based on the CropWat model are compared with an agent-based approach (MAELIA), which serves as a benchmark. To assess simulations in detail, partial variance is calculated for several indicators characterizing daily simulated irrigation. Our sensitivity analysis, applied over a sub-catchment of the Aveyron River (southwestern France), shows a high variability in simulations produced by CropWat between the modeling assumptions tested, principally explained by the rules for irrigation triggering and the quantification of daily irrigation. The analysis also shows that several simplified approaches are able to reproduce the irrigation simulated by the high-accuracy MAELIA model, but not necessarily corresponding to an optimal irrigation scheme. Hence, this study confirms the possibility of assessing daily irrigation with simplified approaches, but warns about high modeling uncertainties, reflecting uncertainty in effective irrigation practices. This uncertainty can be taken into account by water managers and modelers through the combination of a set of irrigation models.

Updated repository for "Reconstructing sediment distributions in meandering river deposits through a simplified numerical modelling approach with applications to the Holocene deposits of the Venetian Plain (Italy)"

Updated repository for "Reconstructing sediment distributions in meandering river deposits through a simplified numerical modelling approach with applications to the Holocene deposits of the Venetian Plain (Italy)"

Repository 2 for "Reconstructing sediment distributions in meandering river deposits through a simplified numerical modelling approach with applications to the Holocene deposits of the Venetian Plain (Italy)"

Repository 2 for "Reconstructing sediment distributions in meandering river deposits through a simplified numerical modelling approach with applications to the Holocene deposits of the Venetian Plain (Italy)"

How Can Machine Learning Advance Quantitative Asset Management?

The emerging literature suggests that machine learning (ML) is beneficial in many asset pricing applications because of its ability to detect and exploit nonlinearities and interaction effects that tend to go unnoticed with simpler modelling approaches. In this article, the authors discuss the promises and pitfalls of applying machine learning to asset management by reviewing the existing ML literature from the perspective of a prudent practitioner. The focus is on the methodological design choices that can critically affect predictive outcomes and on an evaluation of the frequent claim that ML gives spectacular performance improvements. In light of the practical considerations, the apparent advantage of ML is reduced, but still likely to make a difference for investors who adhere to a sound research protocol to navigate the intrinsic pitfalls of ML.

Water Disappearance and Manure Production at Growing–Finishing Commercial Pig Farms in Brazil—A Simplified Model Approach

The aim of this study was to fit water disappearance and manure production curves at growing–finishing commercial pig farms and compare the curve that best describes the evolution of parameters evaluated, according to three variables: age, body weight, and pigs’ housing period. Accordingly, 33 production cycles were evaluated considering a housing period of 105 days (13,276 pigs—nine weeks old and 24.5 kg average body weight) during 13 months in 15 commercial pig farms located in southern Brazil. The variables analyzed were used to adjust the water disappearance and manure production curves (Brody, Gompertz, Logistic, Richards, and Von Bertalanffy) and to estimate its biological parameters according to the NLMIXED SAS procedures. It was found that the Logistic model was the one that best described both the water disappearance and the manure production, displaying an asymptotic adjustment and estimated values measured in farms, e.g., pigs age (water: R² = 0.989, absolute error: 1.11 L/pig/day, and prediction error = 1.32%; manure: R² = 0.995, absolute error = 0.04 L/pig/day, and prediction error = 0.96%). It is emphasized that the models determined in this research are the basis of the development of an instantaneous measuring device that allows the producer to visualize both the water disappearance (plotting the daily measures) as well as manure production in the farm and compare the values with the estimated curves.

Phase changes in cementitious materials exposed to saline solutions

This article summarizes long-term degradation mechanisms of cementitious materials in contact with fresh and saline solutions based on a review of experimental observations in field and laboratory studies. In addition, a simplified thermodynamic modelling approach was used to calculate the effect of the solution composition, ranging from river water to sea water, on the intensity of leaching and the kind and quantity of phases formed at the interface with the environment. This study shows that leaching is the main underlying degradation mechanism for all investigated exposure solutions. The presence of carbonates and sulphates in the solution increases leaching and decalcification of Ca-rich phases leading to the precipitation of calcium carbonate and calcium sulfate, while the presence of chloride has little influence on the intensity of leaching. Carbonates in the interacting solution can suppress ettringite formation. If present, magnesium precipitates as brucite, M-S-H or hydrotalcite-like phase.

Modeling of sodium-cooled fast reactor core – A sensitivity study on number of core channels and axial meshes

System thermal–hydraulic codes are used in the dynamics analysis of sodium-cooled fast reactors (SFRs). In such simulations, the accuracy of the reactor core model is very important to establish plant safety. Coupled physical phenomena, namely, heat transfer, fluid dynamics, and neutronics, need to be simulated in the core. Due to the complexity, a simplified core modeling approach has been traditionally followed in system dynamics codes. Firstly, steady-state core neutronics calculations are carried out using a 2D axisymmetric model to obtain perturbation worth and power distributions. Later, this data is mapped to several core channels (usually 10 to 20), each representing a set of fuel subassemblies (SAs) for thermal-hydraulics calculations.In this paper, a more sophisticated core modeling approach has been followed to understand the importance of such an exercise. A 3D neutronics model was used to obtain subassembly-wise perturbation worths and power distributions. For thermal-hydraulics calculations, the number of core channels was increased with the idea of one subassembly per channel. The number of axial meshes in each channel was also increased. The traditional and new modeling approaches were used to simulate the benchmark problem of FFTF LOFWOS test#13 for comparison. Steady-state parameters from both the new and the old models were comparable. Notably, there was a peaking of the axial power profile in the new model compared to the old model, which resulted in slightly higher peak fuel temperatures in the new model. However, the difference in the evolution of transient parameters between the two models was insignificant, and both models compared reasonably well with the benchmark data.