Comprehensive Modeling Method Research Articles

Modelling and protection of grotto temples based on iterative closest point and Poisson

As a non-renewable cultural heritage, grotto temples face many value threats and the crises of rapid extinction. Due to the unique environment, diverse volume and complex geometric structure of grotto temples, cultural relic protection faces huge challenges. Digitisation has become the most important and effective preventive protection method. This study proposes a comprehensive modeling method, which uses three-dimensional (3D) laser scanning technology to obtain the point cloud data of grotto ruins, close range photogrammetry to obtain multi-angle and high-resolution two-dimensional (2D) image data, and through the fusion modelling of the laser point cloud and image dense matching point cloud, a complete geometric model of grotto is obtained. The registration method of the improved algorithm is based on Euclidean distance residual. The performance is better, with residuals mainly distributed in the range of 0.02 to 0.03 mm. In terms of texture mapping, the accuracy of model mapping is adjusted by adjusting the constraints of control points. The gray values of 50 pixels around the control points show significant gradient changes in the X direction, while the changes in the Y direction are relatively small. These methods and technologies provide practical and effective means for the protection and preservation of cultural relics in grotto temples.

Measuring the worldwide spread of COVID-19 using a comprehensive modeling method

BackgroundWith the global spread of COVID-19, detecting high-risk countries/regions timely and dynamically is essential; therefore, we sought to develop automatic, quantitative and scalable analysis methods to observe and estimate COVID-19 spread worldwide and further generate reliable and timely decision-making support for public health management using a comprehensive modeling method based on multiple mathematical models.MethodsWe collected global COVID-19 epidemic data reported from January 23 to September 30, 2020, to observe and estimate its possible spread trends. Countries were divided into three outbreak levels: high, middle, and low. Trends analysis was performed by calculating the growth rate, and then country grouping was implemented using group-based trajectory modeling on the three levels. Individual countries from each group were also chosen to further disclose the outbreak situations using two predicting models: the logistic growth model and the SEIR model.ResultsAll 187 observed countries' trajectory subgroups were identified using two grouping strategies: with and without population consideration. By measuring epidemic trends and predicting the epidemic size and peak of individual countries, our study found that the logistic growth model generally estimated a smaller epidemic size than the SEIR model. According to SEIR modeling, confirmed cases in each country would take an average of 9–12 months to reach the outbreak peak from the day the first case occurred. Additionally, the average number of cases at the peak time will reach approximately 10–20% of the countries’ populations, and the countries with high trends and a high predicted size must pay special attention and implement public health interventions in a timely manner.ConclusionsWe demonstrated comprehensive observations and predictions of the COVID-19 outbreak in 187 countries using a comprehensive modeling method. The methods proposed in this study can measure COVID-19 development from multiple perspectives and are generalizable to other epidemic diseases. Furthermore, the methods also provide reliable and timely decision-making support for public health management.

Deciphering the function of Xiangsha-Liujunzi-Tang in enhancing duodenal mucosal barrier by inhibiting MC/Tryptase/PAR-2 signaling pathway in functional dyspepsia rats

Ethnopharmacological relevanceXiangsha-Liujunzi-Tang (XSLJZT) is a classical formula for treating the diseases of digestive system, which can effectively and significantly improve the symptoms of functional dyspepsia (FD) patients. The main function of XSLJZT is to benefit Qi and spleen, and harmonize stomach. Aim of the studyThe purpose of this study was to investigate the intervention effect of XSLJZT on duodenal mucosal injury in FD rats and the response mechanism of MC/Tryptase/PAR-2 signal pathway. Materials and methodsUltra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was employed to qualitatively and quantitatively identify the chemical component of XSLJZT. A comprehensive modeling method (iodoacetamide infusion + irregular diet + swimming exhaustion) was used to construct the FD rat model. XSLJZT decoction was given to intervene FD rats for 2 weeks. The indicators of digestive function including body mass, 3-h food intake, visceral sensitivity, gastric emptying rate and intestinal propulsion rate were routinely measured for FD rats. The pathological changes of duodenum and microstructure of intestinal epithelial cells were observed by HE staining and transmission electron microscopy respectively. The inflammatory factors (VCAM-1, IL-6, TNF-α, and ICAM-1) and histamine content were evaluated by enzyme-linked immunosorbent assay (ELISA). The expression levels of Tryptase, PAR-2, ZO-1, β-catenin, p–NF–κBp65 and p-ERK1/2 in duodenal tissues were measured by Western blot (WB) and immunofluorescence colony-staining (IFC). ResultsXSLJZT administration significantly improved the survival of FD rats, increased body mass and 3-h food intake, improved visceral sensitivity, and restored gastric emptying rate and intestinal propulsion rate. HE staining showed that XSLJZT recovered the structure of duodenal mucosal and reduced inflammatory infiltration. ELISA revealed that XSLJZT reduced the content of inflammatory factors (VCAM-1, IL-6, TNF-α, and ICAM-1) and histamine. In addition, WB and IFC uncovered that the protein levels of ZO-1 and β-catenin were up-regulated and MC/Tryptase/PAR-2 signaling pathway was inhibited by XSLJZT. ConclusionXSLJZT significantly improved the integrity of duodenal mucosa and decreased the inflammation in FD rats through the inhibition of MC/Tryptase/PAR-2 signaling pathway response.

Air quality and health co-benefits of climate change mitigation and adaptation actions by 2030: an interdisciplinary modeling study in Ahmedabad, India

Climate change-driven temperature increases worsen air quality in places where coal combustion powers electricity for air conditioning. Climate solutions that substitute clean and renewable energy in place of polluting coal and promote adaptation to warming through reflective cool roofs can reduce cooling energy demand in buildings, lower power sector carbon emissions, and improve air quality and health. We investigate the air quality and health co-benefits of climate solutions in Ahmedabad, India—a city where air pollution levels exceed national health-based standards—through an interdisciplinary modeling approach. Using a 2018 baseline, we quantify changes in fine particulate matter (PM2.5) air pollution and all-cause mortality in 2030 from increasing renewable energy use (mitigation) and expanding Ahmedabad’s cool roofs heat resilience program (adaptation). We apply local demographic and health data and compare a 2030 mitigation and adaptation (M&A) scenario to a 2030 business-as-usual (BAU) scenario (without climate change response actions), each relative to 2018 pollution levels. We estimate that the 2030 BAU scenario results in an increase of PM2.5 air pollution of 4.13 µg m−3 from 2018 compared to a 0.11 µg m−3 decline from 2018 under the 2030 M&A scenario. Reduced PM2.5 air pollution under 2030 M&A results in 1216–1414 fewer premature all-cause deaths annually compared to 2030 BAU. Achievement of National Clean Air Programme, National Ambient Air Quality Standards, or World Health Organization annual PM2.5 Air Quality Guideline targets in 2030 results in up to 6510, 9047, or 17 369 fewer annual deaths, respectively, relative to 2030 BAU. This comprehensive modeling method is adaptable to estimate local air quality and health co-benefits in other settings by integrating climate, energy, cooling, land cover, air pollution, and health data. Our findings demonstrate that city-level climate change response policies can achieve substantial air quality and health co-benefits. Such work can inform public discourse on the near-term health benefits of mitigation and adaptation.

Integrating biokinetics with computational fluid dynamics for energy performance analysis in anaerobic digestion

Anaerobic digestion (AD) is an effective process for decomposing organic matter in wastewater treatment plants (WWTPs) where highly efficient digesters properly mix the sludge. To ensure a uniform substance distribution, a comprehensive modeling method is necessary. Computational fluid dynamics (CFD) helps in the modeling of AD tanks but few studies have focused on integrating hydrodynamics with biokinetics because of complex AD processes. The current study presents a new CFD platform for estimating the biokinetics of WWTPs to assess the energy performance of AD tanks. The presented method is validated by numerical and experimental studies, and facilitates a link between methane production and mixing energy consumption. The on-site settings of the recirculation mixing system in the studied WWTP was able to prepare a uniform mixture of the material. However, reducing mixing rate to decrease energy consumption did not lead to proper mixing quality.

Research of Comprehensive Modeling of Two-Dimensional Vector Nozzle/Actuator Load/Turbofan Engine

To investigate the effect of the dynamic deflection process of a two-dimensional vector nozzle on its actuator load and engine performance, a comprehensive modeling method of two-dimensional vector nozzle/actuator load/turbofan engine is proposed. Firstly, based on the two-dimensional vector nozzle spatial motion model, combined with force and moment analysis, the mechanical model of vector nozzle actuation system is established; The load spectrum of the actuating system under different working conditions and deflection angles is obtained by CFD numerical simulation results; Using AMESim, the hydraulic actuation system model of two-dimensional vector nozzle is established. Finally, a two-dimensional vector nozzle/actuator/turbofan engine comprehensive model is established based on the component-level model of turbofan engine. The comprehensive model can accurately calculate the changes of main performance parameters such as engine rotor speed, thrust and pre-turbine temperature when the nozzle vector deflects. The simulation results show that the load on the nozzle actuator is positively correlated with the deflection angle, and the load change will lead to the fluctuation of the output displacement of the hydraulic actuation system. During vector deflection, due to the change of engine circulation capacity and thrust coefficient, the performance parameters such as engine low-pressure rotor speed and surge margin fluctuate greatly.

The impact of global warming on the potential suitable planting area of Pistacia chinensis is limited

Pistacia chinensis Bunge. is one of the main woody oil crops with a large artificial planting area in China and has important economic and ecological value. Here, based on 237 occurrence data and 22 environmental variables, we explored the potential planting area of P. chinensis in China in the present and future climate change scenarios by using a comprehensive model method. To fully consider the potential planting area of P. chinensis under specific climate change conditions and the limitations of soil conditions, we separately built two niche models to simulate the climate niche and soil demand niche, and then used the intersection of the two models as the result of the comprehensive habitat suitability model, finally, we used land-use data to filter the CHS model result. Our results showed, that under the baseline condition, the potential planting area of P. chinensis covers approximately 0.74 × 106 km2 in China. The future projection showed that the impact of global warming on the potentially suitable planting area of P. chinensis is limited, and most of the existing suitable habitats are not affected by climate change. With increasing temperature, the potential planting area will expand northward and slightly contract in the south margin, and its area will be slightly increased. Therefore, this species has great planting potential in China and should be given priority in the future afforestation plan.

Walk Score Assessment Using Urban Modeling Interface in Mahachai City, Thailand

The objectives of this study were to exhibit walk scores in the Mahachai sub-district, Mueng District, Samut Sakhon Province, Thailand, and build and construct acceptable models for diverse problem circumstances. The 3D physical model and walk score simulations were examined utilizing an urban modeling interface (UMI) plug-in, a part of a comprehensive modeling method in Rhinoceros computer-aided design software. The algorithm evaluates the proximity of points of interest to amenities of grocery stores, restaurants, shopping malls, coffee shops, banks, schools, bookstores, and entertainment. The simulation results show that the average walk score of the existing urban context is 87 points, according to the walkable city. However, the trial of new amenities added to the urban context by the same amenity type can change the score to 88 points, which would not significantly improve the score. The score increased to 93 points when adding the different amenities to the area. These reflect the need for urban amenities variety can improve the walkable quality in the city. The research proves the ease of using the UMI plug-in associated with the Rhinoceros software. Moreover, the results are necessary to guide urban designers to create walkable cities in the future.

A comprehensive modeling method for proton exchange membrane electrolyzer development

Hydrogen attracts significant interests as an effective energy carrier that can be derived from renewable sources. Hydrogen production using a proton-exchange membrane (PEM) electrolyzer can efficiently convert renewable power via water splitting in wide scales—from large, centralized generation to on-site production. Mathematical models with multiple scales and fidelities facilitate the continuing improvements of PEM electrolyzer development to improve performance, cost, and reliability. The model scopes and methods are presented in this paper, which also introduces a comprehensive PEM electrolysis modeling tool based on computational fluid dynamics (CFD) software, ANSYS/Fluent. The modeling tool incorporates electrochemical model of a PEM electrolysis cell to simulate the performance of coupled thermal-fluid, species transport, and electrochemical processes in a product-scale cell or stack by leveraging the powerful meshing generation and CFD solver of ANSYS/Fluent. The thermal-fluid modeling includes liquid water/gas two-phase flow and simulates a PEM electrolysis cell by using Fluent user-defined functions as add-on modules accounting for PEM-specific species transport and electrochemical processes. The modeling outcomes expediate PEM electrolyzer scaling up from basic material development and laboratory testing.

Comprehensive modeling method for deformation errors of different types of rolling joints in motion systems and its application in machine tools

This paper proposes a novel comprehensive modeling method for deformation errors of different types of rolling joints in machine tools to improving the analysis efficiency. This method comprehensively considers the deformation of three types of rolling joints, i.e., linear guideway, ball screw and bearing, firstly from the perspective of analytical modeling. Two comprehensive models for deformation errors of all rolling joints in two types of motion systems of machine tools are established respectively with the method. The nonlinear interfacial characteristics at rolling joints and the geometric and stiffness coupling characteristics are considered. In order to study characteristics of the synthetical deformation error of rolling joints, a synthetical error model for a five-axis machine tool is developed. Several results and optimizations of the joints are carried out. The proposed method in this paper can effectively avoid the tedious finite element modeling in the traditional analysis process and improve the efficiency.

Study on the Shidan granules for chronic atrophic gastritis with dysplasia rat model based on NF-κB signaling pathway

Objective To establish a rat chronic atrophic gastritis with dysplasia model and observe the effect of Shidan granules on the positive expression of NF-κB p65 in gastric tissues and the extent of IKKβ protein content in gastric tissues of chronic atrophic gastritis with dysplasia model rats. Methods Seventy SPF male Wistar rats were randomly divided into the blank group and 60 into the model group. In addition to the blank group, the modeling group was made using the MNNG-based comprehensive modeling method (150 μg/ml MNNG 5 ml/kg each stomach, containing 0.03% ranitidine feed, free drinking 0.1% ammonia), and then model successed at the 28th week. The remaining rats in the modeling group were randomly divided into 5 groups: the model group with intragastric administration of gavage, the western medicine group with intragastric administration of viralin, the Shidan granules group with intragastric administration of low/medium/high concentration Chinese medicine decoction. After 12 weeks of treatment, they were sacrificed and the expression of NF-κB p65 and IKKβ was measured and compared. Results Compared with the model group, the average optical density of NF-κBp65 (0.387 ± 0.011, 0.252 ± 0.022, 0.193 ± 0.003 vs. 0.442 ± 0.035) and the expression level of IKKβ (0.309 ± 0.056, 0.216 ± 0.025, 0.125 ± 0.016 vs. 0.405 ± 0.042) in the low-, middle- and high-dose Shidan granules groups significantly decreased (all Ps<0.01). Conclusions The mechanism of improving the precancerous lesions of gastric cancer by Shidan granules may be achieved by inhibiting the expression of IKK, reducing the abnormal activation of NF-κB. Key words: Gastritis, atrophic; Shidan granules; Precancerous lesions of gastric cancer; NF-kappa B; IKK; Rats

Geologic modeling study of foothill area of the Junggar Basin rim

The varied terrain and complex subsurface structure in the foothill segment of fold and thrust belts results in low-quality seismic data. Therefore, a structural model built only on the basis of seismic will have low reliability and be nonunique. To solve these problems, we have developed a comprehensive modeling method for foothill zones that combines gravity, magnetic (MT), electric, and seismic data. Information from gravity, MT, electric, and seismic data is fully used in each step of modeling. This reduces the nonuniqueness and guarantees the rationality and reliability of the tectonic model. The core of this procedure is simultaneous joint inversing gravity, MT, electric, and seismic multiparameters, which improves the accuracy of velocity model and results in a higher quality of seismic image. The Hala’alate Mountain area in the Junggar Basin, western China, is chosen as the application place, and the process of modeling is evaluated in detail; the structural model is proven to be correct by drilling data. Our method is more accurate and reliable than methods only using seismic data to build a geologic model in foothill zones.

Laminar burning velocity and structure of coal dust flames using a unity Lewis number CFD model

Despite decades of research, predictive methods remain unavailable to estimate flame propagation in dust clouds under industrial scenarios. The complexity of scaling the fundamental processes occurring in multiphase flames to industrial geometries, and a lack of tools to explore and extend knowledge in this area, may be key factors missing in the research literature. The main objective of this work is to verify the ability of a CFD model based on a unity Lewis number assumption to explore laminar burning velocity in coal dust clouds. A second objective is to perform parametric analysis including the role of surface reactions, particle diameter, and initial system temperature. The third and final objective is to explore the impact of discrete particle combustion on flame structure and burning velocity. Despite a simplified treatment of gas phase transport properties, single-step devolatilization, and single-step surface reaction, the current model correctly captures the effects of particle diameter and initial temperature on burning velocity and demonstrates good agreement with previous investigations once preheating in the experimental results is accounted for. Furthermore, the reduced model complexity may allow future investigation by the current authors and other research groups into different combustible dusts, more detailed system geometry, and turbulent flow conditions. Lastly, the results of the current study provide a baseline that more comprehensive modeling methods may be compared to, which is currently missing in the literature.

Long-term knowledge evolution modeling for empirical engineering knowledge

In this era of knowledge economy, appropriate management of the rapidly evolving knowledge is a real and urgent issue for factories and enterprises, in order to maintain the competitive edges. However, facing the onerous analysis required for understanding the long-term knowledge evolution, especially the evolving of empirical knowledge in the engineering field, effective and comprehensive modeling methods for knowledge evolution are absent. In this paper, a novel knowledge evolution modeling method is proposed for portraying the long-term evolution of empirical engineering knowledge (EEK) and assisting engineers in comprehending the evolving history. Three phases, EEK elicitation and formalization, EEK networks foundation, and family-tree evolution model construction, are included in the modeling method. This method is developed using natural language processing, semantic similarity calculation, fuzzy neural network prediction, clustering algorithm, and latent topic extraction techniques. To evaluate the performance of the proposed modeling method, an evolution model of empirical knowledge in computer-aided design (CAD) is constructed and then verified. Experimental results show that the proposed method outperforms the former approaches in feasibility and effectiveness, and hence opens up a better way of further understanding the long-term evolution course of EEK.

A Geometry Deformation Model for Braided Continuum Manipulators

Continuum manipulators have gained significant attention in the robotic community due to their high dexterity, deformability and reachability. Modeling of such manipulators has been shown to be very complex and challenging. Despite many research attempts, a general and comprehensive modeling method is yet to be established. In this paper, for the first time, we introduce the bending effect in the model of a braided extensile pneumatic actuator with both stiff and bendable threads. Then, the effect of the manipulator cross section deformation on the constant curvature and variable curvature models is investigated using simple analytical results from a novel geometry deformation method and is compared to experimental results. We achieve 24% simulation accuracy using our constant curvature model for a braided continuum manipulator in presence of body load and 10% error using our variable curvature model in presence of extensive external loads. With proper model assumptions and taking to account the cross section deformation, an 8-20% increase in the simulation accuracy is achieved compared to a fixed cross section model. The presented models can be used for the exact modeling and design optimization of compound continuum manipulators by providing an analytical tool for the sensitivity analysis of the manipulator performance. Our main aim is the application in minimal invasive manipulation with limited workspaces and manipulators with regional tuneable stiffness in their cross section.

Modeling outdoors algal cultivation with compartmental approach

Abstract A comprehensive modeling method for the simulation of outdoors algal cultivation in bubble column photobioreactors is presented. The compartmental modeling approach presented earlier by Nauha and Alopaeus (2013) [1] is used and extended to consider changes in the directionality of light during the day. The nightly loss of biomass due to darkness is also considered. The model is capable of predicting the system hydrodynamics, mass transfer and growth of algae. Model results are verified against measurements and show good agreement. The predictive capability of the model is validated. The model is used to make suggestions for optimization of outdoors algal cultivation.

Modeling method for combining fluid dynamics and algal growth in a bubble column photobioreactor

A comprehensive modeling method for algal growth in a photobioreactor is introduced. The model integrates fluid dynamics, mass transfer and the growth kinetics of algae. Availability of light, nutrients and carbon source as well as oxygen inhibition on growth is considered. The modeling approach has three-stages: (1) Detailed prediction of the flow field by Computational Fluid Dynamics (CFD), (2) Division of the computational domain into larger compartments (blocks or zones), and (3) Compartmental modeling. Compartmentalization is performed because calculations with CFD would be very time consuming. Use of the compartmental model allows fast calculation of several concurrent phenomena while accuracy of the important flow parameters is retained. The approach uses a dynamic model called photosynthetic factory to model algal biomass growth. The combination of fluid dynamics and light distribution in the reactor model is important because the fluid dynamics defines the time–irradiance profile the algal cell experiences. Adequate mixing is therefore not only important for mass transfer but for light distribution as well. The movement of biomass in the column between light and dark areas allows for the continuation of growth even at high biomass concentrations, where light is only available on the sides of the reactor. The model is inherently capable of predicting this behavior from the fluid dynamics without the need to define time–irradiance profiles i.e. light–dark cycles. A comprehensive model such as this is needed for photobioreactor design and scale up, because the phenomena in the reactor are all interdependent.

Assessment of the restoration of a degraded semi-humid evergreen broadleaf forest ecosystem by combined single-indicator and comprehensive model method

We conducted a long-term restoration experiment in the degraded ecosystems of a semi-humid evergreen broadleaf forest in Muding County, Yunan Province, China. We used single-indicator assessment and our newly established comprehensive assessment model to compare the effects of four types of management (different historical disturbances + restoration measures) on forest restoration based on a vegetation survey. (1) Species richness in each of the four restoring communities was still lower than that of the zonal forest. There was a compensatory effect of species richness among different layers within communities. Restoration management by natural succession was clearly efficient at restoring species richness and composition, but the effect of disturbance history was minor. Human-assisted restoration had a great effect on biomass accumulation and model tree growth. Plant density was also affected by the different management types, which progressively led to differences in model tree growth and biomass accumulation. (2) The comprehensive assessment model, a simple method based on the restoration mechanism, can precisely quantify the overall restoration of ecosystems, historical disturbance and actual disturbance, using only one set of data. Restoration index ( R d ), turning-point restoration index ( R 0), restoration-effect index ( R a ), turning-point disturbance index ( D 0), actual disturbance index ( D r ) and overcoming disturbance index ( D a ) presented gradual changes in the four restoring communities. The combined single-indicator and comprehensive model method fully assessed the restoration of degraded ecosystems in a semi-humid evergreen broadleaf forest.