Parameterized Modeling Methodology for Efficient Aeroservoelastic Analysis of a Morphing Wing

High-Efficient parametric aeroelastic modeling and experimental validation for a morphing aircraft testbed

Dynamic parametric modeling-based model updating strategy of aeroengine casings

To investigate the impact of wing asymmetry on the aerodynamic characteristics of a 20kg-class UAV, this paper develops a MATLAB-AVL-based joint automated simulation method for tandem folding wing configurations. This method efficiently supports batch aerodynamic characteristic analysis of multiple configurations, filling the gap in existing systematic research on the aerodynamic performance of asymmetric folding wings. First, parametric modeling is performed around four independently rotatable wing surfaces. Second, automated simulation is established using MATLAB and AVL software. Finally, aerodynamic characteristic analysis is conducted on typical asymmetric configurations. Simulation results show that in typical asymmetric configurations, the forward wing sweep angle is more sensitive to aerodynamic performance than the rear wing sweep angle. As the sweep angle increases, the overall aerodynamic efficiency decreases, with increased separation and more significant efficiency degradation at medium to high angles of attack. Compared to asymmetric forward sweep, asymmetric backward sweep and slanted configurations exhibit better pitch static stability. The research findings can provide a reference for the selection of asymmetric configuration strategies and the construction of aerodynamic databases for folding wing UAVs.

Folding angle and wing flexibility influence the flight performance of origami winged fruits

A method of building hull model with OpenGL and C++ is proposed, which can better realize 3D modeling. Compared with the traditional 2D method, 3D design can express products more intuitively. Compared with some major commercial modeling software on the market, although commercial software can establish a complete surface space, the entire system modeling cannot be separated from the operation of commercial software, and software application cannot be promoted without independent intellectual property rights. The model constructed by this method analyzes the complex curves and surfaces contained in the shape of the hull according to the characteristics of the hull, and proposes a geometric modeling algorithm based on key points, which uses quadrilateral patches to splicing key points. Implement model meshing. Finally, a parametric model is formed by OpenGL rendering. The hull parametric model system developed based on OpenGL has good stability and strong compatibility, and can better assist in the evaluation of ship damage effects and target vulnerability, which are two extremely important tasks.

ملخص:- تحتوي نماذج الانحدار على مکونين أحدهما مکون عشوائي يمثل حد الخطأ (Error Term) والأخر مکون غير عشوائي يمثل متغير الاستجابة(Response Variable) وهذا المکون هو محل الاهتمام فيتم تقديره بإحدى الطريقتين هما: الطريقة المعلمية أو الطريقة اللامعلمية أو کلاهما. نموذج الانحدار المعلمي (Parametric Regression Model) هو النموذج الأکثر شيوعا حيث أنه يفترض أن متغير الاستجابة له صيغه دالية محدده مسبقا والتي تم الحصول عليها من معلومات سابقه حول هيکل دالة الانحدار من خلال ذلک يتم تقدير فئة من المعالم. ورغم أن النماذج المعلمية تعد أحد أهم أدوات تحليل البيانات؛ لأنها فعاله ويمکن تفسيرها بسهوله، إلا انها لم تستطع ان تکون کافية في بعض الحالات. أما نموذج الانحدار اللامعلمي (Nonparametric Regression Model) فانه يعتمد على تقدير دالة الانحدار مباشرة من البيانات کما أنه لا يفترض فروضا معينه لتقدير معالم النموذج مثل التي يفترضها النموذج المعلمي وبالتالي فهو يتمتع بمرونة أکثر لاکتشاف البيانات التي قد تکون مفقودة او في الحالات التي لا تتوافر فيها معلومات سابقة. يتم انشاء نموذج الانحدار شبه المعلمي (Semi parametric Regression Model) من خلال مزج الطريقتين السابقتين معا. فغالبا ما يتم استخدام هذا النموذج في المواقف التي تکون فيها الافتراضات المعلمية غير محددة وغير متسقة، أو أن النموذج اللامعلمي لا يعمل بشکل کامل. يشتمل هذا البحث على تطبيق نماذج الانحدار المعلمية وشبه المعلمية بالإضافة إلى النموذج اللامعلمى کحالة خاصة من نموذج الانحدار شبه المعلمى لتقدير الدالة الافتراضية وتحديد شکل العلاقة بين المتغير التابع والمتغيرات المستقلة بالاضافة الى شکل انتشار البيانات مع خط (أو منحني) التقدير وذلک على بيانات واقعية تم الحصول عليها من الإتحاد المصري لألعاب القوى والمعروفة بـبيانات لعبة العشاري . Regression models contain two components, one of which is a random component that represents the Error Term and the other is a non-random component that represents the response variable and this component is of interest and is estimated in one of two methods: the parametric method or the nonparametric method or both. Parametric regression model is the most common model since it assumes that the response variable has a predetermined functional formula which was obtained from previous information about the structure of the regression function by which a class of parameters is estimated. Although parameter models are one of the most important tools for analyzing data; Because it is effective and can be explained easily, but it could not be sufficient in some cases. As for the nonparametric regression model, it relies on estimating the regression function directly from the data, as it does not assume specific assumptions for estimating the model parameters, such as those assumed by the parametric model, and thus it has more flexibility to discover data that may be missing or in cases where previous information is not available. The semi-parametric regression model is constructed by blending the two previous methods together. This model is often used in situations where the parametric assumptions are indeterminate and inconsistent, or the nonparametric model is not fully functional. This research includes the application of parametric and semi-parametric regression models in addition to the nonparametric model as a special case of the semi-parametric regression model for estimating the hypothetical function and determining the form of the relationship between the dependent variable and the independent variables in addition to the data spread form with a line (or curve) estimation on realistic data On it from the Egyptian Athletics Federation, known as Decathlon data.

This article studies the application of nonparametric modeling approach to model magnetorheological (MR) dampers. For comparison purposes, another typical parametric modeling method for electrorheological (ER) and MR dampers is reviewed. The existing parametric MR damper model includes a stiff Bouc-Wen model that is not friendly for simulation study and real time implementation of model-based advanced control algorithms. In order to avoid the difficulties by using the existing parametric model, the test data from a commercialized MR damper is employed to develop nonparametric models, which can consist of a series of numerically efficient mathematic functions. In addition, the selected functions are required to be continuous and differentiable for potential model-based control algorithms. The results of the nonparametric models show that such different models are comparable. Furthermore, one nonparametric model is selected to be compared with a parametric model and the test data to illustrate the accuracy of the model. The comparison shows that the proposed nonparametric models are able to accurately predict the damper force characteristics, damper bilinear behavior, hysteresis, and electromagnetic saturation. It is further shown that the nonparametric models can be numerically solved with an integration step size of the order of 10 2 s, much faster than the parametric models of the order of 10 5 s, which clearly shows that the proposed nonparametric models are feasible even for real time model-based control algorithms.

Simplified models are widely applied in finite element computations regarding mechanical and structural problems. However, the simplified model sometimes causes many deviations in the finite element analysis (FEA) of structures, especially in the non-designed structures which have undergone unknowable deformation features. Hence, a novel FEA methodology based on the parametric model by approximating three-dimensional (3D) feature data is proposed to solve this problem in the present manuscript. Many significant and effective technologies have been developed to detect 3D feature information accurately, e.g., terrestrial laser scanning (TLS), digital photogrammetry, and radar technology. In this manuscript, the parametric FEA model combines 3D point clouds from TLS and the parametric surface approximation method to generate 3D surfaces and models accurately. TLS is a popular measurement method for reliable 3D point clouds acquisition and monitoring deformations of structures with high accuracy and precision. The B-spline method is applied to approximate the measured point clouds data automatically and generate a parametric description of the structure accurately. The final target is to reduce the effects of the model description and deviations of the FEA. Both static and dynamic computations regarding a composite structure are carried out by comparing the parametric and general simplified models. The comparison of the deformation and equivalent stress of future behaviors are reflected by different models. Results indicate that the parametric model based on the TLS data is superior in the finite element computation. Therefore, it is of great significance to apply the parametric model in the FEA to compute and predict the future behavior of the structures with unknowable deformations in engineering accurately.

This study is based on the Multiple Reference Frame (MRF) method to construct a numerical simulation model of the transition state of a folding wing vertical takeoff and landing unmanned aerial vehicle, and to investigate the influence of propellers on the aerodynamic characteristics of the wing under different inflow velocities during the transition phase. The research results indicate that the lift and drag of the wing increase first and then decrease with the increase of folding angle, especially at higher inflow velocities, where airflow separation is significantly intensified, resulting in a significant increase in drag. When the folding angle f=0°, i.e. no folding occurs, the propeller can accelerate the airflow velocity on the upper and lower surfaces of the wing, thereby increasing lift. However, as the folding angle increases, the presence of the propeller changes the direction of the airflow, resulting in a decrease in actual lift compared to without the propeller.

Standard, nonparametric statistical methods estimate only the impact of therapy on survival rate up to a selected follow-up interval. In contrast, parametric methods can estimate the impact of treatment on the two cardinal parameters of malignancy: likelihood of cure and recurrence free survival time among uncured patients. The authors screened a total of six parametric survival models. Three of these, including the log normal model, were applied to survival data from five clinical trials of adjuvant therapy for Stage II breast cancer. For comparison, the log rank test, a standard nonparametric method, was also applied to the same data. Both parametric and nonparametric methods identified a significant therapeutic in three of the five trials. In only one of these three trials, however, did parametric analysis identify a significant difference in the likelihood of cure between treatment groups. In the remaining two trials, a significant difference was found in recurrence free survival time among uncured patients. The three parametric survival models gave similar results. These findings suggest that parametric analysis may warrant further study as a method for measuring the long term clinical impact of adjuvant therapy on Stage II breast cancer.

This study proposes a reinforcement learning-based multi-objective optimization framework for automotive energy-absorbing box structures, aiming to improve specific energy absorption (SEA) and reduce peak crushing force (PCF). A parametric model with adjustable folding angle, layer number, and multi-wall thicknesses is developed and integrated with automated modeling, simulation, and evaluation. An improved MO-SAC algorithm enables joint optimization of W2W and W2C structures. The agent explores optimal designs based on simulation feedback. Results show that the optimal 9-layer W2W structure with a 122.46° folding angle and wall thicknesses of 1.35 mm, 1.29 mm, and 1.47 mm achieves a 21.28% increase in SEA and a 12.59% decrease in PCF. This method offers a data-efficient and interpretable solution for structural optimization.

Effect of oblique incidence angle of sunlight on the optimized folding angle of V-shaped organic solar cells

An efficient aerodynamic topology optimization method was constructed based on the parameterized level set method (PLSM) and large neighborhood search algorithm. The traditional aerodynamic optimization design process is to optimize the shape of a basic shape, and the aerodynamic configuration is determined. The determination of the basic shape relies on the experience of human designers, making it difficult to obtain innovative aerodynamic configurations. To this end, the PLSM is used to obtain aerodynamic configurations of supersonic Busemann biplane with different topological structures. In response to the characteristics of large sample size and low computational efficiency in aerodynamic topology optimization design, a large neighborhood search algorithm is adopted as the optimization algorithm. Aerodynamic topology optimization design was carried out to achieve good drag reduction effect for the Busemann biplane. Compared with shape optimization design, aerodynamic topology design can generate airfoils with different topological structures, greatly improving the design freedom and making it possible to find different aerodynamic configurations in a wide design space.

Forecasting of sea-state characteristics has a great importance in coastal and ocean engineering studies. Therefore, the purpose of this study was to investigate performances of Adaptive-Network-Based Fuzzy Inference System (ANFIS) and several parametric methods in the Black Sea. For this purpose, different fuzzy models with different input combinations were developed for two different wind data sources (TSMS and ECMWF) at two offshore buoy stations. It also aimed to apply several approaches to event-based data sets for wave predictions. Generally, in literature the tendency is to use time series data for wave predictions. In this kind of prediction approach, lagged time series data are taken as inputs and current or future variables are taken as output. In this study, event-based data for each independent storm were extracted from time series data. Simultaneous or concurrent data of wind speed, blowing duration, fetch length and wave characteristics were detected for each single storm. These event data were then used to set up models. The hindcast results were validated with significant wave height and mean wave period data recorded in Hopa and Sinop buoy stations. The performance of developed fuzzy models were also compared with that of four different parametric methods (Wilson, SPM, Jonswap, and CEM methods) applied for two wind data sources at both buoy stations. Finally, it was determined that in the prediction of both wave parameters (Hs and Tz) the ANFIS models (R = 0.66, squared correlation coefficient, and MAE = 0.37 m, mean absolute error, for the best model in prediction of Hs) were more accurate than the parametric methods (R = 0.63 and MAE = 0.75 m for the best model in prediction of Hs).

A parametric 3D geological modeling method considering stratigraphic interface topology optimization and coding expert knowledge