Analytical Method For Prediction Research Articles

Initial Comparison of analytical methods for noise prediction of future electric aircraft powertrains

Increasing requirements regarding greenhouse gas emissions produced in the aviation sector require new technologies for aircraft propulsion systems. A suitable technology for a more sustainable and low emission aircraft is the electrification of the powertrain. The noise emission by electric machines becomes an important contribution to the overall aircraft noise, especially since future aircraft will need high-power density electric machines that pose additional challenges regarding design and manufacturing. Electric machines with power densities of 10 kW/kg and higher are currently not available for detailed measurements, to get a first impression of the dominating noise sources of electric motors, models for predicting the noise emission are necessary. Compared to numerical methods, analytical models offer a fast estimation of the noise generated by electric motors. In this paper, analytical models for noise prediction generated by electric motors suitable for aircraft propulsion systems are presented. The most advanced model includes the calculation of the excitation forces acting on the stator due to the magnetic flux density that is coupled with a sound radiation analysis of the outer surface of the motor. By varying the basic parameters for each model under investigation, the noise radiation of a permanent magnet synchronous electric motor is assessed.

Analytical time-coordinated entry guidance for multi-hypersonic vehicles within three-dimensional corridor

A coordinated entry mission requires multiple hypersonic vehicles to arrive at the designated area simultaneously from different times and locations. To satisfy the coordinated entry mission, this paper investigates the coordinated entry guidance problem for multi-hypersonic vehicles. An analytical time-coordinated entry guidance method is proposed based on the algorithms of analytical prediction, profile correction, and coordination time determination. Firstly, considering the altitude variations of the trajectory, high-precision analytical solutions for the remaining flight time and range are derived based on quasi-equilibrium glide conditions. Compared to the traditional numerical integration prediction methods, this analytical prediction method achieves superior computational efficiency while ensuring high-precision prediction. Subsequently, a flight corridor based on longitudinal lift-to-drag ratio is constructed, extending from the traditional two-dimensional corridor to a three-dimensional one. Within the corridor, the analytical lift-to-drag ratio profile is corrected by minimizing the prediction errors, and the guidance commands for both angle of attack and bank angle can be generated directly without tracking law. With the above analytical solutions and algorithms, the coordinated entry guidance method enables rapid generation of guidance commands for each hypersonic vehicle. Finally, numerical simulations under dispersed launching time and launching location conditions are performed, and the simulation results verify the effectiveness and robustness of the proposed time-coordination entry guidance algorithm.

Pragmatic Prediction Model of Droplet Trajectory in a Turbine Cascade

Abstract Droplet deposition on a turbine cascade is important for the turbine system performance but its experimental analysis is difficult. Thus, the simulation of a droplet liquid phase in a gas flow field was studied to optimize turbine cascade design. However, the computational fluid dynamics (CFD)-based approach for such droplet problems requires enormous costs. Thus, the application of CFD simulation in the turbine blade's early-stage design is challenging, requiring iterative optimization for adjusting design with performance prediction. Therefore, this study proposed an analytical prediction method, having a reasonable cost and moderate accuracy, as an alternative to the whole multi-phase numerical simulation approach. The proposed method predicts droplet motion using the outline of the turbine blade and gas–liquid physical properties. Furthermore, the approach was validated by performing a three-dimensional Eulerian–Lagrangian simulation with low-pressure turbine blade T106. It was found that the droplet trajectories in the turbine cascade are governed by Stokes number. Furthermore, the streamlines of the gas flow were characterized by the shape of the turbine blade. The proposed model reproduced droplet trajectories obtained using CFD within an error margin of 10%. Consequently, it was concluded that the proposed analytical model is a promising approach to predict the droplet trajectory in a turbine cascade, obtained by the three-dimensional numerical simulation at a low cost.

Prediction method of thermal expansion coefficient for 2D composite fabric

In this article, an analytical method for predicting the thermal expansion coefficient of 2D composite fabrics is established. First of all, different from the traditional prediction of thermal expansion coefficient by classical laminate theory, this paper extends the self-consistent method of micromechanics to 2D composite fabrics to improve the accuracy of thickness direction prediction. Analytical Prediction method of Thermal expansion coefficient of 2D Composite fabric (APTC)was established. In the x section of Representative Volume Element(RVE) model, the stress balance equation and deformation coordination equation are applied to derive the internal thermal expansion coefficient. In the z section, the coefficient of thermal expansion is derived from the Poisson effect. Secondly, the formula of thermal expansion coefficient is derived for plain fabric, twill fabric and satin fabric respectively, which is consistent with the APTC method, indicating that the method is representative. Finally, RVE finite element model is established according to the braided structure parameters of 5284/T800 composite fabric. Comparing analytical solution, numerical solution and experimental solution, the α 1 and α 2 of the numerical and experimental solutions is close enough to be considered equal, which is consistent with the transverse isotropy of the composite fabric in xOy plane predicted by theoretical analysis.When predicting α 1 and α 2 , the maximum error between numerical solution and analytical solution is 1.79%, the maximum error between numerical solution and experimental solution is 22.29%, and the error remains at about 4% during predicting α 3 . In general, the APTC method for predicting the thermal expansion coefficient of composite fabrics is accurate and effective, and the simplified formula is more convenient to popularize and apply.

Study of 3D-printed onyx parts reinforced with continuous glass fibers: Focus on mechanical characterization, analytical prediction and numerical simulation

The 3D printing of continuous-fiber composites is currently relevant to engineers and researchers. This study aims to characterize and predict the mechanical properties of Onyx/glass fiber specimens printed using 3D printing. The work assesses the impact of glass fiber printing parameters on the mechanical behavior of printed parts and proposes analytical and numerical methods to predict mechanical properties. A physicochemical analysis was conducted on 3D printed continuous glass fibers. The study also investigated the impact of fiber printing parameters on composite parts. The results indicate that the 3D-printed glass fibers consist of nylon, continuous glass fibers, and voids (porosity), which range from 58% to 63%, 31% to 38%, and 5% to 8%, respectively. Mechanical characterizations indicate that printing fiber layers in blocks results in superior mechanical properties compared to printing alternating layers of glass fibers and Onyx. Additionally, the concentric mode of fiber printing can be challenging if the ‘start rotation’ parameter is not adjusted correctly. Premature specimen breakage occurred when fiber printing began within their useful length, resulting in a deformation at break that was approximately 34% less, depending on the starting position. The proposed analytical and numerical prediction methods had prediction errors of approximately 7% to 12% and 5% to 7%, respectively. Engineers can use these prediction approaches during the dimensioning phase of 3D printed composite parts.

FINANCIAL DISTRESS ANALYSIS USING ALTMAN AND ZMIJEWSKI ON TOURISM INDUSTRY

This study examines financial distress scenarios in the tourism and recreation industry using the Altman Z-score and Zmijewski X-Score methodologies. Employing a quantitative descriptive research approach with purposive sampling, the study analyzes 12 publicly listed companies on the Indonesia Stock Exchange from 2019 to 2022. The results indicate that PT. Eastparc Hotel is the most financially stable, contrasting with PT. Bukit Uluwatu Villa as the weakest. While both methods yield different results, the disparity is not highly significant due to the varied components analyzed in the financial reports. The research recommends using multiple analytical methods for bankruptcy prediction to allow for accuracy assessment and to determine the suitability of each model for specific companies. Keywords : Financial distress, Tourism and recreation industry, Z-score altman, zmijewski x-score.

Experimental and analytical studies of infill wall with sliding joints considering a door opening

AbstractSemi‐rigid steel frame stands out due to its remarkable deformation capability under seismic loading, while the introduction of partitioned walls would disturb the expected seismic behavior of the infilled steel frames. Furthermore, the presence of door openings might exacerbate these negative effects. To mitigate the detrimental multiple‐diagonal strut effect of traditional infill walls around the door opening, an innovative low‐damage wall panels system: prefabricated infill wall panels with a door opening and sliding joints are presented for semi‐rigid steel frames. For testifying the effectiveness of the proposed structure, a quasi‐static test was carried out on three half‐scaled steel frames: a bare frame, a frame infilled with conventional wall panels with a door opening, and a frame infilled with the novel wall panel system with a door opening. Experimental results reveal that the developed innovative wall panels with a door opening could avoid unfavorable crack developments and opening deformation around the door area. It is mainly attributed to the releasement of the adverse multiple‐diagonal strut mechanism of traditional wall panels with door openings. Thus, the presented infilled frame showcases seismic performance similar to the bare steel frame, while having a higher energy dissipation capacity. Moreover, the developed analytical prediction method based on the superposition principle could accurately estimate the lateral load‐carrying capacity of the structures. Due to negligible deformation of the both bottom infill wall panel and the door opening, the innovative infill wall only contributes about 10% lateral load‐carrying capability to the infilled frame.

Review of the analytical prediction method of surf-riding threshold in following sea, and its relation to IMO Second-Generation Intact Stability Criteria

Review of the analytical prediction method of surf-riding threshold in following sea, and its relation to IMO Second-Generation Intact Stability Criteria

Assessment of functional components in sika deer and wild boar meats with improvement in processing and flavor and a novel analytical prediction method

In Japan, where food self-sufficiency is low, gibier (wild game) is expected to contribute to agriculture by reducing greenhouse gases and to contribute to regional development without requiring imported feed. However, the toughness and odor of gibier have prevented its use in many areas. In this study, we increased the content of functional ingredients by liquefying the meat and also increased the contents of L-glutamic acid and L-aspartic acid, amino acids with umami taste, to investigate their use as supplements and seasonings. Because these analyses require expensive equipment and time-consuming labor, we examined the use of a colorimeter as a simple method.When deer and wild boar meats were subjected to protease treatment under high hydrostatic pressure (200 MPa, 50 °C) for 24 h, the meats were liquefied. When the imidazole peptides of the liquefied gibier meat were examined, a maximum fourfold increase in the amount of anserine was observed in deer meat and a 10-fold increase in the amount of anserine was observed in wild boar meat. When this increased amount of anserine was compared with CIE L*a*b* values measured with a colorimeter, a negative correlation was observed. These results indicate that the amount of anserine can be easily measured by a colorimeter without free amino acid analysis. On the other hand, there was an increase or decrease in carnosine content. This may be because carnosine is decomposed more quickly than anserine. The amount of amino acids with umami flavor was dependent on the type and amount of enzyme.The drawback of this experiment was that only loin meat was used, and meat from other parts of the body might yield different results. In summary, protease treatment of deer and wild boar meats at high hydrostatic pressure (200 MPa, 50 °C) for 24 h resulted in liquefaction of the meat. In addition, the increase in functional and umami components shown in this study has made it possible to use the meat as a supplement or seasoning. Further investigation of other body parts or types of meat is planned in the future.

Analytical method for assembly-induced deformation prediction of composite bolted joints with assembly gap

Shimming position and amount have a significant influence on the weight and mechanical performance of the thin-walled product that having assembly gap during aerospace components assembly process. An analytical method for assembly-induced deformation prediction of the bolted composite joints with assembly gap was developed. The assembly-induced deformation under the preloading force was computed as bending deformation and bolt head compression deformation by evaluating whether assembly gap can be eliminated and whether the calculating point is within the conical and spherical envelope of the fastener. The proposed method was validated by the preloading experiment of three-bolt composite joints with relative error less than 10%. Then it was applied to analyse the assembly-induced deformation of a composite box structure including composite spars and skins. Under the guide of the analytical result, shimming assembly of the composite box structure was carried out. The proposed analytical method has a good application prospect to predict the assembly-induced deformation during preloading process for composite/composite joints or composite/metal joints.

Examination and Prediction of the Lift Components of Low Aspect Ratio Rectangular Flat Plate Wings

An investigation of the lift components present over low aspect ratio rectangular wings is presented. Wing aspect ratios ranging from 0.5 to 3 are examined using published experimental results and analytic analysis methods. The methods are based on the fundamental decomposition of Polhamus; that is, lift is attributed to a potential flow lift component coupled with a vortical lift component stemming from the leading and side edges of the flat plate wing. The analysis suggests a low sensitivity to Reynolds numbers spanning three orders of magnitude and brings into doubt the realization of a leading edge vortex lift component for wings with unswept leading edges under steady state conditions. The analytic prediction method of Purvis is shown to provide close accord with all experimental data sets when lift contributions caused by a leading edge vortex are excluded.

Analytical prediction method of power system frequency deviation under uncertain power fluctuations

AbstractIn modern power systems, the impact of random power sources and loads on power systems is increasing, resulting in threatened system frequency security. However, traditional methods are often not comprehensive in modelling randomness, and there is no analytical method to assess the frequency response of power systems under uncertain power fluctuations. Here, the power fluctuation in a power system is regarded as an interval random quantity. An analytical prediction method of the power system frequency deviation under uncertain power fluctuation is proposed. Through further deduction, the allowable range of power fluctuation under the premise of secure frequency deviation can also be defined, which provides a reference for frequency security and accident prevention in power systems. Numerical simulations with the model of the East China Power Grid demonstrate that the proposed analytical method can delimit the response interval of system frequency deviation well, and the backstepping calculation can also delimit the allowable range of power fluctuation to ensure the secure operation of the system.

Finite Element Analysis of Residual Stress Distribution Patterns of Prestressed Composites Considering Interphases

New finite element analysis procedures are developed in this study to obtain the precise stress distribution patterns of prestressed composites. Within the FEM procedures, an equivalent thermal method is modified to realize the prestress application, and a multi-step methodology is developed to consider coupling effects of polymer curing and prestress application. Thereafter, the effects of interphases' properties, including the elastic modulus and coefficient of thermal expansion (CTE), on the stress distribution patterns are revealed. Analytical methods for residual stress prediction are modified in this study to demonstrate the finite element analysis procedures. From the residual stress results, it is found that the increase in the prestress level tends to contribute to the initiation of interphase debonding. The increase in the elastic modulus or CTE of the interphase results in very large circumferential and axial stress values appearing in the interphase. When the elastic modulus in the interphase is heterogeneous, the predicted stress values in the fiber and matrix are similar to the results predicted with the equivalent elastic modulus of the interphases. However, the heterogeneous elastic modulus results in serious circumferential and axial stress gradients in the interphase.

Analytical method for elastic recovery prediction of air bending sheet

The estimation of the elastic recovery is of great importance during the planning of plastic deformation processes, because this estimation could reduce the number of required steps to reach the target geometry. The sheet bending process is one of the most widely used industrial processes, and that is why this paper seeks to provide an analytical model based on an elastic behavior with potential hardening of the material that could be combined with the geometric information of the process to estimate the degree of recovery of the components. The potential hardening model was selected due to its simplicity and good fit with the experimental data observed in steel sheets in this application. The effectiveness of the model was compared with the results obtained by several authors. The effectiveness of the model is significantly influenced by the parameters of the bending process and the method used to estimate the radius of curvature.

Analytical trajectory prediction for skip re-entry of lifting vehicle

An analytical trajectory prediction method is put forward for skip re-entry of lifting vehicles. First, the 3-D analytical solutions of skip re-entry trajectory are developed, which are crucial to realize the analytical trajectory prediction. To facilitate the derivation, an auxiliary geocentric inertial frame is established to deal with the strong nonlinear problem caused by the Earth’s rotation. Thereafter, the analytical solutions of the downrange, crossrange, and velocity are approximated by the outer solutions of a two-time scale singular perturbation. The analytical solutions of the altitude and flight-path angle are developed using regular perturbation techniques which can decompose the strongly coupled and nonlinear system into a sequence of linear problems. Second, since the analytical solutions are with respect to the lift-to-drag ratio and bank angle, a method based on the EKF technique is proposed to estimate the lift-to-drag ratio and bank angle of the re-entry vehicle. Third, the analytical trajectory prediction schemes for the lifting re-entry vehicle with multiple bank reversals are put forward. The simulations show that the proposed analytical solutions are in good agreement with the numerical solutions, but the computation time of the analytical solutions is about two orders of magnitude less than that of the numerical solutions. In addition, the superior performance of the proposed analytical trajectory prediction method is well demonstrated by the simulation results.

A Modified FMEA Approach to Predict Job Shop Disturbance

Failure modes and effects analysis (FMEA) is a systematic approach that focuses on evaluating critical disturbances in a system. However, traditional FMEA has its own drawbacks, such as invalid computations and ambiguous priority definitions, which lead to many constraints in the application of complex production processes, especially in job shops with various resources. Therefore, this paper proposes an analytic disturbance prediction method for job shop with multiple resources and multiple evaluation indexes, which combines the vector computing techniques, FMEA, and fuzzy analytic hierarchy process (FAHP). In contrast to other work, this paper focuses on the establishment of FMEA mathematical model to improve the readability of multi-resource disturbance risk results. To this end, the projection of the disturbance vector is visualized to reduce repeated calculation results, triangles and trapezoids are used as membership functions to improve the accuracy of weight, and the differentiation index is used to reduce the ambiguity of priorities. The proposed method can effectively discover the critical disturbances and enable managers to undertake more assertive decisions.

Curvature-enabled analytical method for bending-induced crack location prediction

Condition assessment of civil infrastructure damaged by naturaldisasters with insufficient structural information has been a challenge for engineers. This paper proposes an analytical method to predict bending-induced crack locations on damaged reinforced concrete (RC) beams merely using curvature characteristics obtained from vision-based technologies. Firstly, critical equations that calculate minimum crack spacing followed by bending curvature information are derived through bond-slip theory and assumed boundary conditions. Secondly, a prediction procedure is proposed using derived critical equations to determine bending-induced crack locations. Two RC beam specimens under four-point bending were investigated to verify the validity and accuracy of the proposed method. Experimental results show that the combination of vision-based technologies and the analytical method proposed in this research has great potential in structural inspection and safety evaluation in field.

An analytical prediction method for the bifurcation of an asymmetric rotor system partially filled with viscous incompressible fluid

Instability of a rotor partially filled with viscous incompressible fluid will cause the amplitudes of perturbations to increase exponentially. Many models of an isotropic rotor partially filled with fluid have been proposed to investigate its stability. However, the bifurcation of an anisotropic rotor partially filled with viscous incompressible fluid is complicated, which has rarely been studied. To investigate this problem, a continuous model is first established for the isotropic case and the hydrodynamic forces are calculated. The D-decomposition method is then used to determine the stable and unstable regions of the isotropic rotor. An analytical prediction method is then proposed in this paper, and the results for stable and unstable regions are the same as those obtained with the D-decomposition method. Then, this novel analytical prediction model is applied to an anisotropic rotor partially filled with viscous incompressible fluid, and the stable and unstable regions are analyzed. One isotropic and two anisotropic conditions are compared to verify the correctness of the proposed analytical method. The results show that the dimensionless damping and stiffness have significant effects on the stability of an anisotropic rotor partially filled with viscous incompressible fluid; in particular, it is found that there exists a single stable region for low values of the dimensionless damping coefficient and stiffness. Furthermore, the bifurcation law of different anisotropic parameters is first explored, which can provide theoretical guidance for the chosen external stiffness and damping coefficients.

Analytical Iron Loss Evaluation in the Stator Yoke of Slotless Surface-Mounted PM Machines

One of the attractive benefits of slotless machines is low losses at high speeds, which could be emphasized by a careful stator core loss assessment, potentially available already at the predesign stage. Unfortunately, mainstream iron loss estimation methods are typically implemented in the finite element analysis environment with a constant coefficients dummy model, leading to weak extrapolations with huge errors. In this article, an analytical method for the iron loss prediction in the stator core of slotless PM machines is derived. It is based on the extension of the 2-D field solution over the entire machine geometry. Then, the analytical solution is combined with variable coefficient loss models (VARCO) or constant coefficient loss models, which can be efficiently computed by vectorized postprocessing. VARCO loss models are shown to be preferred at a general level. Moreover, this article proposes a lookup-table-based solution as an alternative approach. The main contribution lies in the numerical link between the analytical field solution and the iron loss estimate, with the aid of a code implementation of the proposed methodology. First, the models are compared against a sufficiently dense dataset available from laminations manufacturer for validation purposes. Then, all the methods are compared for the slotless machine case. Finally, the models are applied to a real case study and validated experimentally.

A simple analytical method for accurate prediction of the leakage reactance and leakage energy in high-voltage transformers

Transformers are one of the most crucial pieces of equipment for the distribution and transmission of electric power. A high-voltage transformer plays a vital role to reduce power losses during the transmission of electricity. Leakage reactance plays a vital role in the working and stability of the transformer. The accurate prediction of the leakage reactance is a great asset to the transformer designers during the manufacturing stage to attain the dynamically optimum design of the transformer. In the literature, mostly given analytical techniques for leakage reactance calculations are applied to the transformers with the symmetric axial heights of the low-voltage, and high-voltage windings. Therefore, a proper analytical prediction for the leakage reactance in the transformer with asymmetric axial heights is needed to implement an optimized design. This paper proposes a new advanced method for an accurate calculation of the leakage reactance and leakage energies in different parts of the transformer with symmetrical and asymmetrical axial heights of the windings. Moreover, the finite element method and three different analytical methods are also compared with a new analytical technique for 5 real cases. For 2 cases, the proposed method’s results are also verified by experimental tests. The method’s accuracy in predicting the stored energy and leakage reactance of the high-voltage transformer is found to be more accurate and much simpler than the other analytical methods.