Search

Due to numerous distributed power sources connecting to the grid, which results in strong grid volatility and diminished power quality, the traditional energy storage configuration is limited in terms of flexibility and economy. Based on this, integrating electric vehicles (EVs) into the distribution network as energy storage devices has emerged as a promising development direction. This paper proposes a frequency-response optimization study considering the strong uncertainty model of EVs. First, from the perspective of temporal-spatial characteristics, energy storage resources, and users' willingness to respond, the strong uncertainty model of EVs is constructed by fitting the trip chain and the access probability of their participation in energy storage. Second, the frequency optimization model is integrated and constructed according to the response capability of a single EV. Finally, examples and scenarios are analyzed to verify that the maximum and minimum frequency offsets are reduced by 69.41% and 66.69%, respectively, which significantly reduces frequency fluctuations and stabilizes the output of EV clusters. [ABSTRACT FROM AUTHOR]

As a material screening equipment, vibrating screen is widely used in metallurgy industries due to their simple structure and low production cost. Nevertheless, the traditional vibrating screen box is prone to structural resonance due to low natural frequency and close to the system excitation frequency, which has a serious impact on the service life of the vibrating screen. In order to enhance the natural frequency of the vibrating screen box to avoid resonance, an optimization study of frequency of the vibrating screen was conducted using the response surface analysis method based on a genetic aggregation algorithm. The finite element model of the vibrating screen was established, and a comprehensive analysis of is modal frequency and mode shapes was performed through modal simulation and experimental testing to validate the accuracy of the model and simulation results. Additionally, structural optimization design was implemented using a reinforcement method with ribs, and the response surface method was employed to systematically investigate the influence patterns of rib width and thickness on the modal frequency. Various reinforcement schemes with different rib configurations were designed, and the impact of reinforcement positions on the enhancement of modal frequency was studied. The results indicate that adding ribs at the beams significantly increases the modal frequency of the vibrating screen box. Specifically, the sensitivity of modal frequency to rib thickness is relatively low, while the sensitivity to rib width is higher. The most significant enhancement in modal frequency was observed when reinforcing the intermediate layer of the screen box. By adding reinforced panels to the middle and lower three layers above, the natural frequency of the first four stages of the screen box can be increased by more than 60%, and the optimization effect is good. Through the optimization of the modal frequency, the natural frequency of the vibrating screen can be far away from the exiting frequency, which can effectively solve the structural resonance problem. The aforementioned research findings provide valuable insights and references for the optimization design of the strength and stiffness of vibrating screen boxes. [ABSTRACT FROM AUTHOR]

Aiming at the low-frequency line spectrum noise characteristics of power equipment noise, based on the principle of energy degradation, this paper combines the energy degradation sound insulation structure with the dynamic vibration absorption technology for the first time and applies it to the research field of noise control of power equipment in substations. Dynamic vibration absorption technology is used to effectively control low-frequency vibration and noise. Considering that there is an upper limit to the capacity of DVA, the sound-vibration energy degradation design of the transformer is completed by setting a sound insulation structure on the outside of the original transformer housing. It is analyzed that the vibration energy of the sound insulation structure in the specific frequency band is significantly reduced compared to the transformer housing, realizing efficient degradation of the vibration energy of the transformer housing and effective isolation of sound radiation. Through the optimized design of dynamic vibration absorption for the sound insulation structure, the structural sound isolation ability at the target frequency is further strengthened, and the system noise radiation level is greatly reduced under the action of multiple mechanisms at the target frequency, verifying the feasibility and high efficiency of the optimal DVAs energy degradation design of the transformer. [ABSTRACT FROM AUTHOR]

Due to numerous distributed power sources connecting to the grid, which results in strong grid volatility and diminished power quality, the traditional energy storage configuration is limited in terms of flexibility and economy. Based on this, integrating electric vehicles (EVs) into the distribution network as energy storage devices has emerged as a promising development direction. This paper proposes a frequency-response optimization study considering the strong uncertainty model of EVs. First, from the perspective of temporal-spatial characteristics, energy storage resources, and users’ willingness to respond, the strong uncertainty model of EVs is constructed by fitting the trip chain and the access probability of their participation in energy storage. Second, the frequency optimization model is integrated and constructed according to the response capability of a single EV. Finally, examples and scenarios are analyzed to verify that the maximum and minimum frequency offsets are reduced by 69.41% and 66.69%, respectively, which significantly reduces frequency fluctuations and stabilizes the output of EV clusters.

This research article proposes Model-Free Predictive Control and a Modified Multi-Phase shift Pulse Width Modulation technique for a semi-dynamic Wireless Resonant Inductive Power Transfer for an Electric Vehicle charging system. The semi-dynamic wireless Electric Vehicle charging system recently gained considerable attention in facilitating the user-friendly Electric Vehicle charging infrastructure. The airgap coupling factor and load resistance are significant parameters of the WRIPT system and highly influence power transfer efficiency. By operating the system in constant voltage mode, and realizing the high-power factor, the life span of the equipment is enhanced. The Model-Free Predictive Control scheme addresses the dynamic variations in the system power transfer, by automatic resonant frequency optimization control technique. The input impedance (imaginary part) is considered to introduce three mega parameters into the control functions, it makes the system control independent. The objective is to operate the receiver coil of the EV online at a resonant frequency with the transmitter coil, even when the receiver coil is in a semi-dynamic moving state. Especially, when the receiver coil shifts to align between two transmitter coils on the e-lane, to achieve continuous charging. The group-based frequency control technique is used in the proposed Model-Free Predictive Control, it reduces the dynamic computation burden, enhances the system accuracy, and response speed, and ensures safe operation. The proposed control technique is experimented with to investigate its effectiveness.

To solve the problem where the space vector pulse width modulation (SVPWM) of a three-phase inverter produces large harmonic components near the switching frequency (fs) and its doubling frequency, a frequency-optimized random switching frequency SVPWM (FORSF-SVPWM) control strategy is proposed in this paper. In this strategy, the basic principle of the chaotic ant colony algorithm in path optimization is used to determine the optimized scheme of the switching frequency distribution in the FORSF-SVPWM. Research shows that the frequency sample formed by the sigmoid function curve in the switching frequency range can cause the energy that was originally concentrated on the switching frequency and its doubling frequency to be more evenly distributed in the whole frequency range. Moreover, the amplitude of each harmonic wave is shown to be suppressed. The proposed strategy reduces the high-frequency noise and conducted electromagnetic interference (EMI) existing in power switching circuits. Thus, this strategy is obviously better than the traditional random switching frequency SVPWM (RSF-SVPWM) algorithm with its approximately uniform frequency distribution. Simulation and experimental results show that this strategy can work well in the hardware platform of a three-phase inverter without changing the topology of the main circuit of the system. In addition, this strategy is easy to implement. [ABSTRACT FROM AUTHOR]

Facilitating charging of Electric Vehicles (EVs), dynamic Inductive Power Transfer (IPT) technology has recently gained considerable attention. Yet, stabilizing the transferred power under different load resistances and coupling coefficients is still an issue. On the other hand, realizing high power factor (PF) operation in constant voltage (CV) operation increases the life of equipment in the system. A new model-free predictive control (MFPC) for DWPT systems is proposed in this paper based on the frequency optimization. The imaginary part of the input impedance is expressed as a function mega parameter. The control system becomes independent of the system parameter by calculating the mega parameters. Also, the group-based control approach used in the MFPC method, reduces the computing burden, improves the system dynamics, and avoids unsafe operating points. Moreover, the system output voltage is regulated by adjusting the duty cycle of the inverter. Simulation and experimental results validate the effectiveness of the proposed method.

Frequency optimization plays a vital role in designing machines and structures to avoid destructive responses caused by external excitation. In the current study, most frequency optimization research focuses on algorithm innovation to pursue better numerical results. However, with the development of additive manufacturing, increasingly more organic structures produced by topology optimization can be physically fabricated. Therefore, the combination of topology optimization and additive manufacturing is promising and widely investigated. This paper proposes a concurrent topology optimization method for maximizing the natural frequency of Fused Deposition Modelling (FDM) parts printed by a Hybrid Deposition Path (HDP) pattern. The proposed algorithm concurrently optimizes the shape of the structure and the raster directions of the substrate domain, wherein the method of solid orthotropic materials with penalization (SOMP) with double layers of smoothing and projection (DSP) is adopted. A dedicated sensitivity analysis is performed on both the topology and direction variables. Several numerical results are studied to show the effectiveness of the proposed method is efficient and to disclose the influence of raster direction on the vibration model. This work would be instructive to design for FDM printing. [ABSTRACT FROM AUTHOR]

This study presents a new approach as an integration of deep neural networks (DNN) into differential evolution (DE) to give the so-called DNN-DE for frequency optimization of laminated functionally graded carbon nanotube (FG-CNT)-reinforced composite quadrilateral plates under free vibration. In the presented approach, the DNN is applied to predict the objective and constraints during the optimization process instead of using the time-consuming finite element analysis (FEA) procedures while the DE is used as an optimizer for solving the optimization problem. Several numerical examples are performed to illustrate the performance of the proposed method. Optimal results obtained by the DNN-DE are compared with those achieved by other methods in order to show the reliability and effectiveness of the proposed methodology. Additionally, the influence of various parameters such as the boundary condition, the carbon nanotube (CNT) volume fraction, the CNT distribution on the optimal results is also investigated. The obtained results indicate that the proposed DNN-DE is an effective and promising method in solving optimization problems of engineering structures. [ABSTRACT FROM AUTHOR]

Metal foreign objects will not only reduce the output power and efficiency of the wireless power transfer (WPT) system, but also will be heated under the eddy current effect. The method based on the detection coil array has been wildly adopted for foreign object detection (FOD), especially in high-power level WPT applications. However, the problems of low sensitivity or misjudgment still exist which leads to a safety hazard. Therefore, high sensitivity of the foreign object-detection method based on the excitation frequency optimization has been proposed in this paper. Based on the impedance change of the detection coil caused by the foreign object coupling, the frequency characteristics of detection sensitivity were analyzed under the conditions of different self-inductance detection coils. Then, the detection coil was designed and its corresponding optimal excitation frequency was selected to achieve the optimal detection effect to eliminate the area of low detection sensitivity. Finally, an FOD experimental prototype was established to verify the proposed frequency optimization strategy. The results show that the sensitivity of the FOD system is up to 97.56%. With the optimal excitation frequency of 6.22 MHz, as for 1-yuan coin in the center position and corner position of the detection coil, the detection sensitivity is 92.89% and 40.16%, respectively, which is 22.13% and 23.89% higher than that of the excitation frequency is 1 MHz. The improvement of detection sensitivity is helpful to detect accurately and eliminate the detection blind area. [ABSTRACT FROM AUTHOR]

The selection of signal frequency in acoustic temperature measurement technology is the key to improve the accuracy of temperature measurement. In order to explore the optimal propagation frequency of low-frequency sound waves in loose coal, lignite, coking coal, and anthracite are used as the research objects. The acoustic loss of three coal samples under six particle sizes（0.9 mm to ＜3 mm, 3 mm to ＜5 mm, 5 mm to ＜7 mm, 7 mm to 10 mm, 9 mm to 10 mm and larger than 10 mm） by using the acoustic loss test system is tested. The experimental results show that the sound transmission loss of three coal samples presents a wave-like rising shape with the increase of the sound wave frequency. Compared with coal samples of other particle sizes, the sound transmission loss of coal samples in the range of 0.9 mm to ＜3 mm is the largest. As the particle size of coal samples increases, the sound transmission loss of coal samples continues to increase, and the sound wave frequency corresponding to the lowest point of sound transmission loss also increases. The degree of coal sample deterioration has no obvious regularity in the influence of sound transmission loss. The sample size is the main factor that affects the change of the sound transmission loss of the coal sample, and the sound waves mainly propagate along the gaps between the particle sizes of the loose coal. By comparing and analyzing the maximum and minimum values of sound transmission loss, there is a maximum value between 250 Hz to 600 Hz and 900 Hz to 1 600 Hz about the sound transmission loss of coal samples of different particle sizes, and the maximum sound transmission loss range is between 4.66 dB and 7.64 dB. By testing the sound transmission loss in the low-frequency sound waves of the mixture of three coal samples, it is determined that the optimal sound transmission frequency range in the loose coal is 600 Hz to 900 Hz.

Inadequate drying and overdrying of grains due to the absence of timely and reliable information on moisture content (MC) aggravates grain postharvest loss. In this study, we investigate the real-time acquisition of MC using microwave free-space transmission measurements. A multifrequency swept signal is used to acquire the attenuation and phase-shift spectrum (2.00–10.00 GHz) of the paddy samples (9.553%–29.633% w.b.) for six thicknesses (1–6 cm). Based on the four rules that are followed in the phase-shift measurement, a phase-shift correction algorithm without any restrictions on the sample thickness is proposed to solve the phase-shift ambiguity that occurs when the sample thickness exceeds the wavelength. To choose the most effective frequencies, 17 candidate frequency subsets are generated by the recursive feature elimination algorithm, and the optimal frequency set, containing eight individual frequencies, is selected by using the Friedman and Nemenyi post hoc tests. The sample thickness and microwave characteristics are used as the input variables to establish the prediction models to achieve a thickness-independent measurement of the MC, and the support vector machine model yielded the best performance ($R^2$ = 0.992, RMSE = 0.555%, and MAE = 0.398%). The results of this study should encourage future research on the real-time acquisition of reliable MC information in food processing and agriculture-related industries. [ABSTRACT FROM AUTHOR]

Copyright of Electric Machines & Control / Dianji Yu Kongzhi Xuebao is the property of Electric Machines & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

• We identify a new phenomenon we call the danger zone of express services. • Raising express service frequencies can damage the level of service in a corridor. • Under certain conditions, this effect occurs in a specific range of frequencies. • The effect happens when the express draws in more demand than it can carry. • We use queuing theory to model and measure this effect on an idealized corridor. Express bus services are services that skip some of the stops along their routes to provide a faster ride for particularly demanded trips on a corridor. There is a growing literature on express services that focuses on route design and performance evaluation. In this work, we study a simplified transit corridor where a regular service operates in tandem with an end-to-end express service. Assuming that passengers minimize their expected travel and waiting times, we show that, even if the system has enough aggregate capacity, it may present a specific range of frequencies for the express service where it attracts more demand than it can actually fulfill. We call this range the "danger zone" of express services. When frequencies fall within the danger zone, a queue of passengers will form at the station. Applying queuing theory, we obtain expressions to estimate these queues and the associated waiting times, expected travel times and social costs of the system. We show that even when the station has unlimited passenger capacity, the performance of the system can be greatly affected in the danger zone. If the station has indeed limited capacity, the scenario can be much worse: if the queue grows to the point of saturating the station, a vicious circle ensues that amplifies the negative effects of the danger zone. [ABSTRACT FROM AUTHOR]

Overcrowding in public transport (PT) is one of the major issues and should be improved in order to make the PT system more attractive in megacities. However, most of the mathematical models do not consider the cost of crowding discomfort faced by the users in the total cost minimization objective function while determining the optimum frequency of PT systems. This work develops a mathematical model that explicitly considers this aspect. The work first develops an exponential function of crowding multiplier with load factor and then uses it to determine the cost of crowding discomfort. The work is applied to a real-life network of 34 bus routes of Delhi, India. Lastly, the work also presents sensitivity analysis with the value of waiting time and travel demand and provides policy and planning implications for the Delhi bus network. [ABSTRACT FROM AUTHOR]

The classic bi-directional evolutionary structural optimization (BESO), which is known as “hard kill” in nature, discretely removes the inefficient material in the continuum structure. Using BESO method, structural stiffness and mass matrix of the elements under low sensitivity and inefficiently utilized suddenly reduced. It means that when solving structural topological optimization, highly efficient elements are possibly incorrectly deleted by original BESO. As a result, the smooth bi-directional evolutionary structural optimization (SBESO), as a variant of the BESO procedure, is proposed to overcome this disadvantage. The introduced SBESO was based on the philosophy that if an element was not really necessary for the structure, its contribution to the structural stiffness and mass would gradually diminish until it no longer influenced the structure. This removal process was thus performed smoothly. This procedure was known as ‘‘soft-kill’’ in nature; where not all of the elements removed from the structure domain using the original BESO criterion were rejected. The weighted function was introduced to regulate element’s mass and stiffness matrix, combined with controlling the element deletion rate to make inefficient elements gradually deleted. This method provides good conditioning for the new system of equations that can be resolved in the next iteration because these elements are important to the structure. In this paper, the proposed SBESO method was applied to resolve the structural dynamic topology optimization including frequency optimization and dynamic stiffness optimization of continuum structure under harmonic force excitation. The frequency optimization model was developed to increase the fundamental natural frequency of continuum structure which was away from the frequency of the external force. The dynamic stiffness model was derived to perform structural optimal design according to the structural strain energy of the continuum structure under dynamic load. Aiming at maximizing the natural frequency of continuum structure, the SBESO procedure was employed to solve it. Subsequently the effect of various weighted function including constant, linear and trigonometric function on topology optimization was compared and analyzed. Performing the structural topology optimization of dynamic stiffness in the time domain was quite expensive due to heavy computational time for function and sensitivity. Thus the equivalent static loads (ESL) method in the time domain was used to overcome these disadvantages. Combining ESL and SBESO, structural topology optimization of dynamic stiffness was resolved at ease for the continuum structure under dynamic load. Numerical results showed that SBESO could inhibit the incorrect element deletion, by regulating the element deletion rate and weighted function. Therefore the inefficient elements would gradually diminish. It was also found that the employed linear and trigonometric functions more contributed to obtaining the optimal solution of frequency for the continuum structure compared with constant function. In addition, decreasing element deletion rate aroused increasingly smooth boundary of optimal configuration in structural topology which converged to identical configuration by SBESO. Consequently the optimization method of SBESO improves the original optimization criterion of BESO, which is significantly theoretical to address the dynamic optimization design of continuum structures. [ABSTRACT FROM AUTHOR]

The optimal match of multiple operation parameters in heat transfer systems (HTSs) is the key to trade‐off heat transfer and flow resistance for energy conservation. For a compound series‐parallel HTS, this study applies the power flow model and the driving‐resistance model to build the heat transfer and fluid flow constraints of the whole system directly, instead of individual components. Utilizing these constraints together with the Lagrange multiplier method offers the optimal operating frequencies of each variable frequency pumps (VFP) with the minimum pumping power consumptions under different heat loads. Operating the experiment platform with the optimized parameters shows that the heat load increment in parallel branches only needs to increase the operating frequency of VFP in the related hot‐water loop, whereas the heat load increment in series branches needs to increases the operating frequencies of VSPs in both cold‐water and the corresponding hot‐water loops. When the heat load varies from 10 to 11 kW in the parallel branch, the downstream, and the upstream of the series branch, the total pumping power consumptions of all VFPs increase by 19.45%, 43.86%, and 39.99%, respectively. It means assigning the additional heat load in the parallel branch is more energy efficient. Applying the power flow model and the driving‐resistance model to build the global heat transfer and fluid flow constraints of a compound series‐parallel system directly. Using the Lagrange multiplier method offers the optimal operating frequencies of each variable frequency pump with the minimum power consumptions under different heat loads. [ABSTRACT FROM AUTHOR]

To achieve in-situ monitoring of the occurrence of grain mildew and ensure food safety, this study took paddy grains as the object and carried out the discrimination of paddy mildew based on microwave dielectric properties. The multi-frequency swept measurement technique was used to acquire the dielectric constant (DC) and dielectric loss factor (DLF) spectra (2.00–10.00 GHz) of healthy samples and samples with different moldy paddy content. To choose the most effective frequencies, 20 frequency subsets (DC subset 1–10, DLF subset 1–10) were generated by an algorithm coupled with the successive projections algorithm and partial least-squares discriminant analysis. Afterwards, four key frequencies were determined from the 100 pairwise combinations of the two types of frequency subsets by exhaustive method. Dielectric properties at key frequencies and sample thickness were used as the input variables to establish the discriminating model for paddy mildew. The established microwave dielectric properties-based model achieved 100% accuracy in distinguishing healthy and moldy samples, showing perfect discriminant validity. Moreover, only 4.4% of those samples whose MPC was at a low level (≤30%) were misclassified by the model, and the discrimination model achieved 97.29% overall accuracy. The results of this study should encourage future research on dielectric-based mildew detection in food processing and agriculture-related industries. • A microwave dielectric-based method for achieving rapid mildew discrimination of paddy grains is proposed. • A SPA-PLSDA combined algorithm to retain the most effective measurement frequencies is proposed. • The mildew information of paddy grains can be obtained through a detection system with mobile App. [ABSTRACT FROM AUTHOR]

The mechanism of the fifth-order inter-modulation was discussed,and a frequency optimization algorithm for reducing the network inter-modulation interference was proposed.The inter-modulation interference produced by frequency combination can be suppressed when the TCH frequencies combination of the cell meets the following requirement:935×106≤fmin＜fmax≤954×106Hz,and the difference between the maximum number and minimum number of frequency points is less than 65.This method can suppress the inter-modulation interference from the source,and provides an innovative idea for inter-modulation interference optimization.

An axial design of a capacitively coupled contactless conductivity detector was tested in combination with fused-silica capillaries with internal diameters of 10, 15, and 25 μm, which are used for high-efficiency electrophoretic separation. The transmission of the signal in the detection probe dependent on the specific conductivity of the solution in the capillary in the range 0-278 mS.m−1 has a complex character and a minimum appears on the curve at very low conductivities. The position of the minimum of the calibration dependence gradually shifts with decreasing frequency of the exciting signal from 1.0 to 0.25 MHz toward lower specific conductivity values. The presence of a minimum on the calibration curves is a natural property of the axial design of contactless conductivity detector, demonstrated by solution of the equivalent electrical circuit of the detection probe, and is specifically caused by the use of shielding foil. The behavior of contactless conductivity detector in the vicinity of the minimum was documented for practical separations of amino acids in solutions of 3.2 M acetic acid with addition of 0-50% v/v methanol. [ABSTRACT FROM AUTHOR]

A reliable and accurate inspection of the hollow axle inner surface is important for the safe operation of high-speed trains. In order to improve the reliability of the inspection, a flexible arrayed eddy current sensor for non-destructive testing of the hollow axle inner surface was designed, fabricated and characterized. The sensor, consisting of two excitation traces and 28 sensing traces, was developed by using the flexible printed circuit board (FPCB) technique to conform the geometric features of the inner surfaces of the hollow axles. The main innovative aspect of the sensor was the new arrangement of excitation/sensing traces to achieve a differential configuration. Finite element model was established to analyze sensor responses and to determine the optimal excitation frequency. Experimental validations were conducted on a specimen with several artificial defects. Results from experiments and simulations were consistent with each other, with the maximum relative error less than 4%. Both results proved that the sensor was capable of detecting longitudinal and transverse defects with the depth of 0.5 mm under the optimal excitation frequency of 0.9 MHz. [ABSTRACT FROM AUTHOR]

Eddy current testing is quite a popular non-contact and cost-effective method for nondestructive evaluation of product quality and structural integrity. Excitation frequency is one of the key performance factors for defect characterization. In the literature, there are many interesting papers dealing with wide spectral content and optimal frequency in terms of detection sensitivity. However, research activity on frequency optimization with respect to characterization performances is lacking. In this paper, an investigation into optimum excitation frequency has been conducted to enhance surface defect classification performance. The influences of excitation frequency for a group of defects were revealed in terms of detection sensitivity, contrast between defect features, and classification accuracy using kernel principal component analysis (KPCA) and a support vector machine (SVM). It is observed that probe signals are the most sensitive on the whole for a group of defects when excitation frequency is set near the frequency at which maximum probe signals are retrieved for the largest defect. After the use of KPCA, the margins between the defect features are optimum from the perspective of the SVM, which adopts optimal hyperplanes for structure risk minimization. As a result, the best classification accuracy is obtained. The main contribution is that the influences of excitation frequency on defect characterization are interpreted, and experiment-based procedures are proposed to determine the optimal excitation frequency for a group of defects rather than a single defect with respect to optimal characterization performances. [ABSTRACT FROM AUTHOR]

The thickness optimization is used to regulate the dynamic response of a thin plate of arbitrary geometry subjected to any type of admissible boundary conditions. The optimization problem consists in establishing the thickness variation law for which the fundamental frequency is maximized, minimized or forced to reach a prescribed value. Beside the equality constraint of constant volume, the thickness variation is subjected also to inequality constraints resulting from serviceability requirements (upper and lower thickness bounds) as well as to a nonlinear inequality constraint which ensures that the optimum solution remains within the limits of Kirchhoff plate theory. The evaluation of the objective function requires the solution of the dynamic bending problem of a plate with variable thickness which is solved using the analog equation method in conjunction with the boundary element method. A nonlinear optimization problem is formulated, and the optimum solution is obtained through the sequential quadratic programming algorithm. The thickness is approximated using integrated radial basis functions which approximate accurately not only the thickness function but also its first and second derivatives involved in the plate equation and in the constraints. Several plate optimization problems have been studied giving realistic and meaningful optimum designs without violating the validity of the thin plate theory. [ABSTRACT FROM AUTHOR]

To better solve the passenger assignment problem, which is a subproblem of the transit network optimization problem, we build an artificial urban transit system (AUTS) and adopt a day-to-day learning mechanism to describe passengers' route and departure-time-choice behaviors. With the support of AUTS to handle the lower level assignment problem, we are able to solve the upper level transit network design problem. Compared with other bilevel models, our approach better accommodates passengers' dynamic learning behavior and their heterogeneity. Based on AUTS, we solve the frequency optimization problem and compare the results with an analytical method. We also perform some numerical experiments on AUTS and discover some interesting issues on the capacity of public transportation system and passengers' heterogeneity. [ABSTRACT FROM PUBLISHER]

Abstract: Electrochemical impedance spectrum frequency optimization to bitter taste receptor cell-based sensors is discussed in this paper. The bitter taste receptor cells (the enteroendocrine STC-1 cells and the ICR mouse isolated taste bud cells) are cultured on carbon screen printed electrodes and used as sensing elements. The HEK-293 cells and dead isolated ICR mouse taste bud cells, without bitter taste receptor expression, are used in negative control experiments. The electrochemical impedance spectrum data is recorded and processed by bistable stochastic resonance for signal-to-noise ratio analysis. The bitter taste receptor cell-based sensor selectively responds to bitter tastants. The tastants species and concentrations can be decided by signal-to-noise ratio parameters. The signal-to-noise ratio eigen peak changes with the shift of electrochemical impedance spectrum frequencies. ICR mouse isolated taste bud cell-based sensor presents bitter tastants perception abilities. 9kHz is the optimal frequency for STC-1 cell-based sensor measurement. For isolated ICR mouse taste bud cells, 1.2kHz is the optimal frequency. Negative control experiments results indicate that cells with no taste receptor expression have no discriminating ability for tastant even if they are modulated by different frequencies. The taste cell-based sensor is of great practical value. [Copyright &y& Elsevier]

The current techniques for topology optimization of material microstructure are typically based on infinitely small and periodically repeating base cells. These base cells have no actual size. It is uncertain whether the topology of the microstructure obtained from such a material design approach could be translated into real structures of macroscale. In this work we have carried out a first systematic study on the convergence of topological patterns of optimal periodic structures, the extreme case of which is a material microstructure with infinitesimal base cells. In a series of numerical experiments, periodic structures under various loading and boundary conditions are optimized for stiffness and frequency. By increasing the number of unit cells, we have found that the topologies of the unit cells converge rapidly to certain patterns. It is envisaged that if we continue to increase the number of unit cells and thus reduce the size of each unit cell until it becomes the infinitesimal material base cell, the optimal topology of the unit cell would remain the same. The finding from this work is of significant practical importance and theoretical implication because the same topological pattern designed for given loading and boundary conditions could be used as the optimal solution for the periodic structure of vastly different scales, from a structure with a few (e.g. 20) repetitive modules to a material microstructure with an infinite number of base cells. [ABSTRACT FROM AUTHOR]

Abstract: The eddy current Thermography is an evolving non-contact, non-destructive evaluation method with applications especially in aircraft industries. It involves two approaches (a) the volumetric heating (skin depth much greater than the thickness) of the specimen and the observation of additional heating at defect locations due to Joule heating (called eddy-therm) and (b) the use of high-frequency eddy current bursts (skin depth is smaller than the thickness) for the transient surface/near surface heating of the objects and sensing the propagation of a “thermal wave” using a high-sensitivity infrared (IR) camera (tone burst eddy-current thermography (TBET)). In this paper, a study on the optimum frequency of eddy current excitation that will give a maximum temperature rise for a given thickness has been conducted using both modeling and experimental techniques. COMSOL 3.2 was used to solve the coupled equations of electromagnetic induction and heat transfer. The dependency of this optimum frequency (peak frequency) on thickness, electrical conductivity, and thermal response of the sample are studied. The relation between defect size and the coil inner radius is considered. The thermal responses of defective samples obtained by simulation are compared with experimental results. [Copyright &y& Elsevier]

In this paper, a linear two-degree-of-freedom quarter car model is used to derive a number of analytical formulae describing the dynamic behaviour of passively suspended vehicles running on a harmonically bumped road. The linearity of the system allows us to analytically investigate the steady-state response characteristics. We derive analytical expressions for the root mean square (RMS) of the sprung mass absolute acceleration and relative displacement. This paper demonstrates the shortcomings of existing classical optimization methods. Hence we introduce a new optimization method based on minimizing the absolute acceleration RMS with respect to the relative displacement RMS. The RMS optimization method is applied for the symbolic derivation of analytical formulae featuring the best compromise among conflicting performance indices pertaining to the vehicle suspension system, i.e ., sprung mass acceleration and working space. The proposed optimization technique is utilized to find the optimal damping and stiffness curves for the main suspension. The RMS optimal values are used to create design charts for suspension parameters, which are very useful particularly in the presence of physical constraints such as a limit on relative displacement. We introduce a numerical example to illustrate the optimality of the obtained solutions. [ABSTRACT FROM AUTHOR]

In this paper, a bilevel programming model for transit network design problem is presented, in which the upper model is a normal transit network design model, and the lower model is a transit equilibrium assignment model. A heuristic solution algorithm based on sensitivity analysis is designed for the model proposed. Finally, a simple numerical example is given to illustrate the application of the model and algorithm and some conclusions are drawn. [Copyright &y& Elsevier]

This paper addresses the problem of the frequency optimization of transit lines in a congested transit network. We consider the transit frequency optimization model proposed by Constantin and we modify it to consider vehicles capacity indirectly. The model is formulated as a two levels Min-Min optimization problem with the same objective function at both levels. This function represents the transportation time including a congestion penalty. The upper level corresponds to the transit operator's optimization problem and the lower level describes the users' behavior. A descent direction for the problem is obtained by using sensitivity analysis of the lower level problem. Computational results are presented for the Winnipeg (Canada) and the Stockholm (Sweden) transit networks. [ABSTRACT FROM AUTHOR]

[Display omitted] • Microstructure classes are mapped into an interpretable and continuous latent space. • Microstructure classes and their volume fractions are concurrently optimized. • Using multiple classes enables higher natural frequencies than single-class designs. • Multiscale designs achieve higher frequencies than single-scale solid designs. • The efficiency of multiscale multiclass design is comparable to single-scale design. For natural frequency optimization of engineering structures, cellular composites have been shown to possess an edge over solid. However, existing multiscale design methods are either computationally exhaustive or confined to a restrictive class of microstructures. In this paper, we propose a data-driven topology optimization (TO) approach to enable the multiscale cellular designs with multiple choices of microstructure classes. The key component is a newly proposed latent-variable Gaussian process enhanced with the sum of separable kernels (LVGP-SoS). It maps different classes of microstructures into a low-dimensional continuous latent space that could capture the correlation of different classes. By introducing latent vectors as design variables, a continuous and differentiable transition of the stiffness matrices between different classes can be achieved, together with an analytical gradient. After integrating the LVGP models with the classical TO, an efficient data-driven cellular composite optimization process is developed to enable concurrent exploration of microstructure classes and their volume fractions for natural frequency optimization. Examples reveal that the proposed designs with multiclass microstructures achieve better performance in maximizing natural frequencies than both single-scale and single-class designs. The same design framework can be easily extended to other multiscale TO problems, such as thermal compliance minimization and dynamic response optimization. [ABSTRACT FROM AUTHOR]

This study proposes a robust and effective evolutionary shape optimization methodology for bell design. Axisymmetric bell profiles are defined within a 2D-half-cross-sectional design space, from which a 3D finite element model is constructed. An objective function is formulated in terms of a desired tuning spectrum and evaluated through a modal analysis. A pseudo-velocity of the boundary profile is derived via a sensitivity analysis and is used to iteratively evolve the design and minimize the tuning error. A series of computational design examples are provided demonstrating effective tuning of up to twelve partial frequencies simultaneously with tuning accuracy equal to or improved with respect to hand-tuned bell data in current literature. Finally, the proposed method is experimentally validated through fabrication of a prototype bell which exhibits close correlation of partial frequencies with its computational model. [ABSTRACT FROM AUTHOR]

Understanding optical properties of food and agricultural products is essential to apply optical techniques for quality and safety assessment. This research was aimed at optimizing the frequency region through an inverse algorithm for better quantification of the optical absorption (μ a) and reduced scattering (μ s ′) coefficients of two-layered food and agricultural products from spatial-frequency domain reflectance. The frequency region, defined by start and end frequencies, was first optimized for parameter estimations of the first and second layers, respectively. Estimation accuracies were then validated by comparing with the conventional all-at-once method through Monte Carlo simulations. On average, accuracies for estimating μ a1 , μ a2 and μ s2 ′ by using the optimized frequency region were improved by 52.9%, 63.0% and 62.1%, respectively, compared to the results by using fixed frequency region before optimization. No improvement for the estimated μ s1 ′ was found because its mean absolute error was already very low (2.4%) and well within the acceptable level. Experimental results for two-layered solid phantoms and liquid milk samples in the wavelengths of 650–830 nm further validated the effectiveness of stepwise method with the optimized frequency region. Finally, the stepwise method, coupled with the optimized frequency region was used to estimate the optical properties of skin and flesh of apples for four cultivars (i.e., Delicious, Golden Delicious, Jonagold and Red Rome). The results were compared with those obtained using the single integrating sphere technique, followed with a discussion on the optical property discrepancies obtained by these two methods. • Optimal frequency ranges for SFDI to estimate optical properties of two-layered samples were determined. • Frequency optimization greatly improved optical property estimations of two-layered samples. • Proposed stepwise method achieved superior performance for optical property estimations. • SFDI was used to quantify and map apple skin and flesh optical properties. [ABSTRACT FROM AUTHOR]