Multi-parameter Optimization Research Articles

Parametric study and multi-parameter optimization of a generalized second-order tri-stable stochastic resonance system

Parametric study and multi-parameter optimization of a generalized second-order tri-stable stochastic resonance system

Pantograph–Catenary Interaction Prediction Model Based on SCSA-RBF Network

As a traditional numerical simulation method for pantograph–catenary interaction research, the pantograph–catenary finite element model cannot be applied to the real-time monitoring of pantograph–catenary contact force, and the computational cost required for the multi-parameter joint optimization of the pantograph–catenary system with the finite element model is very high. In this paper, based on the selective crow search algorithm–radial basis function (SCSA-RBF) network, the time-domain signal of the panhead acceleration, which can be obtained in real-time through non-contact test technology, is taken as the boundary condition to directly solve the pantograph dynamic equation and a data-physics coupling model that can quickly predict the pantograph–catenary interaction is proposed. The prediction model is trained and verified using the dataset generated through the finite element model. Furthermore, the prediction model is applied to the multi-parameter joint optimization of six pantograph dynamic parameters and nine pantograph dynamic parameters, considering nonlinear panhead stiffness, and optimization suggestions under various speeds and filtering frequencies are given.

C2 Product Formation over the C1 Product and HER on the 111 Plane of Specific Cu Alloy Nanoparticles Identified through Multiparameter Optimization.

C2 products are more desirable than C1 products during CO2 electroreduction (CO2ER) because the former possess higher energy density and greater industrial value. For CO2ER, Cu is a well-known catalyst, but the selectivity toward C2 products is still a big challenge for researchers due to complex intermediates, different final products, and large space of the catalyst due to its morphology, plane, size, host surface etc. Using density functional theory (DFT) calculations, we find that alloying of Cu nanoparticles can help to enhance the selectivity toward C2 products during CO2ER with a low overpotential. By a systematic investigation of 111 planes (which prefer the C1 product in the case of bulk Cu), the alloys show the generation of C2 products via *CO-*CO dimerization (* indicates adsorbed state). It also suppresses the counter-pathway of hydrogenation of *CO to *CHO, which leads to C1 products. Further, we find that *CH2CHO is the bifurcating intermediate to distinguish between ethanol and ethylene as the final product. We have used simple graphical construction to identify the catalyst for CO2ER over HER, and vice versa. We have also defined the case of hydrogen poisoning and projected a parity plot to recognize the catalyst for C2 product evolution over the C1 product. Our study reveals that Cu-Ag and Cu-Zn catalysts selectively promote ethanol production on 111 planes. Moreover, an edge-doped 2SO2 graphene nanoribbon as the host layer further lowers the barrier and selectively promotes ethanol on Cu38- and Cu79-based alloys. This work provides new theoretical insights into designing Cu-based nanoalloy catalysts for C2 product formation on the 111 plane.

Trends in Neosubstrate Degradation by Cereblon-Based Molecular Glues and the Development of Novel Multiparameter Optimization Scores.

Molecular glues enable the degradation of previously "undruggable" proteins via the recruitment of cereblon (CRBN) to the target. One major challenge in designing CRBN E3 ligase modulating compounds (CELMoDs) is the selectivity profile toward neosubstrates, proteins recruited by CRBN E3 ligase agents for degradation. Common neosubstrates include Aiolos, Ikaros, GSPT1, CK1α, and SALL4. Unlike achieving potency and selectivity for traditional small molecule inhibitors, reducing the degradation of these neosubstrates is complicated by the ternary nature of the complex formed between the protein, CRBN, and CELMoD. The standard guiding principles of medicinal chemistry, such as enforcing hydrogen bond formation, are less predictive of degradation efficiency and selectivity. Disclosed is an analysis of our glutarimide CELMoD library to identify interpretable chemical features correlated to selectivity profiles and general cytotoxicity. Included is a simple multiparameter optimization function using only three parameters to predict whether molecules will have undesired neosubstrate activity.

Drilling of Ti Grade‐2 Alloy Using WC Tool in Micro‐EDM and Its Multiparameter Optimization

In this study, microelectrical discharge machining (μEDM) is used for drilling microholes on a thin sheet of Ti Grade 2 alloy of thickness 50 μm using a tungsten carbide (WC) microtool of diameter 470 μm. The main focus of the study is to understand the electrical and nonelectrical μEDM parameters on the accuracy, precision, and machining efficiency of drilled holes. The controllable process factors such as capacitance, voltage, tool rotation, and feed rate are considered when conducting the experiments based on a Taguchi L16 orthogonal array. The main effect and interaction contour plots have been prepared to investigate the influence of the process parameters on the response measures like material removal rate, overcut, circularity, and taper angle of the drilled holes. Analysis of variance (ANOVA) has been carried out to study the percentage contribution and significance of each process parameter on the performance measures. The micrographic images reveal the quality of the profiles and edges of the drilled holes. Further, the Overall Evaluation Criterion (OEC) is applied for multiparameter optimization.

Analysis of the effectiveness of using torsional vibration dampers for crankshafts with adaptive characteristics in internal combustion engines

The research aims to determine the effectiveness of torsional dampers with adaptive characteristics for crankshafts of piston internal combustion engines. The paper deals with the pressing issue of designing a torsional vibration damper for crankshafts of internal combustion engines, which can work efficiently in the entire operating range of speed variance. The standard approach to design the damper with constant characteristics implies one resonant operating mode, which in actual practice is not always justified. This fact decreases the operating efficiency, especially for the forced V-type engines. In order to determine the design parameters of dampers with adaptive characteristics, a multi-parameter optimization problem must be solved, which requires experimental validation. The work considers an approximate method, according to which the main parameters of the designed damper for different operating modes are determined. We obtained the general trend of changing the torsional damper characteristics by performing calculations for different engine operating modes. Based on these data, it is possible to determine the operating modes of the control mechanism. Comparing the efficiency of dampers with constant characteristics under the same modes allows validating the results’ adequacy. The scientific novelty lies in the developed method of modes determining torsional vibration damper parameters at changing speed and operating can help design new efficient forced internal combustion engines.

Effect of multi-parameter optimization of water-laser coupling device and nozzle geometry on the stability of water-guided laser beam

The stability of the water jet flow used in water-guided laser processing plays a crucial role in determining the quality of the processing process. The present study aims to investigate the effect of water-laser coupling device and nozzle geometry on the stable length of a water-guided laser beam. A numerical model is developed to analyze the internal flow field within the coupling device. Computational fluid dynamics (CFD) simulations are employed to examine how variations in cone nozzle's length-to-diameter ratio, divergence angle, nozzle aperture, and inlet pressure that affect the flow characteristics of water jet. Subsequently, the Latin Hypercube experimental design method is employed to establish parameter samples and construct a Kriging approximation model for the stable length of water-guided laser beam. The Multiple Island Genetic Algorithm (MIGA) is utilized for global optimization of the approximation model, while CFD methods are employed to analyze and validate the optimization results. Finally, experimental verification was conducted to determine the stable length of water-guided laser beam generated by the optimized cone nozzle structure. The research findings demonstrate that the optimized nozzle structure can compensate for approximately 21 mm in the stable distance of water-guided laser beam under the pressure of 5.0 MPa. This study provides valuable guidance for enhancing the performance and engineering applications of laser micro-jet processing technology.

Совершенствование модели организации поисково-спасательных работ в природной среде Республики Таджикистан

Introduction. The article describes the improvement of the model of organization of search and rescue operations in the natural environment of the Republic of Tajikistan, which can influence the management decisions of the head of search and rescue operations. The authors analyze the degree of readiness of rescuers to eliminate the consequences of accidents, dangerous natural phenomena and man-made disasters, as well as the methods of conducting search and rescue operations in the natural environment. Based on the analysis, it is proposed to introduce an additional criterion in determining the routes of redeployment of forces and means to the search site, which will improve the objectivity and information content of the model. Objectives of the study. Improving the mathematical model for determining optimal routes for the redeployment of forces and resources during rescue operations in the natural environment. Methods. General scientific and special methods of scientific knowledge were used to obtain the results: analysis, synthesis, generalization, which were based on the provisions of probability theory. Results and discussion. A multifactorial analysis of search and rescue operations in the natural environment of the Republic of Tajikistan was conducted. An assessment of the material damage caused to the state as a result of natural emergencies was made. The use of an additional criterion for choosing the route for the redeployment of forces and resources of the Committee for Emergency Situations and Civil Defense of the Republic of Tajikistan during rescue operations in the natural environment was substantiated. The material equipment of rescue units was studied. Conclusions. The obtained results allow us to determine the features and patterns of conducting search and rescue operations in the natural environment, which are necessary for a comprehensive assessment of the situation, the earliest possible decision on the optimal set of measures and the timely dispatch of forces and resources in order to detect and rescue persons in distress as soon as possible. Keywords: search and rescue management; theory of multiparameter optimization; analysis of emergency situations.

Pulsed laser deposition of Sb2S3 films for phase-change tunable nanophotonics

Non-volatile phase-change materials with large optical contrast are essential for future tunable nanophotonic applications. Antimony trisulfide (Sb2S3) has recently gained popularity in this field due to its low absorption in the visible spectral region. Although several Sb2S3 deposition techniques have been reported in the literature, none of them was optimized with respect to stoichiometry, lowest possible absorption, and large refractive index contrast (Δn) upon the phase change. Here we present a comprehensive multi-parameter optimization of pulsed laser deposition of Sb2S3 towards this end. We correlate the specific deposition with the resulting compositional and optical properties and report parameters leading to films with extraordinary qualities (Δn = 1.2 at 633 nm). Additionally, we suggest crystal orientations and vibrational modes associated with the largest change in the refractive index and propose them as useful large-scale indicators of the Sb2S3 switching contrast.

Parameters optimum of multiple underframe suspended equipment on high-speed railway vehicle carbody vibration control by using an improved genetic algorithm

Carbody vibration control and ride comfort improvement are important research parts of high-speed railway vehicle dynamic. The effectiveness of utilizing carbody underframe suspended equipment as dynamic vibration absorbers for carbody vibration suppression has been validated. While previous research has focused mainly on a single suspended equipment without considering its vibration tolerance, a balance must be struck between reducing carbody vibration and maintaining equipment performance. To address the challenging, a multi-objective and multi-parameter optimization method is employed, integrating an improved niche genetic algorithm (INGA) into the numerical simulation process. Considering carbody flexible and multi-suspended equipment, a rigid-flexible dynamics model of a high-speed railway vehicle is established and validated on a vehicle dynamics test rig. Based on the numerical analysis, the optimal parameter combination of the stiffness and the longitudinal installation position is obtained from an evaluation function that comprehensively assesses the vibration performance of both the vehicle carbody and the equipment. Comparative analysis between the results obtained from the optimal and primitive parameters demonstrates that the optimization process not only achieves significant improvements in carbody vibration reduction but also effectively controls equipment vibration within reasonable limits. The multi-objective and multi-parameter optimization method applied on carbody underframe suspended system proves to be valuable in improving the dynamic performance of high-speed railway vehicles.

Insights of structure-based virtual screening and MPO-based SAR analysis of berberine-benzimidazole derivatives against Parkinson disease

Parkinson's disease (PD) is a progressive neurological condition that causes tremors, rigidity and postural instability. In addition, it can lead to complications such as constipation, orthostatic hypotension, and psychiatric disorders like depression and anxiety. Berberine is a natural alkaloid used in Chinese medicine, extracted from various plants such as Berberis vulgaris and Tinospora cordifolia. The compounds have been reported to possess therapeutic activities, including anti-Alzheimer's, anti-diabetic, anti-inflammatory, antiviral, antibacterial and, in the context of this study, anti-Parkinson's action. This study conducts a structure-based virtual screening of aryl-substituted berberine-benzimidazole derivatives (D1–7). Molecular docking and dynamics simulations are used to predict pharmacodynamics against monoamine oxidase B (MAOB), while multiparametric optimization (MPO) is used to predict pharmacokinetics to the Central Nervous System (CNS). The aim is to propose new alkaloids derived from berberine that can modulate the activity of MAOB receptors in treating PD. The simulations revealed that the D7 compound, which contains a dichlorophenyl group, exhibited a high affinity with MAOB, with an affinity energy of −10 kcal/mol. In contrast, the fluoro- and nitro- substituted compounds showed lower affinity. Structure-activity/property relationship (SAR/SPR) analysis suggest that the chloro‑substituted derivatives are more lipophilic and form essentially hydrophobic interactions with the MAOB. This is corroborated by the dynamics simulations, which show that the MAOB-D7 complex is highly stable and allows for a synergistic effect associated with other anti-Parkinson drugs, further enhancing the inhibition of MAOB. Furthermore, pharmacokinetic predictions indicate that optimal levels of lipophilicity and polarity enhance high passive permeability (Papp = 1.7 × 10−5 cm/s) and metabolic stability of the D7 derivative, leading to increased distribution in the CNS.

Multi-Parameter Optimization of Siloxene-PANI Composites for High-Performance and Flexible Energy Storage Application

The development of high-performance energy storage devices is crucial for various applications, such as electric vehicles, portable electronics, and renewable energy systems. Supercapacitors have emerged as a promising technology due to their high power density and long cycle life. However, their low energy density has limited their widespread application. To address this limitation, researchers have been exploring various strategies, including the use of new electrode materials and optimized electrode design. In this study, a high-energy-density energy storage device was developed using a composite material composed of siloxene and polyaniline (PANI) for flexible supercapacitor designs. Here, optimized material's surface area, pore distribution, and electronic transition, achieving a specific capacitance of 483 F/g at 1A/g in a three-electrode system using a 1 M H2SO4 electrolyte. The optimized material also exhibited a retention rate of 92.6% at 5A/g. The optimized siloxene-PANI composite material was then used to fabricate a flexible asymmetrical supercapacitor (SiP4//AC). The supercapacitor exhibited a high energy density of 19.7 Wh/kg at a power density of 248 W/kg, with a cyclic stability of 90.26% and a coulombic efficiency of 97%. The flexible design of the supercapacitor using the siloxene-PANI composite material allowed for its use in wearable electronics and other applications requiring high-performance, flexible energy storage devices. The study provides valuable insights into the development of energy storage devices with high energy density and high power density, which will pave the way for the practical application of supercapacitors in various fields.

A computer code for optimizing the neutronics model parameters based on results of reactor physics experiments

The paper describes in brief the functional capabilities of a computer code for optimizing the neutronics model parameters (neutron data, technological parameters, and their covariance matrices) based on results of reactor physics experiments using conditional nonlinear multi-parameter optimization algorithms. The code’s application scope includes adjustment of neutron constants, technological parameters and their covariance matrices based on integral measurement results, formulation of requiremen117198ts with respect to the neutron data uncertainties for achieving the target accuracies in calculation of the reactor functionals, and estimation of the reactor performance prediction accuracy, as well as the informativity and similarity metrics of reactor physics experiments with respect to each other and in relation to the target reactor system. The paper also considers some examples of using the code to refine the neutronics models of nuclear reactor and fuel cycle systems based on results of reactor physics experiments.

Study on heat transfer coupling mechanism of direct thermoelectric conversion with regenerative cooling for supersonic combustor applications

Direct thermoelectric conversion is a promising technology that converts aerodynamic and combustion heat into electric energy for thermal management of supersonic combustors. However, the heat transfer process of direct thermoelectric conversion coupled with regenerative cooling of supersonic combustors is rarely studied and the coupling mechanism is not clear. In this paper, a novel “SANDWICH” thermoelectric/cooling integrated model (TCIM) proposed by the present work based on Skutterudite (SKD) or Half-Heusler (HH) thermoelectric conversion devices is analytically studied. The energy conversion and heat transfer mechanism of the direct thermoelectric conversion coupled with regenerative cooling are revealed. Using the analytical model, the effects of structural parameters of thermoelectric conversion device and the heat transfer coefficient of regenerative cooling on the energy conversion efficiency and output power are investigated for two typical thermal conditions corresponding to the isolation part and the combustion part of a Mach 2.5 supersonic combustor. The analytical results showed that larger size of the thermoelectric conversion device can effectively improve the conversion efficiency and output power per unit area. Increasing the heat transfer coefficient of regenerative cooling can lower the structural temperature and increase the output power per unit area by more than 12%. Furthermore, with a multi-parameter optimization method based on Genetic Algorithm, optimization for the output power per unit area is conducted with variations of the structural parameters of TCIM under constraints of the tolerance temperature and the types of thermoelectric conversion devices. A more than 10% increase in the output power per unit area for both SKD and HH TCIMs are achieved via the optimization.

Weak fault feature extraction of rolling bearing based on multi-system coupled cascaded stochastic resonance system

The accurate extraction of weak signal features under strong noise background plays a crucial role in the fault detection of rolling bearings. In order to promote the ability of stochastic resonance (SR) system to detect weak signals and improve the output performance of the system, a multi-system coupled cascaded SR (MCCSR) system is investigated and applied to the fault detection of rolling bearings. Firstly, a MCCSR system is constructed by exploiting the positive synergistic effect between multiple systems, which consists of a triangular-topology coupled system composed of three SR subsystems and a cascaded SR system with topology output as input. This system makes full use of the advantages of coupled system and cascaded system in weak signal detection. In terms of parameter optimization, a stepwise multi-parameter optimization strategy is proposed, which adopts different optimization methods for different parameters, and avoids the inconsistency between error and step factor by improving the least mean square algorithm. Finally, through the comparative analysis of numerical simulation and experimental signals, it is verified that the proposed method can effectively enhance the weak signal features and improve the system output signal-to-noise ratio, which can better serve for rolling bearing fault detection.

Model of Multi-Parameter Optimization of the Characteristics of a Cable Car in a Solid Waste Transportation System

Introduction. Modern scientific and applied literature examines the problems of cable cars functioning quite thoroughly. First of all, it concerns ensuring the reliability and safety of traffic, both during operation and during project development. In addition, the paper considers the relationship of cable cars with the environment and the level of environmental load from this type of transport. A good solution could be the use of mathematical models that can take into account a set of parameters and criteria that characterize the cable car as a system. The same approach would be useful for optimizingtechnical characteristics of the object. However, there is no description of such a solution in the literature. This gap is partially filled by the presented work. The study aims to create a model of multivariable optimization of cable car technical characteristics for the transportation of municipal solid waste (MSW). Material and Methods. To clarify the theoretical basis, the literature describing the problems of cable cars and their solutions in general has been studied. Mathematical calculations were justified by a volume of equations that proved their adequacy in determining the useful transport work, load, adjustment of time and speed of cargo movement and other significant parameters of the system under study. When forming the model, we proceeded from the principles of L. S. Pontryagin (needle variation) and Hamilton — Ostrogradsky (kinematics of a certain road segment). Text data about the features of the system elements and their interaction were summarized in tables. The main calculations results were visualized in the form of graphs. Results. The solution to the problem of optimal control of the cable car on which solid waste was moved was presented. The motion control vector was shown as a vector of optimized technical parameters of the system: speed of movement, rope tension, number and weight of containers. The well-known solution to the optimization problem was reproduced in a general form, which involved determination of a control vector function and its corresponding trajectory with the achievement of a minimum of the target functional. The weak point of the system of differential equations for the realization of the goals of this scientific work was noted. In this regard, it was proposed to consider the investigated section of the cable car as a dynamic system with distributed parameters. The formulation of the multi-criteria optimization problem was described in detail. The advantages of reducing the number of criteria taken into account were listed and the use of the reduction method, which was based on the hierarchical structuring of the system of partial optimality criteria, was justified. Four main elements of the municipal solid waste (MSW) transportation system were considered in interrelation. This was a cable car, a transport and logistics point, a transport and logistics terminal and an environment that generated solid waste. Within the framework of this work, we considered an urbanized environment. The sub-elements of the named elements were listed and 12 directions of their interactions were shown. In detail, within the framework of a three-level hierarchy, four main complex indicators of the complexity of the system under study were described: environment, road, point and terminal. The solution of a multi-criteria optimization problem was shown, calculations were performed for the optimized parameters — the characteristic of the complexity of the road and the characteristic of the terrain. The results of calculations were presented in the form of graphs. Thus, the dependences of the optimized parameters on the weight of the loaded container, the length and speed of the cable car were illustrated. Conclusions. The main result of the study is an idea of the possibility of a mathematical solution of a multivariable and multi-criteria problem of optimizing two characteristics of a cable car (complexity and terrain feature). The proposed approach allows you to change the hierarchy in the complex of indicators. The results of this scientific work can be used, if necessary, to integrate the road project with neural network models, to work with fuzzy linguistic indicators, to solve applied problems.

Vibration mitigation and energy harvesting of vibro–impact dielectric elastomer oscillators

Dielectric elastomers (DEs), as a type of intelligent materials, have the characteristics of light weight, high energy density, high conversion efficiency, and damping effect, and thus can achieve the potential dual–use value of concurrent vibration mitigation (VM) and energy harvesting (EH) by combining with mechanical structures. This paper investigates the vibro–impact dielectric elastomer oscillator (VI DEO) and the proposed rolling VI DEO (RVI DEO) to achieve or enhance the potential dual–use value of DE oscillators. First, the schematics of the VI DEO and the RVI DEO are elaborated in detail. Then, the two dynamics analysis models of the linear oscillator (LO)–VI DEO and LO–RVI DEO systems are developed. On this basis, the VM and EH performances of the two DE oscillators under transient and harmonic excitations are numerically studied. It is demonstrated that the two DE oscillators have the most effective VM performance when the LO–VI DEO and LO–RVI DEO systems behave most efficiently in the 1:1 resonance vibro–impact regime with targeted energy transfer (TET). Hence, to achieve this response regime, the influences of the parameters such as the ball's mass, impact distance, pre–stretched ratio and friction coefficient of the two DE oscillators on their VM and EH performances are investigated one by one. The research results show that the most effective VM can only be achieved by adjusting the ball's mass, and the largest output power is generated in the resonance region. Hence, we further perform multi–parameter optimization to find the two DE oscillators with the best performance. Based on the multi–parameter optimization results, the performances of the two optimal oscillators are evaluated under mid–energy level harmonic and variable–frequency excitations with different amplitudes, and it is proved that both optimal DE oscillators not only have good performances, but also the RVI DEO has a better robustness.

Parameter optimization of multi-suspended equipment to suppress carbody vibration of high-speed railway vehicles: a comparative study

ABSTRACT Parameter optimization of equipment suspended under the carbody underframe is one of the important measures to suppress carbody vibration of high-speed trains. Previous work focused on using one equipment as a dynamic vibration absorber to control carbody vibration, overlooking the coupling effects of multiple equipments and their vibration tolerance. To address this, a comprehensive study involving multi-objective and multi-parameter optimization to enhance both carbody and equipment vibration performance is proposed. First, a theoretical model with one equipment is established to derive optimal parameters, and a simulation model with multi-suspended equipment is built to conduct optimize calculations with an improved niche genetic algorithm (INGA). Afterwards, a comparative study on carbody and equipment vibration performance is analysed based on the optimal parameters, proving that the optimal method with INGA is more effective in improving vehicle performance. Finally, the method is applied to a newly designed vehicle, and the performance is validated on a rig, providing technical support for the design of high-speed vehicles.

Численная оптимизация в задачах проектирования многослойных магнитных маскировочных оболочек

A multiparameter optimization problem of magnetic cloaking is solved for a two-dimensional model of magnetostatics. This problem arises when designing cylindrical multilayer cloaking devices filled with anisotropic or isotropic magnetic media with tensor, in the general case, magnetic permeabilities. Applying the optimization method for solving inverse problems the considered problem of magnetic cloaking is reduced to a finite-dimensional extremum problem. The results of applying the developed numerical algorithm based on the particle swarm optimization method to solve the extremum problem confirm its high efficiency and make it possible to establish the important property of the obtained optimal solutions.

Whole cell hydride Meisenheimer complex biotransformation guided optimization of antimycobacterial benzothiazinones

Nitrobenzothiazinones (BTZs) are potent active substances against Mycobacterium tuberculosis with currently two investigational drugs in clinical development for the treatment of tuberculosis. BTZs are the first examples for which a metabolic pathway towards transient hydride Meisenheimer complexes (HMC) has been shown in mammals, including humans. In this study, lead optimization efforts on BTZs are guided by the systematic evaluation of the HMC formation propensity combined with multiparameter assessment. For this purpose, a novel cell-based assay was specifically developed and fully implemented, and a library of 5- and 7-substituted BTZs was prepared to study substituent effects on the HMC formation. The multiparameter optimization revealed 5-methylated BTZs as the most preferred scaffolds, demonstrating a reduced HMC formation propensity combined with potent activity and good microsomal stability in vitro. In vivo experiments showed good systemic exposure upon oral administration and efficacy in a murine M. tuberculosis infection model. This study reports a qualified in vitro HMC assay, which not only enabled the selection of next-generation BTZs with improved pharmacokinetic properties but also allowed forecasting their in vivo metabolism.