Design Procedure Research Articles

Distributed Adaptive Formation Tracking for a Class of Uncertain Nonlinear Multiagent Systems: Guaranteed Connectivity Under Moving Obstacles.

This article explores a guaranteed network connectivity problem during moving obstacle avoidance within a distributed formation tracking framework for uncertain nonlinear multiagent systems with range constraints. We investigate this problem based on a new adaptive distributed design using nonlinear errors and auxiliary signals. Within the detection range, each agent regards other agents and static or dynamic objects as obstacles. The nonlinear error variables for formation tracking and collision avoidance are presented, and the auxiliary signals in formation tracking errors are introduced to maintain network connectivity under the avoidance mechanism. The adaptive formation controllers using command-filtered backstepping are constructed to ensure closed-loop stability with collision avoidance and preserved connectivity. Compared with the previous formation results, the resulting features are as follows: 1) the nonlinear error function for the avoidance mechanism is considered an error variable, and an adaptive tuning mechanism for estimating the dynamic obstacle velocity is derived in a Lyapunov-based control design procedure; 2) network connectivity during dynamic obstacle avoidance is preserved by constructing the auxiliary signals; and 3) owing to neural networks-based compensating variables, the bounding conditions of time derivatives of virtual controllers are not required in the stability analysis.

Design of Two-Wheeler Hybrid Electric Vehicle using MATLAB-Simulink

Abstract: This report presents the design and structural analysis of a go-kart using PTC Creo for CAD modelling and ANSYS for finite element analysis (FEA). The aim is to develop a low-cost, comfortable, and durable go-kart with an optimized frame design. The study involves the application of design principles and advanced simulation tools to ensure the go-kart meets safety and performance standards. The best frame design was identified through iterative testing and analysis, focusing on weight distribution, material selection, and structural integrity. The objective of this work is to demonstrate the design procedure and good strength for a Roll cage. This project emphasizes on the practical and engineering applications of the subjects Vehicle Dynamics and Automotive Technology.

Optimizing asphalt mix design through predicting volumetric properties using interpretable machine learning

Traditional asphalt mix design methods primarily rely on experience, consuming immense time and resources. Currently, advanced machine learning (ML) method can accelerate the asphalt mix design procedure. However, historical data on asphalt mix design exhibit high variability, and the outputs of ML models are often challenging to interpret. To address these issues, this study selectively utilized outlier detection algorithms for data preprocessing and employed interpretable ML to predict and explain the volumetric properties of the mixtures, achieving an automated and rapid mix design method. A database (1525 sets of data) of volumetric properties was established based on experimental data of the engineering site. Z-score, KDE (kernel density estimation) and LOF (local outlier factor) methods were employed to detect outliers of the database. Three ML models were trained to predict the volumetric properties of mixture (air void and voids in mineral aggregate), based on material proportion, gradation morphological and material performance features. The SHAP method was used to interpret the extreme gradient boosting (XGB) model, quantifying feature importance, and aiding in decision-making. Finally, an asphalt mix design framework was proposed. The results indicate that the combination of KDE and LOF methods for outlier detection enabled the machine learning model to achieve optimal performance. The XGB model had the best prediction effect on volumetric properties. According to the SHAP method results, the influence of the critical features on the results was explained by the physical laws. The method proposed effectively reducing the design time and costs. The feasibility of the proposed design method was proved by the case study.

Fatigue-resistant design of carbon/epoxy composites based on a failure tensor polynomial model by particle swarm optimization-sequential quadratic programming algorithm

This article introduces a design procedure to find the optimum fiber orientations of carbon/epoxy composite laminates for fatigue life advancement. The approach incorporates a fatigue failure tensor polynomial model and employs a hybrid algorithm, combining particle swarm optimization and sequential quadratic programming. Firstly, material properties of quasi-static and fatigue of the carbon/epoxy composites, fabricated by the vacuum-assisted resin transfer molding method, were determined to be used in the model. Various design problems involving two optimization scenarios were then solved using the hybrid algorithm. The algorithm’s performance was also evaluated by specific test problems, confirming its speed and robustness. The optimally fiber-oriented carbon/epoxy composite laminates having maximum fatigue lives were obtained for many critical in-plane cyclic loading cases. To validate the proposed design procedure, two optimum designs were experimentally verified under uniaxial loading conditions. The results indicated a good correlation between the estimated fatigue life of the optimally designed laminates and experimental data. This methodology offers a promising approach for the design of carbon/epoxy composite laminates with superior fatigue strength, particularly significant in specific industrial applications.

Seismic Fragility and Reliability of Base-Isolated Structures with Regard to Superstructure Ductility and Isolator Displacement Considering Degrading Behavior

ABSTRACT The present study investigates the effects of the degradation of mechanical properties (pinching, stiffness degradation, and strength degradation) in load-deformation relationship of the superstructures equipped with friction pendulum systems on the seismic fragility and reliability results. An equivalent two-degree-of-freedom model is employed, in which the Bouc-Wen hysteretic model characterizes the inelastic behavior of both the superstructure and the isolator. To examine a wide variety of system combinations with different structural properties and degradation severity, a comprehensive parametric study is performed. Incremental dynamic analyses are carried out to develop fragility functions. Subsequently, the seismic reliability of both the superstructure and the isolation level is assessed. Results indicate that the negative effects of degrading behavior are more prominent in stiff superstructures as it significantly decreases structural capacity and reliability indices. It is demonstrated that the system is primarily influenced by pinching behavior rather than degradation in strength and stiffness, especially at low intensity levels that correspond to lower limit-states. In the majority of investigated systems, the seismic demand in the isolator decreases when superstructures undergo degrading behavior. Overall, such effects should be considered in the reliability-based design procedure to attain design consistency in terms of reliability. The results of this paper that account for the degrading effects enable reliable estimations of key parameters essential for the design of the superstructure and the isolator.

An optimal experimental design framework for fast kinetic model identification based on artificial neural networks

The development of mathematical models to describe reaction kinetics is crucial in process design, control, and optimisation. However, distinguishing between different candidate kinetic models presents a non-trivial challenge. Recent works on this topic introduced an approach that employs artificial neural networks (ANNs) to identify kinetic models. In this paper, the ANNs-based model identification approach is expanded by introducing an optimal experimental design procedure. The performance of the method is evaluated through a case study related to the identification of kinetics in a batch reaction system, where different combinations of experimental design variables and noise level on the measurements are compared to assess their impact on kinetic model identification. The proposed experimental design methodology effectively reduces the number of required experiments while enhancing the artificial neural network's ability to accurately identify the appropriate set of equations defining the kinetic model structure.

Compact Ultra-Wideband Wilkinson Power Divider in Parallel Stripline with Modified Isolation Branches.

An efficient design method for a compact and ultra-wideband multi-stage Wilkinson power divider in a parallel stripline (PSL) is proposed. To enhance the frequency bandwidth of the proposed power divider while reducing its size, the isolation branch is modified; that is, two capacitors are connected to both sides of a resistor at each isolation branch. For an efficient design process, the PSL power divider is equivalently represented by two microstrip power dividers, and the design equations are derived. Based on the design equations, an in-house algorithm is utilized to optimally determine the design parameters, including the line impedance, resistance, and capacitance of each stage. For example, a three-stage PSL power divider is designed with three λ/4 transmission lines at a base frequency of 5 GHz. To verify the accuracy of the design procedure, 3D EM simulations and measurements are performed, and the results show good agreement. Compared with the conventional three-stage Wilkinson power divider, the proposed PSL power divider achieves a wider frequency bandwidth of 1.16 to 6.51 GHz (139.5%) and a 23% shorter transmission line length of 207°, while exhibiting an insertion loss of 0.7 to 1.4 dB.

Pedagogical Skills Needs of Motor Vehicle Mechanics Work Teachers for Effective Content Delivery in Government Science and Technical Colleges in Adamawa and Taraba States

The main purpose of the study was to explore the pedagogical skills needs of motor vehicle mechanics work teachers for effective content delivery in government science and technical colleges in Adamawa and Taraba States. The study was guided by two research questions and two null hypotheses. The study was conducted in Adamawa and Taraba States using descriptive survey research design. The population of the study was 123 respondents comprising 81 MVMW teachers and 42 instructors from all the 21 BEST Centres and Government Science and Technical colleges in Adamawa and Taraba States, Nigeria. There was no sampling as the entire population was used because it was manageable. A structured questionnaire tagged: Pedagogical Skills Needs of Motor Vehicle Mechanics Works Teachers Questionnaire (PSNMVMWTQ) consisting of 30 items was validated by three experts. The Instrument was trial tested in Gombe State and the Cronbach Alpha reliability method was used to test the reliability of the instrument and a 0.84 reliability coefficient was obtained. Data collected for the study was analyzed using Statistical Package for Social Sciences (SPSS) version 27.0. Mean statistics was used to answer the two research questions while a t-test was used to test the null hypotheses at a 0.05 level of significance. The findings of the study revealed among others that pedagogical skills needed include stimulating critical thinking, designing effective evaluation procedures, and implementing appropriate instruction. Similarly, affective skills were deemed needed including effective communication, active listening, and conflict resolution. Importantly, there were no significant differences between instructors and MVMW teachers regarding the perceived importance of these skills. It is recommended that Given the identified pedagogical skills needs of motor vehicle mechanics work (MVMW) teachers, Ministries of Education should design and implement targeted training programs focusing on instructional goal identification, task analysis, instructional design, questioning techniques, and evaluation procedures.

Seismic Design Procedure for Low-Rise Cold-Formed Steel–Special Bolted Moment Frames

In 2007, the American Iron and Steel Institute (AISI) established a standard for cold-formed steel–special bolted moment frames (CFS-SBMFs). This structural system is designed to resist seismic forces. The CFS-SBMF system employs double-channel beams and square hollow structural section (HSS) columns that are bolted together to create a sturdy and robust structural frame. However, the CFS-SBMF system is only suitable for constructing one-storey buildings, and ASCE 7 prohibits its use in buildings with a height of over one storey. This study was conducted to expand the use of CFS-SBMFs to the construction of multi-storey low-rise buildings. Firstly, a new moment connection detail is proposed, and a design procedure is proposed to ensure that bolted connections, instead of beams or columns, have the ductility to withstand seismic forces. Secondly, the proposed design procedure for bolted connections was verified through full-scale cyclic testing. Finally, a comprehensive evaluation was undertaken to evaluate the proposed structural system’s performance under seismic excitation. The evaluation included nonlinear dynamic analysis and incremental dynamic analysis (IDA) according to FEMA P695, which provided a detailed understanding of the seismic design factors (SDFs) in multi-storey low-rise CFS-SBMF buildings.

Arab minority social workers trained in a foreign language: linguistic challenges and coping mechanisms

ABSTRACT The research highlights challenges involved in ensuring professional authentication faced by social workers working in cultural minorities. The findings contribute to the knowledge corpus that discusses authentication. They describe and explain possible consequences of linguistic difficulties arising in Arab minority social workers’ work in Israel. These workers acquired their profession in a foreign language (Hebrew) but work with their native minority population whose mother tongue is Arabic. A phenomenological study elicited data from semi-structured in-depth interviews with 19 Arab welfare bureau social workers. The workers encounter three language difficulties when working with their service users: They are accused of identifying with the hegemon because they adopt its language; they are viewed as foreign because they have difficulty conveying professional messages accurately; and are seen as alien because the Hebrew terminology they use is anchored in a secularist-individualist culture. The research also identified three coping mechanisms: Ignoring the language barriers; being aware but passive, and adopting three active strategies: self-improvement, getting help from the immediate professional milieu and harnessing external resources. The findings reinforce the requirement of ethical codes for language competence in three fields: lifelong learning, policy design (laws, procedures and guidelines) and implementation (interventions, mentoring and supervision).

Evaluation of Different Filtering Methods Devoted to Magnetometer Data Denoising

In this article, we describe a performance comparison conducted between several digital filters intended to mitigate the intrinsic noise observed in magnetometers. The considered filters were used to smooth the control signals derived from the magnetometers, which were present in an autonomous forestry machine. Three moving average FIR filters, based on rectangular Bartlett and Hanning windows, and an exponential moving average IIR filter were selected and analyzed. The trade-off between the noise reduction factor and the latency of the proposed filters was also investigated, taking into account the crucial importance of latency on real-time applications and control algorithms. Thus, a maximum latency value was used in the filter design procedure instead of the usual filter order. The experimental results and simulations show that the linear decay moving average (LDMA) and the raised cosine moving average (RCMA) filters outperformed the simple moving average (SMA) and the exponential moving average (EMA) in terms of noise reduction, for a fixed latency value, allowing a more accurate heading angle calculation and position control mechanism for autonomous and unmanned ground vehicles (UGVs).

Human digital twins to inform ship design

A key building block of digital twin solutions is a virtual counterpart for an asset that can be coupled to the asset throughout its lifecycle – predicting an asset’s potential performance at design and providing insight into operation during service. This paper presents the development of human digital twins that integrate human factors into conventional ship design procedures, particularly focussing on seakeeping performance assessments. A novel method for incorporating human-centric performance criteria in seakeeping analyses is proposed and initial validation thereof is detailed. Human digital twins are seen to provide a platform for informing the ship design process using data captured during vessel operation.

Capillary-assisted flat-field formation: a platform for advancing nanoparticle tracking analysis in an integrated on-chip optofluidic environment

Abstract Here, we present the concept of flat-field capillary-assisted nanoparticle tracking analysis for the characterization of fast diffusing nano-objects. By combining diffusion confinement and spatially invariant illumination, i.e., flat-fields, within a fiber-interfaced on-chip environment, ultra-long trajectories of fast diffusing objects within large microchannels have been measured via diffraction-limited imaging. Our study discusses the design procedure, explains potential limitations, and experimentally confirms flat-field formation by tracking gold nanospheres. The presented concept enables generating flat-fields in a novel on-chip optofluidic platform for the characterization of individual nano-objects for fundamental light/matter investigations or applications in bioanalytics and nanoscale material science.

A piecewise-linear backbone model for unbonded post-tensioned concrete masonry shear walls

Unbonded post-tensioned concrete masonry (UPCM) shear walls present an effective seismic force resisting system due to their ability to mitigate expected damage risks through their self-centering capabilities. A few design procedures were proposed to predict the in-plane flexural response of UPCM walls, albeit following only basic mechanics and/or extensive iterative methods. Such procedures, however, may not be capable of capturing the complex nonlinear relationships between different parameters that affect UPCM walls’ behavior or are rather tedious to be adopted for design practice. In addition, the restricted datasets used to validate these procedures may cast doubt on their accuracy and validity for new, unseen data, further hindering their adoption by practitioners and design standards. To address these issues, an experimentally-validated nonlinear numerical model was adopted in this study and subsequently employed to simulate 95 UPCM walls with a range of different design parameters to compensate for the lack of relevant diverse experimental data in the current literature. Guided by mechanics, and employing this database, an evolutionary algorithm—multigene genetic programming (MGGP), was adopted to uncover the relationships controlling the response of UPCM walls, and subsequently develop simplified closed-form wall behavior prediction expressions. Specifically, through integrating MGGP and basic mechanics, a piecewise-linear backbone model was developed to predict the load-displacement backbone for UPCM walls up to 20% strength degradation. Compared to existing predictive procedures, the prediction accuracy of the developed model and its closed-form nature are expected to facilitate better understanding of such wall behaviors and subsequently open the gate to further incorporate other experimental and numerical results to ultimately deploy UPCM in mainstream building designs in the near future.

АНАЛІЗ ТА УЗАГАЛЬНЕННЯ ІСНУЮЧОГО ДОСВІДУ ЩОДО ЗАСТОСУВАННЯ ТА ВПЛИВУ АРМУЮЧИХ МІКРОВОЛОКОН НА ВЛАСТИВОСТІ АСФАЛЬТОБЕТОНІВ

Introduction. Excessive axle loads and environmental influences cause permanent deformation, cracking, residual deformations in the form of rutting, fatigue and shortening the service life of highways. The use of reinforcing microfibers (fibers) in the asphalt concrete mixture is gaining popularity, as it can improve the mechanical properties of the asphalt concrete layers of the road structure and increase its strength and durability. Problems. Based on the literature analysis, it was established that the use of fiber (fibers) can improve the properties of asphalt concrete. Goal. It consists in the analysis and generalization of the existing experience regarding the use and influence of fiber on the properties of asphalt concrete. Results. An analysis of the experience of using fiber and the influence of fiber on the properties of asphalt concrete, in particular natural fiber, synthetic fiber, glass fiber, metal fiber, and mineral fiber, was conducted. Conclusions. The review highlights the potential benefits of using fiber in an asphalt mixture, including improved stiffness and cracking resistance, reduced rutting, and increased fatigue resistance. However, the effectiveness of fiber in improving the mechanical properties of asphalt concrete is influenced by various factors such as fiber type, content, and distribution. Further research and studies are needed to optimize fiber selection, refine mixture design procedures, improve fiber introduction technologies into the asphalt concrete mixture, and conduct environmental and economic impact assessments.

Self-tuning Database Systems: A Systematic Literature Review of Automatic Database Schema Design and Tuning

Self-tuning is a feature of autonomic databases that includes the problem of automatic schema design. It aims at providing an optimized schema that increases the overall database performance. While in relational databases automatic schema design focuses on the automated design of the physical schema, in NoSQL databases all levels of representation are considered: conceptual, logical, and physical. This is mainly because the latter are mostly schema-less and lack a standard schema design procedure as is the case for SQL databases. In this work, we carry out a systematic literature survey on automatic schema design in both SQL and NoSQL databases. We identify the levels of representation and the methods that are used for the schema design problem, and we present a novel taxonomy to classify and compare different schema design solutions. Our comprehensive analysis demonstrates that, despite substantial progress that has been made, schema design is still a developing field and considerable challenges need to be addressed, notably for NoSQL databases. We highlight the most important findings from the results of our analysis and identify areas for future research work.

Experimental Investigation on Shear Strength and Microstructure of Chemically Treated Sisal Fiber-Reinforced Concrete

The incorporation of sisal fiber into the concrete matrix reduces waste disposal, which has negative environmental impacts. The aim of this study was to perform an experimental investigation on shear strength and microstructure of chemically treated sisal fiber-reinforced concrete (SFRC). In order to accomplish the aim of the study, physical, shear, and mechanical properties of concrete reinforced with chemically treated sisal fiber have been performed. 0.50%, 1.00%, 1.25%, 1.50%, 1.75%, and 2.00% of sodium hydroxide (NaOH) and sulfuric acid (H2SO4) treated sisal fiber were used as an addition to the dry weight average with the help of the American Concrete Institute (ACI) mix design procedure. After the 7th and 28th days of curing, shear strength according to the ASTM D5379M standard and the mechanical properties of concrete have been conducted. For microstructural properties, scanning electron microscopy (SEM) and X-ray diffraction (XRD) were conducted after the concrete was cured for 28 days. Forty-six percent and 20% compressive strength enhancement at the 7th and 28th days of curing was compared to the control mix. Twenty-seven percent enhancement was recorded in the split tensile strength of 1.5% SFRC as compared to the control mix at 28 curing days. A shear strength of 1.5% SFRC was improved by 95% at the 7th curing days and 28% at the 28th curing days as compared to the control mix. As compared to conventional concrete, SFRC shows a denser microstructure. In addition to this, portlandite, quartz, calcium aluminum silicate, and C─S─H crystal are the available phases in the concrete matrix.

Application of automatic few-group structure optimization based on perturbation theory to VHTR cores

A new automatic group structure optimization method based on the perturbation theory was proposed for the few-group structure in two-step nuclear design procedure for VHTR. It applies the sensitivity coefficient of the perturbation theory which includes not only the effect of the cross section on the multiplication factor but also the adjoint weighted reaction rate. The sensitivity coefficient of the fine group for the multiplication factor was calculated and the group boundary for a few-group can be determined so that the summation of the fine group sensitivity for a few-group should be evenly distributed over every few-group. This method was successfully implemented in the ABGO code. VHTR-350 and MiHTR 2D core were used to investigate the performance and applicability of the proposed method. The code generated the new group structures for two cores and the error of the multiplication and reaction rate by the new group structure was compared with the result by the fine group structure. The comparisons indicate that the new group structure by the proposed method can provide the multiplication factor and reaction rates comparable to the existing group structure and more accurate results than the group structure obtained using the Contributon theory.

An optimization-free Fisher information driven approach for online design of experiments

Developing mathematical models used to elucidate reaction kinetics plays a crucial role in the design, control, and optimization of chemical processes. One of the most challenging tasks in kinetic model identification is the precise estimation of unknown kinetic model parameters. This challenge can be effectively addressed through the application of Model-Based Design of Experiments (MBDoE) techniques, which enable the design of experiments facilitating precise model parameter estimation with minimal runs and analytical resources. Nevertheless, MBDoE techniques rely on an optimization procedure that is susceptible to parametric uncertainty, making the design procedure computationally intensive and prone to issues of local optimality. MBDoE techniques are also employed in online procedures to expedite the identification of kinetic models in autonomous platforms. As a result, ensuring rapid convergence becomes imperative to mitigate numerical issues during operational processes. In this paper a Fisher Information Matrix Driven (FIMD) approach is introduced to tackle these challenges. The methodology integrates a sampling-based experimental design approach with experiment ranking based on FIM to select the most informative experiment at each iteration. The effectiveness of the proposed design methodology is examined and discussed via two different case studies of increasing complexity: a fed-batch reactor in which the fermentation of baker’s yeast is carried out and a nucleophilic aromatic substitution in a flow reactor system.

Performance-Based Seismic Design for Bridge Bents Retrofitted with BRBs Using the Ductility Demand Spectra of SDOF Oscillators with Bilinear Fuses

ABSTRACT Reinforced concrete bridge bents with double columns in bridge substructures are commonly used, but it has suffered severe damage during strong earthquakes. The seismic retrofit with structural fuses is used to effectively mitigate seismic damage of bridge bents. To obtain the displacement ductility demand for dual systems including the primary structure (PS) and structural fuses (SF), the corresponding ductility demand factor spectra were developed. The interaction between the PS and SF is described by defining two parameters of dual systems: the yield displacement ratio (α) and the initial stiffness ratio (β), and the influence of α, β, and strength reduction factor on the ductility demand factor spectra are also analyzed. For seismic retrofitting in bridge bents, buckling-restrained braces (BRBs) are used as energy dissipation fuses, and the steel core lengath of BRBs with three configurations forms, including diagonal, inverted-V, and toggle systems, are also explored. Then, based on the structural fuses concept and ductility demand factor spectra of dual systems, a performance-based seismic design procedure is proposed for bridge bents retrofitted with BRBs to ensure that the bridge bents maintain the target ductility under design-level earthquakes. Finally, the procedure was utilized to design the bridge bents with BRBs, and the procedure’s feasibility was verified by nonlinear time-history analysis.