Dimensions Of Components Research Articles

A Review on Design and Fabrication of Affordable Lift for Built Home

Lift may be a very simple mechanical equipment used to raise elements or objects or load from ground level to a specific height to perform a particular work with maximum load capacity and minimum efforts of a worker. The objective of this work is to develop a mechanism for climbing up and down over stairs for aged and physically challenged people and easy mobility of the whole elevator. To achieve this, we require high strength materials, wheels, etc. All the researchers attempt to optimize these parameters according to the concerned requirements. This review paper is focused on the analysis of some research papers containing the entire study of components, selection of materials, and analysis of dimension of components. After the analysis of research papers, long term scope of the research was also suggested. This review paper focuses on the analysis of several research papers that explore the entire study of components, selection of materials, and analysis of dimension of components. It provides insights into current advancements in the field and evaluates different approaches to developing a stair-climbing mechanism for aged and physically challenged individuals.

A fully automated tool for constructing multiphysics model and performing simulations of kW-scale solid oxide cell stacks

Multiphysics simulations of solid oxide cell (SOC) require extensive experience and can be labor intensive. This paper reports the first successful implementation of automated multiphysics simulation process for industrial-scale planar SOC stacks. The automation is realized through Python based Ansys SpaceClaim scripting for building geometric model, Python based Ansys Workbench Meshing scripting for setting numerical grids, and Scheme based Ansys Fluent TUI commands for performing multiphysics simulations. The model building process allows for customized dimensions of all stack components and the corresponding edge grid counts. The automation of simulations streamlines all the computational steps in multiphysics modeling. The multiphysics model is shown to agree well with the experimental data. The automated tool is illustrated in a parametric analysis of SOC operations, illuminating the influences of size, shape and thermal boundary on the stack performance. The automation makes the simulations simple and efficient, invaluable for the SOC design and operation analysis.

Experimental and numerical study on the blast performance of the corrugated double steel plate concrete composite wallboard under blast loads

The corrugated double steel plate concrete composite wallboard (CDSCW) exhibits superior axial compressive load-bearing capacity, lateral flexural stiffness, impact resistance, and seismic performance compared to the traditional reinforced concrete wallboard and plane double steel plate concrete composite wallboard (PDSCW). Therefore, it has great potential application in offshore engineering and military engineering. This study designs and fabricates two types of CDSCW specimens. Firstly, a comparative analysis is conducted to examine the damage patterns and dynamic responses of the two specimens under near-field explosion experiments. Secondly, the damage mechanisms and explosion response of CDSCW and PDSCW subjected to close-in explosions are numerically investigated by using ANSYS/LS-DYNA, and the results are then compared with experimental findings. Parameter analysis is performed to assess the influence of concrete thickness, steel plate thickness, and explosive charge on the blast resistance of CDSCWs. Furthermore, a nonlinear resistance equation and an equivalent single degree of freedom (ESDOF) theoretical model for simply supported beams is established to predict the dynamic response of CDSCWs under near-blast loads. This theoretical model considers the constitutive model of bilinear materials and the effect of plastic hinges. The reliability of the proposed theoretical model is verified by comparing the residual deflection of CDSCWs obtained from explosion tests with validated numerical simulation results. The results demonstrate that the CDSCWs, with the same concrete and component dimensions (length, width), exhibit greater flexural stiffness and superior energy dissipation capacity subjected to close-in explosion. Moreover, their blast resistance significantly surpasses that of PDSCWs. In particular, an increase in corrugation depth effectively improves the blast resistance of CDSCWs. The dynamic response equations, based on the established elastic-plastic model and primarily considering bending deformation of the components, precisely predict the dynamic response of simply supported CDSCWs under near-blast loads. consequently, these findings can provide a robust foundation for further research and the design of blast-resistant structures.

Enhanced Model Predictions through Principal Components and Average Least Squares-Centered Penalized Regression

We address the estimation of regression parameters for the ill-conditioned predictive linear model in this study. Traditional least squares methods often encounter challenges in yielding reliable results when there is multicollinearity. Therefore, we employ a better shrinkage method, average least squares-centered penalized regression (ALPR), as it offers a more efficient approach for handling multicollinearity than ridge regression. Additionally, we integrate ALPR with the principal component (PC) dimension reduction method for enhanced performance. We compared the proposed PCALPR estimation technique with existing ones for ill-conditioned problems through comprehensive simulations and real-life data analyses using the mean squared error. This integration results in superior model performance compared to other methods, highlighting the potential of combining dimensionality reduction techniques with penalized regression for enhanced model predictions.

A Novel Hybrid Binary Bat Algorithm for Global Optimization

In this article, a novel hybrid binary bat algorithm named HBBA is proposed for global optimization problems. First, to avoid simultaneous updating of bat velocity's dimensional components, i.e., elements of velocity vector, a random black hole model is modified to adapt to binary algorithm for updating in unknown spaces for each dimensional component individually. Through this way, the search ability of bats around the current group best is increased greatly. Second, a time-varying v-shaped transfer function, rather than a time-invariant one as in closely related works, is proposed to map velocity in continuous search space to a binary one. This accelerates the speed to switch individuals' positions, i.e., solutions in binary space. Third, a chaotic map is utilized to replace monotonous parameters in original binary bat algorithm, which is beneficial for avoiding premature convergence. Simulation results demonstrate the effectiveness of the proposed algorithm by three types of benchmark functions and unit commitment problem.

Clinical profiles of adolescent personality pathology: a latent structure examination of the Semi-Structured Interview for Personality Functioning DSM-5 (STiP-5.1) in a help-seeking sample

BackgroundDespite the introduction of dimensional conceptualisations of personality functioning in the latest classification systems, such as Criterion A of the Alternative Model of Personality Disorders in the DSM-5, heterogeneous clinical presentation of personality pathology remains a challenge. Relatedly, the latent structure of personality pathology as assessed by the Semi-Structured Interview for Personality Functioning DSM-5 (STiP-5.1) has not yet been comprehensively examined in adolescents. Therefore, this study aimed to examine the latent structure of the STiP-5.1, and, based on those findings, to describe any unique clinical profiles that might emerge.MethodsThe final sample comprised 502 participants aged 11–18 years consecutively recruited from a specialised personality disorder outpatient service, as well as general day clinic and inpatient wards at the University Hospital University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University Hospital Bern, Switzerland. Participants were assessed using the STiP-5.1, as well as a battery of other psychological measures by clinical psychologists or trained doctoral students. Variations of Factor Analysis, Latent Class Analysis and Factor Mixture Models (FMM) were applied to the STiP-5.1 to determine the most appropriate structure.ResultsThe best fitting model was an FMM comprising four-classes and two factors (corresponding to self- and interpersonal-functioning). The classes differed in both overall severity of personality functioning impairment, and in their scores and clinical relevance on each element of the STiP-5.1. When compared to the overall sample, classes differed in their unique clinical presentation: class 1 had low impairment, class 2 had impairments primarily in self-functioning with high depressivity, class 3 had mixed levels of impairment with emerging problems in identity and empathy, and class 4 had severe overall personality functioning impairment.ConclusionsA complex model incorporating both dimensional and categorical components most adequately describes the latent structure of the STiP-5.1 in our adolescent sample. We conclude that Criterion A provides clinically useful information beyond severity (as a dimensional continuum) alone, and that the hybrid model found for personality functioning in our sample warrants further attention. Findings can help to parse out clinical heterogeneity in personality pathology in adolescents, and help to inform early identification and intervention efforts.

Switching Behavior of the Composite Low Dimensional Structural Hybrids of Carbon After UV Exposure

Low dimensional multi structural components of carbon are of great interest currently owing to their applications in developing flexible plastic electronics. In this work, we discuss emergence of different structural hybrids of carbon from as-prepared HiPCO SWCNTs subjecting them to oxidative acid purification and covalent functionalization process. Transmission electron microscopy (TEM) investigations reveal single wall carbon nanotubes (SWCNTs) serve as a building block to obtain multi wall carbon nanotubes (MWCNTs), graphene sheets (GS), carbon nano scrolls (CNS) structures which coexist in the sample. These structures when grafted with polymer binder and spray coated on Si substrate provide highly sustainable thin film coatings that are stable even in adverse space conditions [1]. These CNT and CNS based composite coatings are promising candidates for stray light control space applications exhibiting a low reflectance of the order of 2-3% in the visible spectral range [1]. Electrical switching behaviour of these films were investigated by capturing current(time) (I(t)) response, displaying promising switching character with distinct ON-OFF cycle. These coatings offer opportunities for the development of facile, cost-effective carbon-based devices without going into the nontrivial task of separating different the structures.

Beyond the surface: Understanding obsessive symptoms and body perceptions, from shape concerns to fear of blushing

IntroductionRecent reclassifications have expanded the understanding of Obsessive-Compulsive Disorders (OCDs), now incorporated into a broader category known as Obsessive-Compulsive Disorder and Related Disorders (OCRDs). This study sought to assess obsessive-compulsive symptoms and body uneasiness among outpatients seeking treatment for Eating Disorders (ED). Additionally, we aimed to explore associations and potential mediation effects between obsessive-compulsive symptoms and body uneasiness. This investigation extended beyond concerns related solely to body shape and weight, encompassing fears associated with specific body components (such as facial features, abdominal region, and limbs) or functions (including sweating, blushing, emitting noises, and releasing odors). MethodsPsychometric assessments included the Obsessive-Compulsive Inventory-Revised (OCI-R) and the Body Uneasiness Test (BUT). Statistical analyses involved bivariate correlations, linear regression, and mediation analysis to explore the associations and potential mediation effects between obsessive-compulsive symptoms and different manifestations of body uneasiness. ResultsThe sample (N = 210) demonstrated substantial obsessive-compulsive symptoms and notable body discomfort. OCI-R scores positively correlated with various dimensions of body dissatisfaction, including shape, weight, and specific body components or functions. Linear regression revealed significant associations between OCI-R scores and overall body uneasiness (BUT-A) as well as concerns about body components or functions (BUTB). Mediation analysis indicated that BUT-A mediated the relationship between obsessive-compulsive symptoms and BUTB. ConclusionThis study offers new insights into the comprehensive landscape of OCRDs. It specifically emphasizes the association between obsessive-compulsive symptoms and body uneasiness, embracing not only concerns about body shape and weight but also extending to body components and functions.

Promoting hEalthy Diet and Active Lifestyle (PEDAL): a protocol for the development and feasibility study of a multicomponent intervention among primary school children in Singapore

BackgroundSetting healthy lifestyle habits during the formative years of childhood is critical as habits can track to adulthood and help prevent obesity and chronic disease risks in later life. While multicomponent interventions have been shown to be effective in changing the lifestyle behaviours of children, there is a limited understanding of the feasibility of such interventions in primary schools in Singapore. A multiphase mixed method study was conducted to develop and examine the feasibility of a theory-based multicomponent school-based intervention—Promoting hEatlthy Eating and Active Lifestyle (PEDAL).MethodsUnderpinned by Kincaid’s ideation model, the PEDAL intervention was developed to increase fruit and vegetable consumption and decrease sedentary behaviours among children. This study consists of three phases. Phase 1 details the development of PEDAL, which consists of four components: (A) a series of interactive health education lessons, (B) actionable home activities to support habit formation, (C) parental/guardian engagement, and (D) optimising the school environment. In Phase 2, components A and B of PEDAL were implemented in two public, co-educational primary schools among Primary 5 students (aged 10–12 years) in Singapore. Data was collected quantitatively using questionnaires and qualitatively using focus group discussions (FGDs) with students and teachers. The feasibility dimensions of components A and B, including recruitment capability, data collection, social validity, and practicality were examined, and ideation on healthy eating and physical activity was explored. In Phase 3, the full PEDAL intervention was pilot-tested in two other public, co-education primary schools with the same target population, using a concurrent mixed method quasi-experimental study design. Feasibility dimensions and potential effectiveness of the intervention will be assessed.DiscussionThis study will provide insights into the feasibility of PEDAL and inform its refinement. Findings from the pilot test will guide the planning of a larger-scale definitive trial.Trial registrationRegistered with ISRCTN registry (ISRCTN16114046) on 16 October 2022.

Key attributes of designers’ competencies for design-for-deconstruction implementation

Successfully integrating design for deconstruction (DfD) principles into the construction industry will require articulated design guides and designers’ competencies. This calls for understanding the attributes of designers’ competencies essential for effective DfD implementation. This study explored the attributes of designers’ competencies for DfD implementation in the Ghanaian construction industry. The study adopted an exploratory sequential mixed-design method with an initial qualitative data collection phase followed by a quantitative data collection phase. Responses from the qualitative phase (through interviews) were thematically analysed, while data obtained from the quantitative phase were analysed using mean scores and standard deviations, the normalised value test and the Mann–Whitney U test. The study identified ten attributes of designers’ competencies for DfD implementation. The four key competencies were identified as, in order of importance, proper expertise and motivation, designers’ knowledge of material quality and durability, strong understanding of construction and effective coordination of element and component dimensions. The results of this study shed light on a less explored aspect of competencies for DfD implementation in the construction sector, particularly in the global south. It provides fresh data and new insights into the attributes of designers’ competencies for DfD implementation.

An Investigation of Representative Customer Load Collectives in the Development of Electric Vehicle Drivetrain Durability

To ensure the precise dimensioning and effective testing of drivetrain components, it is crucial to have a thorough understanding of customer requirements, with a particular emphasis on customer stress on these components. An accurate interpretation of customer data is essential for determining representative customer requirements, such as load collectives. The automobile industry has faced challenges in analyzing large amounts of customer driving data to obtain representative load collectives as target values in durability design. However, due to technical limitations and cost constraints, collecting data from a large sample size is not feasible. The ongoing digitalization of the automotive industry, driven by an increasing number of connected vehicles, enhances data-based and customer-oriented development. This paper investigates representative customer load collectives using cloud data from over 40,000 customer vehicles to lay the groundwork for realizing robust requirement engineering. A systematic method for analyzing big data on the cloud was introduced. The derived component-specific damage distribution from these collectives adopts a unique approach, utilizing the 1% vehicle term instead of the common 1% customer term to represent typical customer stress. This study shows that the driven mileage and the number of vehicles are crucial factors in 1% vehicle analysis. An analysis of the characteristics of the 1% vehicle is conducted, followed by an exploration to determine the required vehicle quantity for obtaining stable results. The shape parameter of the damage distribution determines the necessary number of vehicles for a reliable conclusion. Additionally, a comparative analysis of market-specific customer requirements between the US and Europe is presented, and real usage differences in customer operations are explained using an operating point frequency heatmap. The information presented in this paper provides valuable input for optimizing durability design and conducting efficient, customer-oriented tests, resulting in significant reductions in development time and costs.

Influence of corrosion on loading capacity of circular concrete-filled steel tubular column

Concrete-filled steel tubular (CFST) columns are commonly used in engineering, especially in load-bearing structures. This study conducts an in-depth examination of how the axial resistance of CFST columns varies with random corrosion. A finite element model for circular CFST columns is developed and its accuracy is verified using available experimental data. The interaction between the outer steel tube and the concrete column is explored, along with the introduction of a strength reduction coefficient concept. Additionally, the concept of an axial load-bearing capacity reduction coefficient is introduced to illustrate variations in the axial resistance of circular CFST columns during different corrosion stages. The degradation patterns of reduction coefficients for uniform and random corrosion depths in the steel tube and CFST columns with varying mass loss rates are analyzed, and formulas are provided to predict the axial resistance in different corrosion stages. Furthermore, the study investigates the influence of variables such as material strength, component dimensions, and the thickness of the external steel tube, resulting in adjustments to the original expressions for various conditions.

A nonsmooth dynamics framework for simulating frictionless spatial joints with clearances

AbstractReal-world multibody systems do not have ideal joints; most joints have some clearance. The clearance allows the connected bodies to undergo a misalignment, and the resulting dynamics is governed by the contacts thus formed. Two approaches are typically taken to deal with contacts: the commonly used continuous dynamics approaches assume the Hertzian nature of the contact modeled by nonlinear unilateral spring-damper elements; while the nonsmooth dynamics approach results in a complementarity problem. This paper employs a nonsmooth dynamics approach to develop a coherent framework for the simulation of multibody systems having frictionless joints with clearances. Because clearances are of small magnitude relative to the dimensions of the mechanical components, the nature of the contact in the joints is assumed to be inelastic. Using this assumption and the general nonsmooth dynamics framework, the parametric formulations for cylindrical, prismatic, and revolute joints with clearances are derived. The equations of motion are formulated, and their time-discretized counterparts are cast as a nonlinear programming problem. The proposed scheme also enforces normalization constraint on Euler parameters in contrast to state-of-the-art methods that is conducive to stability of the solution for a suitable range of step sizes. In addition, a variable time-stepping scheme that includes the step size as an extra variable in the optimization is introduced and its stability properties are discussed. The versatility of the proposed framework is demonstrated through numerical experiments.

An improved optimization method combining particle swarm optimization and dimension reduction kriging surrogate model for high-dimensional optimization problems

An improved optimization method is proposed which combines the particle swarm optimization (PSO) algorithm with the dimension reduction kriging surrogate model (DK), namely PSO + DK. In this method, a surrogate model is dynamically constructed and updated between the lower dimensional principal components and the response, instead of between the high-dimensional design variables and the response as in traditional methods. The key point of DK is that the principal components analysis (PCA) is integrated with the active learning kriging surrogate model (AK). Since PCA can reduce the dimension effectively, DK makes surrogate model construction possible for complex high-dimensional optimization problems. Numerical examples and four classical engineering problems are presented to validate the effectiveness of the proposed method. The results show that the proposed method can decrease the computational cost significantly while guaranteeing the precision compared with PSO and PSO + AK for high-dimensional optimization problems.

Ultra-miniature dual-wavelength spatial frequency domain imaging for micro-endoscopy.

There is a need for a cost-effective, quantitative imaging tool that can be deployed endoscopically to better detect early stage gastrointestinal cancers. Spatial frequency domain imaging (SFDI) is a low-cost imaging technique that produces near-real time, quantitative maps of absorption and reduced scattering coefficients, but most implementations are bulky and suitable only for use outside the body. We aim to develop an ultra-miniature SFDI system comprising an optical fiber array (diameter 0.125mm) and a micro camera ( package) to displace conventionally bulky components, in particular, the projector. First, we fabricated a prototype with an outer diameter of 3mm, although the individual component dimensions could permit future packaging to a diameter. We developed a phase-tracking algorithm to rapidly extract images with fringe projections at three equispaced phase shifts to perform SFDI demodulation. To validate the performance, we first demonstrate comparable recovery of quantitative optical properties between our ultra-miniature system and a conventional bench-top SFDI system with an agreement of 15% and 6% for absorption and reduced scattering, respectively. Next, we demonstrate imaging of absorption and reduced scattering of tissue-mimicking phantoms providing enhanced contrast between simulated tissue types (healthy and tumour), done simultaneously at wavelengths of 515 and 660nm. Using a support vector machine classifier, we estimate that sensitivity and specificity values of are feasible for detecting simulated squamous cell carcinoma. This device shows promise as a cost-effective, quantitative imaging tool to detect variations in optical absorption and scattering as indicators of cancer.

Penalized deep partially linear cox models with application to CT scans of lung cancer patients.

Lung cancer is a leading cause of cancer mortality globally, highlighting the importance of understanding its mortality risks to design effective patient-centered therapies. The National Lung Screening Trial (NLST) employed computed tomography texture analysis, which provides objective measurements of texture patterns on CT scans, to quantify the mortality risks of lung cancer patients. Partially linear Cox models have gained popularity for survival analysis by dissecting the hazard function into parametric and nonparametric components, allowing for the effective incorporation of both well-established risk factors (such as age and clinical variables) and emerging risk factors (eg, image features) within a unified framework. However, when the dimension of parametric components exceeds the sample size, the task of model fitting becomes formidable, while nonparametric modeling grapples with the curse of dimensionality. We propose a novel Penalized Deep Partially Linear Cox Model (Penalized DPLC), which incorporates the smoothly clipped absolute deviation (SCAD) penalty to select important texture features and employs a deep neural network to estimate the nonparametric component of the model. We prove the convergence and asymptotic properties of the estimator and compare it to other methods through extensive simulation studies, evaluating its performance in risk prediction and feature selection. The proposed method is applied to the NLST study dataset to uncover the effects of key clinical and imaging risk factors on patients' survival. Our findings provide valuable insights into the relationship between these factors and survival outcomes.

Design And Analysis of Flapping Wing Aircraft Based on Crank Mechanism

This paper is proposed a flapping wing aircraft based on the crank slider mechanism to solve the problems of the two flapping wing structures, such as synchronization and excessive local stress common to existing ornithopters. MATLAB is used to solve the equations to determine the dimensions of the individual components, and the 3D model is designed by SolidWorks software. The static analysis on flapping wings, the static stress, and the static strain distribution map of flapping wings are carried out. Moreover, the mechanism of flapping wing aircraft is modeled in Adams software, which simulates the actual structure by designing the kinematic constraint relationships between the components. It was concluded that the flapping wing could achieve a flapping angle of 30 degrees in one cycle, which was consistent with the simulation results by MATLAB. Furthermore, it was found that the first principal stress of the danger point was less than the yield strength of the material to determine the rationality of material selection. Finally, the fluid trace distribution on the upper and lower sides of the flapping wings was analyzed, which was consistent with the actual situation.

Identification of Vegetation Surfaces and Volumes by Height Levels in Reservoir Deltas Using UAS Techniques—Case Study at Gilău Reservoir, Transylvania, Romania

The hydrophilic vegetation from reservoir deltas sustains rapid expansions in surface and important increases in vegetal mass against a background of a significant influx of alluvium and nutrients from watercourses. It contributes to reservoir water quality degradation and reservoir silting due to organic residues. In this paper, we propose an evaluation method of two-dimensional and three-dimensional parameters (surfaces and volumes of vegetation), using the combined photogrammetric techniques from the UAS category. Raster and vector data—high-resolution orthophotoplan (2D), point cloud (pseudo-LIDAR) (3D), points that defined the topographic surface (DTM—Digital Terrain Model (3D) and DSM—Digital Surface Model (3D))—were the basis for the realization of grid products (a DTM and DSM, respectively). After the successive completion of the operations within the adopted workflow (data acquisition, processing, post-processing, and their integration into GIS), after the grid analysis, the two proposed variables (topics) of this research, respectively, the surface of vegetation and its volume, resulted. The data acquisition area (deriving grids with a centimeter resolution) under the conditions of some areas being inaccessible using classical topometric or bathymetric means (low depth, the presence of organic mud and aquatic vegetation, etc.) has an important role in the reservoirs’ depth dynamics and reservoir usage. After performing the calculations in the abovementioned direction, we arrived at results of practical and scientific interest: Cut Volume = 196,000.3 m3, Cut 2D Surface Area = 63,549 m2, Fill Volume = 16.59998 m3, Fill 2D Surface Area = 879.43 m2, Total Volume Between Surfaces = 196,016.9 m3. We specify that this approach does not aim to study the vegetation’s diversity but to determine its dimensional components (surface and volume), whose organic residues participate in mitigating the reservoir functions (water supply, hydropower production, flash flood attenuation capacity, etc.).

The catcher in the mind: validation of the brief-mentalized affectivity scale for adolescents in the Italian population.

The concept of mentalized affectivity (MA) encompasses the dimensions of identifying, processing, and expressing emotions and describes the process of making sense of and reevaluating one's affects in light of autobiographical memory. This construct was developed within the theoretical framework of mentalization and, due to its interpersonal nature, added further complexity to the emotion regulation construct. This research aimed to examine the factor structure and psychometric properties of the Brief-Mentalized Affectivity Scale for adolescents (B-MAS-A) on an Italian sample of young people (aged 13-19 years). Data were collected using non-probabilistic sampling and an online survey. Participants were asked to complete a large battery of instruments, including the B-MAS-A, the Toronto Alexithymia Scale, the Reflective Functioning Questionnaire, the Epistemic Trust, Mistrust, and Credulity Questionnaire, the Strengths and Difficulties Questionnaire, and the General Self-Efficacy Scale. In study 1, factor analyses carried out on a total sample of 566 adolescents identified 3 distinct dimensions of the same components of MA found in the adult population: i) identifying; ii) processing; iii) expressing emotions. The subscales showed excellent internal consistency. Study 2 (involving a subsample of 288 participants) demonstrated good levels of construct and criterion validity. These results confirm that the B-MAS-A represents a valid and robust instrument for assessing the complex and multifaceted characteristics of MA in adolescents. The B-MAS-A can make a significant contribution to clinical practice and research and encourage systematic studies on MA in psychotherapy, taking into account the developmental stage of adolescence.

Wideband high-gain low-profile series-fed antenna integrated with optimized metamaterials for 5G millimeter wave applications.

This paper presents a series-fed four-dipole antenna with a broad bandwidth, high gain, and compact size for 5G millimeter wave (mm-wave) applications. The single dipole antenna provides a maximum gain of 6.2 dBi within its operational bandwidth, which ranges from 25.2 to 32.8GHz. The proposed approach to enhance both gain and bandwidth involves a series-fed antenna design. It comprises four dipoles with varying lengths, and a truncated ground plane. These dipoles are connected in series on both sides, running in parallel through a microstrip line. The proposed design significantly enhances the bandwidth, which extends from 26.5 to 40GHz. This frequency range effectively covers the 5G bands of 28 and 38GHz. The expedited trust-region (TR) gradient-based search algorithm is utilized to optimize the dimensions of the antenna components, resulting in a maximum gain of 11.2 dBi at 38GHz. To further enhance the gain, modified H-shaped metamaterial (MTM)-based unit cells are integrated into the antenna substrate. The TR algorithm is employed once more to optimize the MTM dimensions, yielding a maximum gain of 15.1 dBi at 38GHz. The developed system is experimentally validated, showing excellent agreement between the simulated and measured data.