Designs

33 pages, 824 KiB

Open AccessReview

Artificial Intelligence in Generative Design: A Structured Review of Trends and Opportunities in Techniques and Applications

by Owen Peckham, Jonathan Raines, Erik Bulsink, Mark Goudswaard, James Gopsill, David Barton, Aydin Nassehi and Ben Hicks

Designs 2025, 9(4), 79; https://doi.org/10.3390/designs9040079 - 23 Jun 2025

Abstract

This review explores the intersection of Artificial Intelligence (AI) and Generative Design (GD) in engineering within the mechanical, industrial, civil, and architectural domains. Driven by advances in AI and computational resources, this intersection has grown rapidly, yielding over 14,000 publications since 2016. To [...] Read more.

This review explores the intersection of Artificial Intelligence (AI) and Generative Design (GD) in engineering within the mechanical, industrial, civil, and architectural domains. Driven by advances in AI and computational resources, this intersection has grown rapidly, yielding over 14,000 publications since 2016. To map the research landscape, this review employed semantic search and Natural Language Processing, parsing 14,355 publications to ultimately select the 88 most relevant studies through clustering and topic modelling. These studies were categorised according to AI and GD techniques, application domains, benefits, and limitations, providing insights into research trends and practical implications. The results reveal a significant growth in the integration of advanced generative AI methods, notably Generative Adversarial Networks for direct design generation, alongside the continued use of genetic algorithms and surrogate models (e.g., Convolutional Neural Networks and Multilayer Perceptrons) to manage computational complexity. Structural and aerodynamic applications were the most common, with benefits including improvements in computational efficiency and design diversity. However, barriers remain, including data generation costs, model accuracy, and interpretability. Research opportunities include the development of generalisable foundation surrogate models, the integration of emerging generative methods such as diffusion models and large language models, and the explicit consideration of manufacturability constraints within generative processes. Full article

(This article belongs to the Special Issue Application of Artificial Intelligence in Smart Factories: From Sensor Networks to Large Language Models)

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16 pages, 2357 KiB

Open AccessArticle

A Novel Integrated CAD-Multibody Approach for TMJ Prosthesis Design

by Talal Bin Irshad, Giulia Pascoletti, Stefano Pagano, Chiara Valenti and Elisabetta Maria Zanetti

Designs 2025, 9(4), 78; https://doi.org/10.3390/designs9040078 - 20 Jun 2025

Abstract

This study presents a methodology for optimizing the design of the fossa component in temporomandibular joint (TMJ) prostheses, particularly in cases requiring replacement due to severe pathology or trauma. Leveraging advancements in 3D printing, the research aims to align prosthetic function with natural [...] Read more.

This study presents a methodology for optimizing the design of the fossa component in temporomandibular joint (TMJ) prostheses, particularly in cases requiring replacement due to severe pathology or trauma. Leveraging advancements in 3D printing, the research aims to align prosthetic function with natural jaw movements. A multibody simulation model was used to evaluate different designs based on key performance indicators: range of motion, condylar trajectory accuracy, and contact force magnitudes. Three designs were analyzed: a compact design fossa (CDF) with a spherical condyle, an enhanced design fossa (EDF) with a more anatomically realistic structure, and a simulation-driven design (MEDF) derived from condylar motion patterns. The results indicate that CDF could lead to dislocation at 13° of mouth opening. In contrast, EDF and MEDF safely enabled full opening (20°), closely replicated natural condyle trajectories (with deviations under 2.5 mm in all directions), and reduced contact forces, which can contribute to a longer prosthesis lifespan. MEDF showed the lowest peak contact force (−21% compared to EDF). The study successfully established a framework for evaluating and guiding patient-specific TMJ prosthetic designs, enhancing both functional rehabilitation and mechanical durability by minimizing wear through optimized contact dynamics. Full article

(This article belongs to the Collection Editorial Board Members’ Collection Series: Biomaterials Design)

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19 pages, 2042 KiB

Open AccessArticle

The Role of Building Geometry in Urban Heat Islands: Case of Doha, Qatar

by Mohammad Najjar, Madhavi Indraganti and Raffaello Furlan

Designs 2025, 9(3), 77; https://doi.org/10.3390/designs9030077 - 19 Jun 2025

Abstract

The increase in temperature in the built environment impedes the utilization of outdoor amenities and non-motorized transportation by residents of Arabian Gulf cities throughout the prolonged hot season. The urban heat island (UHI) phenomenon, denoted by the substantial temperature difference between the city [...] Read more.

The increase in temperature in the built environment impedes the utilization of outdoor amenities and non-motorized transportation by residents of Arabian Gulf cities throughout the prolonged hot season. The urban heat island (UHI) phenomenon, denoted by the substantial temperature difference between the city and its periphery, is associated with multiple parameters. Building heights, setbacks, and configurations influence the temperature within street canyons. Nowadays, it is vital for urban designers to understand the role of these parameters in UHI effect, and translate those insights into design guidelines and urban forms they propose. This study delves into the relationship between building geometry and urban heat island effects in the context of Doha City, using residential building areas as the basis for comparison. Using dual-pronged methodology, the study entails simulating the dry bulb temperature and the sky view factor, alongside field measurements for land surface temperature (LST), across two residential zones within the city. This analytical approach integrates both prescribed building regulations and the physical characteristics of the extant urban fabric and configuration. Climate data were collected from the weather station in the format of EnergyPlus weather data, and LST historical data were collected from satellite imagery datasets. The results show a correlation between building geometry and UHI-related metrics, particularly evident during nocturnal periods. Notably, a negative correlation was found between the sky view factor and temperature increments. The study concludes with a strong correlation between building geometry and UHI, underscoring the imperative of integrating the building geometry and configuration considerations within the broader context of urban environmental assessments. While similar studies have been undertaken in different regions, there is a research gap in UHI within the GCC region. This study aims to contribute valuable insights to understanding urban heat island dynamics in Gulf cities. Full article

(This article belongs to the Special Issue Sustainable Construction: Innovations in Design, Engineering, and the Circular Economy)

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20 pages, 3823 KiB

Open AccessArticle

Theoretical Performance of BaSnO₃-Based Perovskite Solar Cell Designs Under Variable Light Intensities, Temperatures, and Donor and Defect Densities

by Nouf Alkathran, Shubhranshu Bhandari and Tapas K. Mallick

Designs 2025, 9(3), 76; https://doi.org/10.3390/designs9030076 - 18 Jun 2025

Abstract

Barium stannate (BaSnO₃) has emerged as a promising alternative electron transport material owing to its superior electron mobility, resistance to UV degradation, and energy bandgap tunability, yet BaSnO₃-based perovskite solar cells have not reached the efficiency levels of TiO [...] Read more.

Barium stannate (BaSnO₃) has emerged as a promising alternative electron transport material owing to its superior electron mobility, resistance to UV degradation, and energy bandgap tunability, yet BaSnO₃-based perovskite solar cells have not reached the efficiency levels of TiO₂-based designs. This theoretical study presents a design-driven evaluation of BaSnO₃-based perovskite solar cell architectures, incorporating MAPbI₃ or FAMAPbI₃ perovskite materials, Spiro-OMeTAD, or Cu₂O hole transport materials as well as hole-free configurations, under varying light intensity. Using a systematic device modelling approach, we explore the influence of key design variables—such as layer thickness, donor density, and interface defect concentration—of BaSnO₃ and operating temperature on the power conversion efficiency (PCE). Among the proposed designs, the FTO/BaSnO₃/FAMAPbI₃/Cu₂O/Au heterostructure exhibits an exceptionally effective arrangement with PCE of 38.2% under concentrated light (10,000 W/m², or 10 Sun). The structure also demonstrates strong thermal robustness up to 400 K, with a low temperature coefficient of −0.078% K⁻¹. These results underscore the importance of material and structural optimisation in PSC design and highlight the role of high-mobility, thermally stable inorganic transport layers—BaSnO₃ as the electron transport material (ETM) and Cu₂O as the hole transport material (HTM)—in enabling efficient and stable photovoltaic performance under high irradiance. The study contributes valuable insights into the rational design of high-performance PSCs for emerging solar technologies. Full article

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21 pages, 1445 KiB

Open AccessArticle

1D Finite Element Modeling of Bond-Slip Behavior and Deflection in Reinforced Concrete Flexural Members

by Rahaf Mohamad, George Wardeh, Mayada Al Ahmad Al Kousa and Ali Jahami

Designs 2025, 9(3), 75; https://doi.org/10.3390/designs9030075 - 18 Jun 2025

Abstract

The serviceability limit state (SLS) is a crucial aspect of structural design, ensuring that reinforced concrete structures perform satisfactorily under everyday loading conditions without excessive deflections, vibrations, or cracking that could compromise their functionality or aesthetics. This study investigates the bond-slip relationship in [...] Read more.

The serviceability limit state (SLS) is a crucial aspect of structural design, ensuring that reinforced concrete structures perform satisfactorily under everyday loading conditions without excessive deflections, vibrations, or cracking that could compromise their functionality or aesthetics. This study investigates the bond-slip relationship in flexural reinforced concrete members. The focus is on the influence of concrete fracture properties on the stress and strain distribution in the cracked zone. A 1D Finite Element Method (FEM) model was developed to better predict the distribution of stress and slip along the length of the reinforcement as well as the deflection. The proposed method uses material models and their interactions to provide a reliable analysis of the nonlinear behavior of RC beams, including crack width and crack spacing. A database built with numerous experimental results available in the bibliographic references allowed for the validation of the model. The results of some phenomenological models were discussed. A comprehensive analysis of the Eurocode 2 (EC2) method for calculating the deflection and cracking control of RC members was also performed. The results indicate a clear enhancement in the precision of deflection prediction in comparison to the perfect bond assumptions outlined in Eurocode 2. Additionally, the research successfully quantifies a 4–17% increase in deflection attributable to bond-slip effects. Full article

(This article belongs to the Special Issue Sustainable Construction: Innovations in Design, Engineering, and the Circular Economy)

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16 pages, 14369 KiB

Open AccessArticle

Durability Analysis of a Magneto-Rheological Fluid for Automotive Braking System

by Giovanni Imberti, Henrique de Carvalho Pinheiro, Matteo De Carlo, Guglielmo Peruzzi and Massimiliana Carello

Designs 2025, 9(3), 74; https://doi.org/10.3390/designs9030074 - 17 Jun 2025

Abstract

The automotive market is looking for innovative braking solutions that can mitigate or eliminate secondary emissions. For this reason, new braking paradigms have been developed, and magnetorheological brakes could be considered a suitable solution due to their performance and controllability features. Reliability is [...] Read more.

The automotive market is looking for innovative braking solutions that can mitigate or eliminate secondary emissions. For this reason, new braking paradigms have been developed, and magnetorheological brakes could be considered a suitable solution due to their performance and controllability features. Reliability is a key factor for automotive braking systems, so it is essential to analyze the behavior of such technological solutions in iterative cycles to understand their capability of maintaining brake performance throughout their operative lifecycles. This article presents a preliminary experimental durability analysis and defines the testing standard procedures to be used as boundaries for this analysis. Then, a durability test bench is developed and produced to evaluate the magnetorheological fluid over an equivalent distance of 100,000 km. After the tests, the fluid’s characteristics are compared to its original features using a rheometer apparatus and Scanning Electron Microscopy (SEM). Full article

(This article belongs to the Collection Editorial Board Members’ Collection Series: Designs of New Generation Vehicles)

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22 pages, 2918 KiB

Open AccessArticle

Design and Development of a Low-Power IoT System for Continuous Temperature Monitoring

by Luis Miguel Pires, João Figueiredo, Ricardo Martins, João Nascimento and José Martins

Designs 2025, 9(3), 73; https://doi.org/10.3390/designs9030073 - 12 Jun 2025

Abstract

This article presents the development of a compact, high-precision, and energy-efficient temperature monitoring system designed for tracking applications where continuous and accurate thermal monitoring is essential. Built around the HY0020 System-on-Chip (SoC), the system integrates two bandgap-based temperature sensors—one internal to the SoC [...] Read more.

This article presents the development of a compact, high-precision, and energy-efficient temperature monitoring system designed for tracking applications where continuous and accurate thermal monitoring is essential. Built around the HY0020 System-on-Chip (SoC), the system integrates two bandgap-based temperature sensors—one internal to the SoC and one external (Si7020-A20)—mounted on a custom PCB and powered by a coin cell battery. A distinctive feature of the system is its support for real-time parameterization of the internal sensor, which enables advanced capabilities such as thermal profiling, cross-validation, and onboard diagnostics. The system was evaluated under both room temperature and refrigeration conditions, demonstrating high accuracy with the internal sensor showing an average error of 0.041 °C and −0.36 °C, respectively, and absolute errors below ±0.5 °C. With an average current draw of just 0.01727 mA, the system achieves an estimated autonomy of 6.6 years on a 1000 mAh battery. Data are transmitted via Bluetooth Low Energy (BLE) to a Raspberry Pi 4 gateway and forwarded to an IoT cloud platform for remote access and analysis. With a total cost of approximately EUR 20 and built entirely from commercially available components, this system offers a scalable and cost-effective solution for a wide range of temperature-sensitive applications. Its combination of precision, long-term autonomy, and advanced diagnostic capabilities make it suitable for deployment in diverse fields such as supply chain monitoring, environmental sensing, biomedical storage, and smart infrastructure—where reliable, low-maintenance thermal tracking is essential. Full article

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17 pages, 6132 KiB

Open AccessArticle

Crash Performance of Additively Manufactured Tapered Tube Crash Boxes: Influence of Material and Geometric Parameters

by Ahmed Saber, Mehmet Ali Güler, Erdem Acar, Omar Soliman ElSayed, Hussain Aldallal, Abdulrahman Alsadi and Yousef Aldousari

Designs 2025, 9(3), 72; https://doi.org/10.3390/designs9030072 - 12 Jun 2025

Abstract

Crash boxes play a crucial role in mitigating force during vehicle collisions by absorbing impact energy. Additive manufacturing (AM), particularly Fused Deposition Modeling (FDM), has emerged as a promising method for their fabrication due to its design flexibility and continuous advancements in material [...] Read more.

Crash boxes play a crucial role in mitigating force during vehicle collisions by absorbing impact energy. Additive manufacturing (AM), particularly Fused Deposition Modeling (FDM), has emerged as a promising method for their fabrication due to its design flexibility and continuous advancements in material development. This study investigates the crash performance of tapered crash box configurations, each manufactured using two FDM materials: Carbon Fiber-Reinforced Polylactic Acid (PLA-CF) and Polylactic Acid Plus (PLA+). The specimens vary in wall thickness and taper angles to evaluate the influence of geometric and material parameters on crashworthiness. The results demonstrated that both specific energy absorption (

S E A

) and crush force efficiency (

C F E

) increase with wall thickness and taper angle, with PLA-CF consistently outperforming PLA+ in both metrics. ANOVA results showed that wall thickness is the most influential factor in crashworthiness, accounting for 73.18% of

S E A

variation and 58.19% of

C F E

variation. Taper angle contributed 13.49% to

S E A

and 31.49% to

C F E

, while material type had smaller but significant effects, contributing 0.66% to

S E A

and 0.11% to

C F E

. Regression models were developed based on the experimental data to predict

S E A

and

C F E,

with a maximum absolute percentage error of 4.97%. These models guided the design of new configurations, with the optimal case achieving an

S E A

of 32.086 ± 0.190 kJ/kg and a

C F E

of 0.745 ± 0.034. The findings confirm the potential of PLA-CF in enhancing the energy-absorption capability of crash boxes, particularly in tapered designs. Full article

(This article belongs to the Special Issue Post-manufacturing Testing and Characterization of Materials)

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30 pages, 5635 KiB

Open AccessReview

Advances and Perspectives in Alkali–Silica Reaction (ASR) Testing: A Critical Review of Reactivity and Mitigation Assessments

by Osama Omar, Hussain Al Hatailah and Antonio Nanni

Designs 2025, 9(3), 71; https://doi.org/10.3390/designs9030071 - 11 Jun 2025

Abstract

The alkali–silica reaction (ASR) is a critical concern for concrete durability, yet its assessment remains challenging and directly impacts mixture design decisions. This review shows that the inconsistencies are more prevalent in mitigation evaluations compared to aggregate reactivity assessments, mainly due to the [...] Read more.

The alkali–silica reaction (ASR) is a critical concern for concrete durability, yet its assessment remains challenging and directly impacts mixture design decisions. This review shows that the inconsistencies are more prevalent in mitigation evaluations compared to aggregate reactivity assessments, mainly due to the chemical variations in SCMs. A validated framework is suggested to determine the optimal SCM optimal replacement levels for ASR mitigation based on extensive field data, offering direct guidance for mix design decisions involving potentially reactive aggregates. The combination of the accelerated mortar bar test (AMBT) and the miniature concrete prism test (MCPT) is shown to be a reliable alternative for the concrete prism test (CPT) in aggregate reactivity. Also, their extended versions, AMBT (28-day) and MCPT (84-day), can be applied for SCMs mitigation evaluation. Given the slower reactivity of SCMs compared to ordinary Portland cement (OPC), the importance of incorporating indirect test methods, such as the modified R3 test and bulk resistivity is underscored. In addition, emerging sustainability shifts further complicate ASR assessment, including the adoption of Portland limestone cement (PLC), the use of seawater in concrete, and the declining availability of fly ash (FA) and slag. These changes call for updated ASR testing specifications and increased research into natural pozzolans (NPs) as promising SCMs for future ASR mitigation. Full article

(This article belongs to the Special Issue Sustainable Construction: Innovations in Design, Engineering, and the Circular Economy)

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16 pages, 4576 KiB

Open AccessArticle

EMM Project—LD GRIDS: Design of a Charged Dust Analyser for Moon Exploration

by Diego Scaccabarozzi, Abdelrahman Mohamed Ragab M. Ahmed, Andrea Appiani, Bortolino Saggin, Carmen Porto and Francesca Esposito

Designs 2025, 9(3), 70; https://doi.org/10.3390/designs9030070 - 10 Jun 2025

Abstract

This work presents a comparative design of the sensing elements for the Lunar Dust GRID System (LD GRIDS), a dust analyser conceived to measure charged particles on future lunar missions. LD GRIDS replaces traditional electrodes with continuous conductive grids, i.e., the sensing elements [...] Read more.

This work presents a comparative design of the sensing elements for the Lunar Dust GRID System (LD GRIDS), a dust analyser conceived to measure charged particles on future lunar missions. LD GRIDS replaces traditional electrodes with continuous conductive grids, i.e., the sensing elements of the instrument, which are able to collect induced charge when charged particles pass through them. The investigation focuses on evaluating the influence of various grid geometrical parameters (size, thickness, and patterns) on the sensor’s performance, either from an electrical or a mechanical perspective. All simulations were carried out using off-the-shelf numerical modelling software, where electrostatic simulation (i.e., induction performance), modal analysis, and quasi-static structural responses under a high acceleration quasi-static load were examined. The results indicate that while grids with round patterns tend to produce a higher induced charge, they also experience higher localised stresses compared to square pattern ones. Moreover, grid size does not significantly affect the instrument sensitivity, whereas increasing the grid thickness significantly reduces peak stresses, with only minor effects on electrostatic performance. Overall, the findings provided valuable insights for optimising the LD GRIDS design, aimed at balancing either electrostatic sensitivity or mechanical resistance, facing the harsh lunar environment. Full article

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24 pages, 6049 KiB

Open AccessArticle

Bayesian Optimized of CNN-M-LSTM for Thermal Comfort Prediction and Load Forecasting in Commercial Buildings

by Chi Nghiep Le, Stefan Stojcevski, Tan Ngoc Dinh, Arangarajan Vinayagam, Alex Stojcevski and Jaideep Chandran

Designs 2025, 9(3), 69; https://doi.org/10.3390/designs9030069 - 4 Jun 2025

Abstract

Heating, ventilation, and air conditioning (HVAC) systems account for 60% of the energy consumption in commercial buildings. Each year, millions of dollars are spent on electricity bills by commercial building operators. To address this energy consumption challenge, a predictive model named Bayesian optimisation [...] Read more.

Heating, ventilation, and air conditioning (HVAC) systems account for 60% of the energy consumption in commercial buildings. Each year, millions of dollars are spent on electricity bills by commercial building operators. To address this energy consumption challenge, a predictive model named Bayesian optimisation Convolution Neural Network Multivariate Long Short-term Memory (BO CNN-M-LSTM) is introduced in this research. The proposed model is designed to perform load forecasting, optimizing energy usage in commercial buildings. The CNN block extracts local features, whereas the M-LSTM captures temporal dependencies. The hyperparameter fine tuning framework applied Bayesian optimization to enhance output prediction by modifying model properties with data characteristics. Moreover, to improve occupant well-being in commercial buildings, the thermal comfort adaptive model developed by de Dear and Brager was applied to ambient temperature in the preprocessing stage. As a result, across all four datasets, the BO CNN-M-LSTM consistently outperformed other models, achieving an 8% improvement in mean percentage absolute error (MAPE), 2% in normalized root mean square error (NRMSE), and 2% in R² score.This indicates the consistent performance of BO CNN-M-LSTM under varying environmental factors, highlight the model robustness and adaptability. Hence, the BO CNN-M-LSTM model is a highly effective predictive load forecasting tool for commercial building HVAC systems. Full article

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24 pages, 3541 KiB

Open AccessArticle

Substructure Optimization for a Semi-Submersible Floating Wind Turbine Under Extreme Environmental Conditions

by Kevin Fletcher, Edem Tetteh, Eric Loth, Chris Qin and Rick Damiani

Designs 2025, 9(3), 68; https://doi.org/10.3390/designs9030068 - 3 Jun 2025

Abstract

A barrier to the adoption of floating offshore wind turbines is their high cost relative to conventional fixed-bottom wind turbines. The largest contributor to this cost disparity is generally the floating substructure, due to its large size and complexity. Typically, a primary driver [...] Read more.

A barrier to the adoption of floating offshore wind turbines is their high cost relative to conventional fixed-bottom wind turbines. The largest contributor to this cost disparity is generally the floating substructure, due to its large size and complexity. Typically, a primary driver of the geometry and size of a floating substructure is the extreme environmental load case of Region 4, where platform loads are the greatest due to the impact of extreme wind and waves. To address this cost issue, a new concept for a floating offshore wind turbine’s substructure, its moorings, and anchors was optimized for a reference 10-MW turbine under extreme load conditions using OpenFAST. The levelized cost of energy was minimized by fixing the above-water turbine design and minimizing the equivalent substructure mass, which is based on the mass of all substructure components (stem, legs, buoyancy cans, mooring, and anchoring system) and associated costs of their materials, manufacturing, and installation. A stepped optimization scheme was used to allow an understanding of their influence on both the system cost and system dynamic responses for the extreme parked load case. The design variables investigated include the length and tautness ratio of the mooring lines, length and draft of the cans, and lengths of the legs and the stem. The dynamic responses investigated include the platform pitch, platform roll, nacelle horizontal acceleration, and can submergence. Some constraints were imposed on the dynamic responses of interest, and the metacentric height of the floating system was used to ensure static stability. The results offer insight into the parametric influence on turbine motion and on the potential savings that can be achieved through optimization of individual substructure components. A 36% reduction in substructure costs was achieved while slightly improving the hydrodynamic stability in pitch and yielding a somewhat large surge motion and slight roll increase. Full article

(This article belongs to the Special Issue Design and Analysis of Offshore Wind Turbines)

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18 pages, 9335 KiB

Open AccessArticle

Image Matching Algorithm for Transmission Towers Based on CLAHE and Improved RANSAC

by Ruihua Chen, Pan Yao, Shuo Wang, Chuanlong Lyu and Yuge Xu

Designs 2025, 9(3), 67; https://doi.org/10.3390/designs9030067 - 29 May 2025

Abstract

To address the lack of robustness against illumination and blurring variations in aerial images of transmission towers, an improved image matching algorithm for aerial images is proposed. The proposed algorithm consists of two main components: an enhanced AKAZE algorithm and an improved three-stage [...] Read more.

To address the lack of robustness against illumination and blurring variations in aerial images of transmission towers, an improved image matching algorithm for aerial images is proposed. The proposed algorithm consists of two main components: an enhanced AKAZE algorithm and an improved three-stage feature matching strategy, which are used for feature point detection and feature matching, respectively. First, the improved AKAZE enhances image contrast using Contrast-Limited Adaptive Histogram Equalization (CLAHE), which highlights target features and improves robustness against environmental interference. Subsequently, the original AKAZE algorithm is employed to detect feature points and construct binary descriptors. Building upon this, an improved three-stage feature matching strategy is proposed to estimate the geometric transformation between image pairs. Specifically, the strategy begins with initial feature matching using the nearest neighbor ratio (NNR) method, followed by outlier rejection via the Grid-based Motion Statistics (GMS) algorithm. Finally, an improved Random Sample Consensus (RANSAC) algorithm computes the transformation matrix, further enhancing matching efficiency. Experimental results demonstrate that the proposed method exceeds the original AKAZE algorithm’s matching accuracy by 4∼15% on different image sets while achieving faster matching speeds. Under real-world conditions with UAV-captured aerial images of transmission towers, the proposed algorithm achieves over 95% matching accuracy, which is higher than other algorithms. Our proposed algorithm enables fast and accurate matching of transmission tower aerial images. Full article

(This article belongs to the Section Electrical Engineering Design)

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19 pages, 9237 KiB

Open AccessArticle

Mechanical Properties of 17-4 PH Stainless Steel Manufactured by Atomic Diffusion Additive Manufacturing

by Animesh Kumar Basak, Jasim Mohammed Sali and Alokesh Pramanik

Designs 2025, 9(3), 66; https://doi.org/10.3390/designs9030066 - 28 May 2025

Abstract

Atomic diffusion additive manufacturing (ADAM) is a specialized extrusion-based metal additive manufacturing (MAM) process where metal parts are produced through a three-stage process of printing, de-binding and sintering. Several scientific facts, such as dimensional error, surface quality, tensile behavior and the internal structure [...] Read more.

Atomic diffusion additive manufacturing (ADAM) is a specialized extrusion-based metal additive manufacturing (MAM) process where metal parts are produced through a three-stage process of printing, de-binding and sintering. Several scientific facts, such as dimensional error, surface quality, tensile behavior and the internal structure of this process for specific materials for certain conditions, are not well explained in the existing literature. To address these issues, the present manuscript investigates the effect of infill type and shell thickness on 17-4 precipitation-hardened (PH) stainless steels on the dimensional accuracy, surface roughness and mechanical properties of the printed specimens. It was found that the strength (maximum ultimate tensile strength up to 1049.1 MPa) and hardness (290 HRB) of the specimens mainly depend on shell thickness, while infill type plays a relatively minor role. The principle of atomic diffusion may be the reason behind this pattern, as an increase in shell thickness is essentially an increase in the density of material deposited during printing, allowing more fusion during sintering and thus increasing its strength. The two different infill types (triangular and gyroid) contribute towards minimal changes, although it should be noted that triangular specimens exhibited greater ultimate tensile strength, whereas the gyroid had slightly longer elongation at break. Dimensional accuracy and surface roughness for all the specimens remain reasonably consistent. The cross-section of the tensile tested specimens revealed significant pores in the microstructure that could contribute to a reduction in the mechanical properties of the specimens. Full article

(This article belongs to the Special Issue Post-manufacturing Testing and Characterization of Materials)

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22 pages, 1554 KiB

Open AccessArticle

Designing Sustainable Asphalt Pavement Structures with a Cement-Treated Base (CTB) and Recycled Concrete Aggregate (RCA): A Case Study from a Developing Country

by Oswaldo Guerrero-Bustamante, Rafael Camargo, Jose Duque, Gilberto Martinez-Arguelles, Rodrigo Polo-Mendoza, Carlos Acosta and Michel Murillo

Designs 2025, 9(3), 65; https://doi.org/10.3390/designs9030065 - 20 May 2025

Abstract

Pavement structures are one of the most critical civil infrastructures for the socio-economic development of communities. However, pavement construction demands an elevated financial budget and generates large amounts of environmental impacts. Accordingly, the new trends in daily engineering practices have integrated sustainability criteria [...] Read more.

Pavement structures are one of the most critical civil infrastructures for the socio-economic development of communities. However, pavement construction demands an elevated financial budget and generates large amounts of environmental impacts. Accordingly, the new trends in daily engineering practices have integrated sustainability criteria verification into traditional pavement design procedures. Thus, this research explores the sustainability implications of asphalt pavement incorporating a Cement-Treated Base (CTB) and Recycled Concrete Aggregate (RCA) within the local context of a Global South country. The environmental and economic performances of four different types of asphalt structures were assessed, each differing in how the CTB is employed. These structures include conventional flexible pavement, semi-rigid pavement, inverted base pavement, and simple composite pavement. Furthermore, each structure is evaluated under four varying contents of coarse RCA (i.e., 0%, 15%, 30%, and 45%) in their asphalt mixtures. This approach results in a comprehensive analysis spanning 16 unique scenarios, providing valuable insights into the interplay between RCA content and CTB inclusion for sustainable infrastructure development. It is important to highlight that the Life-Cycle Assessment and Life-Cycle Cost Analysis methodologies were implemented to perform the environmental and economic inspections, respectively. Overall, this investigation demonstrates that although pavement structures comply with mechanistic design standards, they can yield significantly different cost effectiveness and environmental burdens from each other. Therefore, executing a sustainability-related appraisal is essential for accomplishing definitive infrastructure designs. Consequently, this research effort is expected to be used by stakeholders (e.g., civil engineers, designers, and governmental agencies) to support data-driven decision making in the road infrastructure industry. Full article

(This article belongs to the Special Issue Sustainable Construction: Innovations in Design, Engineering, and the Circular Economy)

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21 pages, 6647 KiB

Open AccessArticle

Optimizing Beam Stiffness and Beam Modal Response with Variable Spacing and Extrusion (VaSE)

by Patrick N. Murphy, Richard A. Vittum III and Bashir Khoda

Designs 2025, 9(3), 64; https://doi.org/10.3390/designs9030064 - 19 May 2025

Abstract

This paper presents a novel algorithm, Variable Spacing and Extrusion (VaSE), designed to optimize the infill pattern of material extrusion (ME) 3D-printed parts for specified mechanical performance while ensuring manufacturability. The algorithm adjusts deposition spacing and width across layers to achieve functionally graded [...] Read more.

This paper presents a novel algorithm, Variable Spacing and Extrusion (VaSE), designed to optimize the infill pattern of material extrusion (ME) 3D-printed parts for specified mechanical performance while ensuring manufacturability. The algorithm adjusts deposition spacing and width across layers to achieve functionally graded infill distributions derived from input density maps. First, the variable line spacing algorithm is implemented by normalizing the weighted density distribution. Errors in between the desired density and the density from the line spacing are corrected with a varying extrusion width algorithm. Two application scenarios are demonstrated with the proposed VaSE algorithm. First, beam samples are optimized for flexural stiffness and tested under three-point bending, showing a 10.8–19.2% stiffness increase compared to homogeneous infill, except at low (25%) volume fractions, where local buckling dominated failure. The second scenario involves maximizing the frequency of the first three modes of beams under an induced vibration. The optimized beams, taken straight from a topology optimization algorithm performed in the ANSYS 2023 finite element software, were compared to the beams that were instead put through the VaSE algorithm after the topology optimization. While all manufactured beams underperform relative to simulation, the VaSE-optimized beams show substantial frequency gains (34–63% for the first mode, 0.82–65% for the second mode) over purely geometry-based designs, with the exception of high-mass-fraction beams. These findings highlight the significance of the VaSE algorithm in enhancing mechanical performance and extending the design space of ME additive manufacturing beyond conventional homogeneous infill strategies. Full article

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25 pages, 5202 KiB

Open AccessArticle

Hybrid Adaptive Sheep Flock Optimization and Gradient Descent Optimization for Energy Management in a Grid-Connected Microgrid

by Sri Harish Nandigam, Krishna Mohan Reddy Pothireddy, K. Nageswara Rao and Surender Reddy Salkuti

Designs 2025, 9(3), 63; https://doi.org/10.3390/designs9030063 - 16 May 2025

Abstract

Distributed generation has emerged as a viable solution to supplement traditional grid problems and lessen their negative effects on the environment worldwide. Nevertheless, distributed generation issues are unpredictable and intermittent and impede the power system’s ability to operate effectively. Moreover, the problems associated [...] Read more.

Distributed generation has emerged as a viable solution to supplement traditional grid problems and lessen their negative effects on the environment worldwide. Nevertheless, distributed generation issues are unpredictable and intermittent and impede the power system’s ability to operate effectively. Moreover, the problems associated with outliers and denial of service (DoS) attacks hinder energy management. Therefore, efficient energy management in grid-connected microgrids is critical to ensure sustainability, cost efficiency, and reliability in the presence of uncertainties, outliers, denial-of-service attacks, and false data injection attacks. This paper proposes a hybrid optimization approach that combines adaptive sheep flock optimization (ASFO) and gradient descent optimization (GDO) to address the challenges of energy dispatch and load balancing in MG. The ASFO algorithm offers robust global search capabilities to explore complex search spaces, while GDO safeguards precise local convergence to optimize the dispatch schedule and energy cost and maximize renewable energy utilization. The hybrid method ASFOGDO leverages the strengths of both algorithms to overcome the limitations of standalone approaches. Results demonstrate the efficiency of the proposed hybrid algorithm, achieving substantial improvements in energy efficiency and cost reduction compared to traditional methods like interior point optimization, gradient descent, branch and bound, and a population-based algorithm named Golden Jackal optimization. In case 1, the overall cost in scenario 1 and scenario 2 was reduced from 1620.4 rupees to 1422.84 rupees, whereas, in case 2, the total cost was reduced from 12,350 rupees to 12,017 rupees with the proposed hybrid ASFOGDO algorithm. Further, a detailed impact of attacks and outliers on scheduling, operational cost, and reliability of supply is presented in case 3. Full article

(This article belongs to the Collection Editorial Board Members’ Collection Series: Smart Energy Systems Design)

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17 pages, 9985 KiB

Open AccessArticle

Mechanical Design of a Novel Functionally Graded Lattice Structure for Long Bone Scaffolds

by Fabio Distefano, Gabriella Epasto, Mahsa Zojaji and Heidi-Lynn Ploeg

Designs 2025, 9(3), 62; https://doi.org/10.3390/designs9030062 - 16 May 2025

Abstract

Open-cellular Ti6Al4V lattice structures have found application in porous scaffolds that can match the properties of human bone, which consists of a dense cortical shell and a less-dense cancellous core with an apparent density ranging from 1.3 to 2.1 g/cm³ and 0.1 [...] Read more.

Open-cellular Ti6Al4V lattice structures have found application in porous scaffolds that can match the properties of human bone, which consists of a dense cortical shell and a less-dense cancellous core with an apparent density ranging from 1.3 to 2.1 g/cm³ and 0.1 to 1.3 g/cm³, respectively. The implantation of porous scaffolds is essential for treating large bone defects and must mimic natural bone’s geometric and mechanical behaviour. Functionally graded lattice structures offer spatial variation in mechanical properties, making them suitable for biomedical applications. While the mechanical behaviour of lattice structures is typically evaluated under compression, their flexural properties remain largely underexplored. The aim of this research is to assess the flexural rigidity of a novel lattice material, namely Triply Arranged Octagonal Rings (TAORs), with both uniform and functionally graded architectures, to reproduce the flexural properties of long bones. Titanium alloy scaffolds have been designed with a TAOR cell, whose relative densities range from 10% to 40% with full and hollow sections. Morphological considerations were carried out during the design process to obtain a scaffold geometry which complies with the optimal characteristics required to promote osteointegration. A non-linear finite element (FE) model was developed. Three- and four-point bending tests were simulated, and the results were compared with those of a bone surrogate for long bones. Scaffolds with 10% and 20% relative densities showed flexural rigidity close to that of the bone surrogate and proved to be potential candidates for application in biomedical devices for long bones. Full article

(This article belongs to the Section Bioengineering Design)

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25 pages, 3758 KiB

Open AccessArticle

An Efficient Framework for Secure Communication in Internet of Drone Networks Using Deep Computing

by Vivek Kumar Pandey, Shiv Prakash, Aditya Ranjan, Sudhanshu Kumar Jha, Xin Liu and Rajkumar Singh Rathore

Designs 2025, 9(3), 61; https://doi.org/10.3390/designs9030061 - 13 May 2025

Abstract

The rapid deployment of the Internet of Drones (IoD) across different fields has brought forth enormous security threats in real-time data communication. To overcome authentication vulnerabilities, this paper introduces a secure lightweight framework integrating deep learning-based user behavior analysis and cryptographic protocols. The [...] Read more.

The rapid deployment of the Internet of Drones (IoD) across different fields has brought forth enormous security threats in real-time data communication. To overcome authentication vulnerabilities, this paper introduces a secure lightweight framework integrating deep learning-based user behavior analysis and cryptographic protocols. The proposed framework is verified through AVISPA security verification against replay, man-in-the-middle, and impersonation attacks. Performance analysis via NS2 simulations based on changing network parameters (5–50 drones, 1–20 users, 2–8 ground stations) validates enhancements in computation overhead, authentication delay, memory usage, power consumption, and communication effectiveness in comparison with recent models such as LDAP, TAUROT, IoD-Auth, and LEMAP, thereby establishing our system as an optimal choice for safe IoD operation. Full article

(This article belongs to the Collection Editorial Board Members’ Collection Series: Drone Design)

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