Journal of Sustainable Smart Materials and Structural Systems
The Journal of Sustainable Smart Materials and Structural Systems (JSSMSS) is an international, open-access, peer-reviewed journal dedicated to advancing knowledge in the fields of smart materials, sustainable composites, and structural systems. The journal serves as a multidisciplinary platform for scientists, engineers, academics, and industry practitioners involved in the design, innovation, development, and deployment of advanced materials and intelligent systems. This journal is hosted by Universiti Kuala Lumpur, Malaysian Institute of Marine Engineering Technology (MIMET), Jalan Pantai Remis Lumut Perak, Malaysia. JSSMSS is published by Open Horizon Global. The UNIKL MIMET commitment to genuine open access to scholarly content extends to authors as a service to the research community.
Failure Analysis of Follower Assembly in the 155mm Artillery Gun
Abstract: The follower assembly is a critical component of the 155mm artillery gun, which acts as a safety lock for the trigger mechanism during firing and releases it effortlessly for recoiling. During the firepower mission, issues arose where the follower assembly part would constantly bend or become crooked. This resulted in the roller detaching itself from the assembly and, therefore, reducing the equipment's effectiveness and negatively disrupting the firepower mission. This failure could have major repercussions for both military operations and national defence capabilities. This study investigates the failures and subjects them to macroscopic inspection, metallographic examination, hardness testing, and fractography analysis. A close look at the microstructure showed the existence of three separate layers: an ultra-fine martensitic layer near the surface, a fine martensitic layer closer to the core, and a normal martensite layer covering the rest of the microstructure. The hardness profile also decreases from the near surface to the core of the follower (part of the follower assembly). An analysis using fractography showed small round or long dimples on the fracture surface. The analysis proved that the follower had an overload ductile fracture. The material of the follower is unknown, and a chemical composition analysis was conducted for re-engineering purposes, showing that its composition closely matches that of AISI 4340. The analysis concludes that the follower is a post-treated ductile material. The authors recommend optimising the heat treatment process to enhance its strength and toughness, along with several suggestions for future studies.
Copyright (c) 2026 Journal of Sustainable Smart Materials and Structural Systems
Decision Intelligence in Collaborative Intelligent Manufacturing of smart and sustainable materials: A Comprehensive Review of Artificial Intelligence, Optimization, Digital Twins, and Human-Centered Decision-Making
The rapid transition from Industry 4.0 to Industry 5.0 has significantly increased the complexity of manufacturing systems while accelerating the development and deployment of smart and sustainable materials in advanced industrial applications. These emerging materials require intelligent decision-making approaches that integrate data, advanced analytics, optimization, digital twins, and human expertise throughout their design, production, monitoring, and lifecycle management. Although artificial intelligence, machine learning, digital twins, and mathematical optimization have independently advanced intelligent manufacturing, their isolated application often limits adaptability, explainability, and resilience. This study presents a systematic literature review of Decision Intelligence (DI) in collaborative intelligent manufacturing following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, synthesizing evidence from 140 peer-reviewed publications. The review comprehensively examines the evolution of Decision Intelligence, core enabling technologies, layered architectures, industrial applications, human-centered decision-making, implementation challenges, and emerging research trends. The findings indicate that effective Decision Intelligence requires the seamless integration of artificial intelligence, optimization, digital twins, knowledge graphs, explainable AI, and Human-in-the-Loop AI within a unified decision ecosystem that combines computational intelligence with human judgment. The proposed framework and research roadmap provide valuable theoretical insights and practical guidance for developing resilient, explainable, and human-centric Decision Intelligence systems that support the realization of Industry 5.0 manufacturing for smart and sustainable materials.
Recent Advancements in Sugarcane Bagasse-based Composites for Sustainable Waste Utilization
Sugarcane Bagasse (SB) composites have significant potential as a substitute for conventional materials due to their distinct properties, sustainability, and eco-friendly characteristics. This paper explores the utilization of SB waste in fabricating eco-friendly composite materials for sustainable industrial applications. Technological developments in the fabrication of composites using SB have led to significant enhancements in the mechanical performance, interfacial strength, and durability of these materials. Chemical treatments such as alkali treatment, silane treatment, and acetylation treatment of SB fibers play crucial role in bonding behavior of SB fiber with matrices. Nano- and micro-fillers have also been incorporated to improve the performance of SB-based composites through improved fiber-matrix interaction. Due to the unique properties, SB composites have gained attention in various industries, including construction industry, automobile industry, packaging industry, etc. The automotive sector could utilize SB bio-composites of interior parts contributing to energy reduced dependence on conventional plastic materials. SB-based bioplastics could serve as a substitute for traditional plastics that is biodegradable in the packaging industry to help solve problems related to waste plastic. The continuous development of SB composites indicates a promising future in which SB could become an excellent choice for producing sustainable materials, contributing to the circular economy. However, more systematic research is needed to properly integrate SB-based composites in various advanced applications.
Material Selection and Fiber Orientation Effects in Composite Overwrapped Steel Pipelines: A Numerical Study for Burst Pressure Enhancement
This study establishes a validated finite element framework for optimizing the burst capacity of petroleum-grade steel pipelines reinforced with composite overwraps. Addressing the limitations of classical netting analysis, the research develops a coupled ANSYS Mechanical and ACP workflow to systematically evaluate the influence of fiber orientation on structural integrity. The methodology first validates the static structural approach against Barlow’s equation using a thin-walled baseline (100 mm diameter, 3 mm wall), yielding a numerical failure pressure of 15.75 MPa against an analytical prediction of 13.8 MPa. Upon validation, the framework is scaled to a production-grade geometry (168.3 mm diameter, 7.1 mm wall) to execute a parametric sweep of winding angles (25 to 90 degrees) across four material systems: Epoxy E-Glass Wet, S-Glass UD, Carbon UD (230 GPa), and Woven Carbon. The results reveal a critical divergence in failure mechanics governed by fiber topology. Unidirectional systems (Carbon, S-Glass, E-Glass) consistently exhibit a "helical advantage," achieving maximum burst pressure at 25 degrees—with Carbon UD peaking at 51.24 MPa—due to superior shear stiffening and axial confinement. Conversely, Woven Carbon displays a unique recovery trend, maximizing performance at 90 degrees (49.15 MPa) where its bidirectional architecture effectively balances hoop stresses. These findings provide a reproducible "angle–performance map" for field engineers, demonstrating that while low-angle helical wraps are optimal for high-modulus tapes, hoop-dominant configurations are required for woven fabrics, thereby refining design guidelines for in-situ pipeline rehabilitation.
A Thermally Robust Porous Basalt Foam for Elevated-Temperature Acoustic Absorption
High-temperature sound absorbers are required for thermally severe environments where acoustic attenuation must remain effective during heat exposure. Here, a porous Basalt Foam (BF) was fabricated through Tween 80-assisted fiber dispersion, sodium silicate-mediated local bonding, layer-by-layer assembly, and controlled compaction. The resulting foam combined low bulk density, high porosity, localized binder bonding, and an interconnected fibrous pore network. Direct flame exposure showed localized heating followed by rapid cooling, while the foam retained its structural integrity. SEM analysis confirmed that sodium silicate mainly formed local joints at fiber-fiber contact points without blocking the open porous framework. Acoustic testing using an impedance tube showed that sound absorption was strongly dependent on frequency, thickness, and temperature. The 25 mm BF maintained effective absorption at 100, 300, and 500 °C, while the 50 mm BF showed strong absorption at 200, 400, and 600 °C. Thicker samples provided broader and more stable absorption due to longer acoustic pathways and enhanced viscous/thermal dissipation within the tortuous fiber network. Compression testing further confirmed structural integrity, with partial recovery after large deformation. Overall, the developed BF offers a simple, lightweight, inorganic, and thermally robust porous architecture for high-temperature noise-control applications.
Sustainable Material Selection for Regional Australian Infrastructure
As infrastructure development accelerates globally, engineers are increasingly required to balance structural performance, cost, and environmental responsibility in material selection. This study evaluates the sustainability of conventional and alternative infrastructure materials using a lifecycle-based multi-criteria framework. Reinforced concrete pipe (RCP) and high-density polyethylene (HDPE) pipe were compared for stormwater systems, while conventional asphalt was evaluated against asphalt incorporating recycled glass aggregate for pavements. A weighted Analytic Hierarchy Process (AHP) model was implemented under three decision scenarios: (i) sustainability-led control (aligned with SDGs 11 and 12), (ii) current engineer priorities, and (iii) developer priorities. For stormwater applications, RCP achieved overall preference scores of approximately 83% (control), 67% (engineer), and 65% (developer), consistently outperforming HDPE. For pavements, asphalt with recycled glass aggregate achieved preference scores of 57% (control), 77% (engineer), and 76% (developer). All AHP matrices satisfied the consistency requirement (CR ≤ 0.10). The findings demonstrate that newer materials are not inherently superior and that material preference is highly sensitive to stakeholder weighting structures. The study highlights the importance of transparent, scenario-based multi-criteria evaluation for sustainable infrastructure decision-making in the Australian context.
Effects of Infill Design and Nozzle Diameter on Tensile Performance of Eco-Friendly PLA
This study investigates the combined effect of nozzle diameter (0.2–0.8 mm) and infill pattern (rectilinear vs. concentric) on the tensile performance and production efficiency of eco-friendly PLA components fabricated using Fused Deposition Modeling (FDM). Forty ISO 527-2 Type 1A specimens were printed using a Bambu Lab A1 mini printer and tested for ultimate tensile strength (Rm), elongation at break (εb), and print time. Results indicate that nozzle diameters of 0.4–0.6 mm combined with concentric infill deliver the highest mechanical performance, achieving tensile strengths of 45–55 MPa and elongation superior to rectilinear infill by 10–15%. Increasing nozzle diameter from 0.2 mm to 0.8 mm reduces printing time by up to 80–85%, with only an ~11% decrease in tensile strength, highlighting a favorable strength-to-time trade-off for rapid prototyping and small-series manufacturing. These findings provide practical guidelines for optimizing FDM parameters to enhance sustainability, reduce energy consumption, and support circular economy principles in additive manufacturing.
Recent Advancements, Trends and Future Prospects of Upper Limb Prosthesis through 3D printing- A Systematic Review
New opportunities for personalised, functional, and affordable rehabilitation interventions have been made possible through the use of smart technologies in the design of prosthetic limbs. Prosthetic devices have had customisation and affordability revolutionised by 3D printing, but the integration of additive manufacturing with embedded sensors and adaptive control systems is still an emerging and exciting discipline. Conceptualization, development, and integration of embedded sensors for real-time evaluation, biomechanical feedback, and user-controlled algorithms are the subject of this review paper, which systematically explores the state-of-the-art of smart 3D-printed prosthetics. Important technologies augmenting prosthesis performance and user experience, including force and pressure sensors, electromyography (EMG) interfaces, inertial measurement units (IMUs), and soft robotics, are elaborated. For the creation of fully intelligent prosthetic systems, the article addresses major gaps that should be filled and identifies current developments and technical hurdles in the areas of biocompatibility, computational signaling, strength, and power management. The article concludes by pointing out that cross-disciplinary collaboration among materials science, biomedical engineering, robotics, and artificial intelligence is necessary to develop fully integrated, autonomous, and low-cost smart prostheses. Furthermore, the review highlights sustainability-driven advantages of 3D-printed prosthetics, including material efficiency, recyclability of thermoplastics, low-power sensing architectures, and environmentally responsible, low-cost manufacturing pathways.
Patient-Worn Bracelet for Real-Time Heart Rate and SpO₂ Monitoring with Predictive Health Analysis in Hospital and Remote Settings
This study presents a wearable health monitoring system designed as a smart structural system that integrates mechanical design, and embedded sensing to continuously track heart rate and SpO₂ levels in real time. The need for such a system arises from the growing demand for accessible healthcare, particularly for individuals with limited access to regular medical check-ups. Hospitals face challenges in providing timely care due to overwhelming workloads when staff are responsible for monitoring many patients. This system addresses that issue by offering a tool that facilitates more efficient patient monitoring through intelligent material-structure integration. The system integrates a MAX30102 sensor with an ESP32-C3 Xiao microcontroller and uses fuzzy logic algorithms to classify health conditions, such as Normal or Hypoxemia, in real time. Data is wirelessly transmitted from the sensor to a mobile application using Bluetooth BLE and is then stored in a Firebase database for easy access by healthcare professionals. The mobile application provides healthcare providers with immediate access to the latest health data, allowing them to take action if needed. Testing demonstrated successful real-time data transmission with classification accuracy of health status categories. The system reduces the physical effort required by healthcare staff to check on patients individually, offering a more efficient method of monitoring. Energy efficiency analysis shows optimized power consumption enabling extended battery life suitable for continuous monitoring. This study represents a practical and sustainable solution for enhancing healthcare delivery by allowing for remote monitoring of patients and improving workflow in medical settings. The system is designed with scalability and sustainability in mind, incorporating recyclable materials and modular components that facilitate future upgrades or sensor additions.
Toward Smart and Autonomous Surface Quality Prediction: A Review of AI-Driven Approaches
As precision manufacturing evolves toward Industry 4.0, the transition from retrospective inspection to real-time Surface Quality Prediction (SQP) has become a critical requirement for autonomous process control. This study presents a systematic review and critical synthesis of Artificial Intelligence (AI)-driven SQP methodologies across machining, grinding, and finishing operations. Using a mixed-method framework combining bibliometric mapping with qualitative content analysis, 38 seminal studies were evaluated to classify current approaches into parameter-based, signal-based, and hybrid architectures. The comparative analysis reveals that hybrid models, which fuse static machining parameters with dynamic multi-sensor feedback, consistently outperform single-source techniques, achieving determination coefficients (R²) exceeding 0.90 and reducing root-mean-squared error (RMSE) to below 10%. Furthermore, the integration of physics-aware features was found to improve prediction accuracy by 25–30%, while transfer learning strategies demonstrated the capacity to reduce training data requirements by approximately 60%, effectively mitigating data scarcity in high-mix production environments. Despite these advances, barriers regarding model explainability, computational latency, and data heterogeneity persist. Consequently, this paper proposes a unified framework that converges process physics, data-driven modeling, and digital twin technologies, establishing a theoretical basis for interpretable, scalable, and sustainable precision manufacturing ecosystems.
Copyright (c) 2025 Journal of Sustainable Smart Materials and Structural Systems
Enhancing Sustainability in Construction through Recycled Concrete Aggregate (RCA): Technological and Policy Perspectives
In the context of the circular economy, the incorporation of construction and demolition (C&D) waste as recycled concrete aggregate (RCA) offers a crucial chance to promote sustainability in the building industry. This research investigates the technological, financial, and environmental effects of using construction and demolition waste as RCA in the manufacturing of concrete. The potential of RCA to lessen landfill usage, cut greenhouse gas emissions, and lessen dependency on natural aggregates is highlighted. The study examines life cycle assessment (LCA) measures, performance features of RCA-based concrete, and existing practices. The results show that although RCA could have worse mechanical qualities than virgin aggregates, these impacts can be reduced with the right processing and mix design changes. Additionally, by encouraging resource efficiency, waste reduction, and material reuse, RCA supports the tenets of the circular economy. In order to effectively reap the benefits of recycling construction and demolition waste in sustainable construction practices, this study emphasises the necessity of updated standards, legislative support, and industry collaboration.
Design Simulation of Ultimate Loading Leg Jacket with Different Types of Bracing
The structural performance of fixed offshore jacket platforms is strongly governed by the configuration of their bracing systems, which control global stiffness, load transfer mechanisms, and member utilization. This study presents a comparative linear static analysis of four common jacket bracing configurations—X-bracing, V-bracing, K-bracing, and diagonal bracing—under operational and extreme storm loading conditions. Numerical simulations were performed using the Structural Analysis Computer System (SACS), incorporating realistic geometric parameters, boundary conditions, gravity loads, and environmental actions in accordance with offshore design practice. Key performance indicators evaluated include the total number of structural members, axial stress distribution along elevation, and unity check (UC) ratios for structural safety assessment. The results indicate that X-bracing provides superior load redistribution and consistently lower UC ratios across critical elevations, reflecting higher structural efficiency and redundancy. In contrast, V- and diagonal bracing systems exhibit higher member utilization, particularly at lower elevations, due to less effective load paths. The findings demonstrate that appropriate bracing selection can enhance structural efficiency while reducing material demand, supporting sustainable design strategies for offshore jacket platforms.
Preliminary Finite Element Analysis on Fixed Offshore Platform Joints
This study investigates the structural integrity of a fixed offshore platform using finite element analysis (FEA) to compare the stresses acting on the jacket joints to withstand gravity and environmental loads at two elevation levels with the equivalent static loads (ESLs) method. The three-dimensional CAD model is precisely designed with AutoCAD software and then analysed with FEA PTC Creo software for accurate numerical analysis and stress forecasting. Material selection follows API guidelines, considering necessary properties for the analysis such as Poisson's ratio, Young's modulus, and thermal expansion coefficient. The static stress analysis indicates that the structural steel joints exhibit elastic behaviour and are well below their yield and ultimate tensile strength limits. The displacement and strain values offer details about the platform's deformation characteristics. Comparisons between elevations above and below the sea level reveal variations in stress distribution and provide valuable insights for designing and optimising fixed offshore platforms to improve their reliability.
Comparative Study on Structural Health Monitoring for Small Boat Using Fibre Bragg Grating
The marine sector increasingly requires safer and more efficient vessels, especially small boats used in critical operations. This study explores the use of Fibre Bragg Grating (FBG) sensors for Structural Health Monitoring (SHM) in a small aluminum boat. FBG sensors were chosen for their high sensitivity, immunity to electromagnetic interference, and capability to provide real-time strain measurements. Nine FBG sensors were installed at key structural locations on the boat. Data obtained from Finite Element Analysis (FEA) was compared with real-time sensor readings to evaluate correlation and validate the SHM approach. Findings show that FBG sensors effectively capture structural behavior, particularly in high-strain areas such as the midship. The integration of simulation and sensor-based monitoring enables proactive maintenance, enhances safety, and extends the vessel’s operational lifespan.
Shear Studs Effect on the Seismic Behavior of Steel Beam– Concrete-Filled Tube Column Connections
The purpose of this study is to investigate the effect of the geometrical shape of the shear studs of steel-concrete composite column on the structural behavior of the steel beam to column connection. The effect of the desired parameter on the force-displacement curve, strain energy, internal energy, and the amount of plastic dissipated energy is investigated. In this research, 19 models were developed in ABAQUS finite element software using L-shaped, U-shaped and T-shaped shear studs. The results show that by increasing the parameters such as the stiffness and shear resistance of the steel-concrete composite column system, their bearing capacity increases. Finally, force-displacement interaction diagrams have been developed for steel-concrete composite columns. The results showed that the use of a U-shaped shear stud can increase the column tolerated forces by 295%. Also, the most increases are related to models with U-shaped studs, and then models with L-shaped studs, in which the forces have increased by 233%. The most increase in displacement belongs to U-shaped studs, which showed a 52% increase in displacement capacity of the connection.
Temperature-Dependent Sound Absorption Characteristics of Perforated Porous Metamaterials
Recent studies have demonstrated that sound absorption performance can be improved by constructing macroscopic perforations on a porous material matrix. In this paper, the temperature-dependent sound absorption characteristics of three different perforated porous materials (PPMs) with cylindrical (C-PPM), normal conical (NC-PPM) and reverse conical (RC-PPM) perforations are comparatively studied. We used a double porosity theoretical model to study the high-temperature sound absorption of these PPMs and validated it by numerical simulations. The sound absorption mechanism and temperature effect are revealed by the numerical distributions of sound pressure, sound energy dissipation density and sound intensity flow. The results show that the PPMs exhibit better sound absorption than porous material matrix (PMM), especially at low frequencies. This is attributed to the pressure diffusion effect of PPMs, and this effect is enhanced by high temperatures. Furthermore, the three PPMs have sound absorption peaks in different frequency ranges, but high temperatures delay their appearance. Finally, we discussed the effects of perforated shape, perforated size and material properties on sound absorption and identified their optimal values.
Catalyst Reuse in Biodiesel Production using Waste Cooking Oil for Energy Sustainability
The most important results of these studies demonstrate Amberlite 62i's effectiveness in making energy processes more sustainable. It is traditionally used for water treatment, but also exhibits significant catalytic activity in biodiesel production, making it a versatile material for achieving energy sustainability. This dual-use approach reduces the need for additional catalysts and lowers the overall environmental footprint of biodiesel production, enhancing resource efficiency. The transesterification reaction was carried out between WCO and methanol at molar ratio of 6:1, using Amberlite 62i as the catalyst at loading of 10 wt%. Reactions were conducted at various temperatures (50, 55, 60, and 65 OC) and stirring speeds (100, 200, 300, and 400 rpm) using magnetic stirrer for 120 minutes. Catalyst reusability was assessed based on the condition that yielded the highest conversion, and the catalyst was reused for four consecutive cycles. The highest conversion of 84% was achieved at 300 rpm and 65 OC. Notably, the catalyst demonstrated consistent performance in four cycles, resulting in biodiesel conversion rates above 63% without the need for further treatment.
Sustainable Macadamia Nutshell-Based Particulate Composites: Mechanical Performance and Application Potential in Structural Materials
Growing environmental concerns and the global shift toward circular economy practices have accelerated research into bio-composites derived from agricultural by-products. This study presents an initial systematic investigation of ground macadamia nutshell (MNS)-based particulate composites reinforced with epoxy and vinyl ester resins. The effects of filler content (5-30 wt.%) on mechanical performance were evaluated through compressive, tensile, flexural and SEM analyses. Results reveal that composites containing 10-20 wt.% MNS exhibit optimal strength-to-weight ratios, with flexural strength improvements of up to 15% compared to neat resins. Comparative analysis highlights the unique advantages of macadamia nutshells, high density, hardness, and availability as agro-waste, over other natural fillers. These findings demonstrate that MNS composites are not only environmentally sustainable but also mechanically competitive with conventional timber and synthetic composites, offering scalable potential for eco-construction, green building, and structural applications.