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Impact of post weld heat treatment on structural and mechanical properties of dissimilar high strength steels

(2026-02) Shoke, Lerato S; Mutombo, Kalenda; Olubambi, P; Zondi, MC

This study explores the influence of Submerged Arc Welding (SAW) parameters on the microstructural evolution, mechanical properties, and residual stresses in dissimilar welds of A516 Gr70 and A106 GrB high-strength carbon steels. Through a comprehensive experimental approach, this study delineates the direct relationship between the welding heat input, determined by the voltage, current, and speed, and its profound impact on the heat-affected zone (HAZ) size, microstructure, and mechanical properties, such as hardness and tensile strength. The investigation revealed that the optimal welding parameters play a critical role in controlling the bead geometry and HAZ size, which in tum significantly affect the mechanical integrity and performance of the welded joint. Notably, this study revealed that a higher heat input does not necessarily lead to a larger HAZ, challenging the conventional assumptions in welding practices. Furthermore, this study delves into the effects of post-weld heat treatment (PWHT) techniques, including normalizing, quenching, and annealing, on reversing the microstructural alterations induced by welding and restoring the initial mechanical properties of the base metals. Microstructural analyses employing stereo microscopy, optical microscopy, scanning electron microscopy, and X-ray diffraction techniques provide insight into the granular details of the morphological changes across different regions of the weld, highlighting the formation of martensitic lathes in the weld bead region and variations in the pearlite-ferrite matrix. Mechanical testing and hardness profiles substantiate these findings, illustrating the significant influence of cooling rates and heat treatment methods on the mechanical properties of the weldments. This study highlights the importance of controlled heat treatment in enhancing material performance, suggesting avenues for further research into parameter optimization, fatigue assessments, and advanced heat treatment techniques to refine welding processes for industrial applications.

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Enhanced concept-based exploration of manipulators’ design spaces with kinematics, dynamics and control co-design

(2026-08) Modungwa, Dithoto M

Determining the parameters of a manipulator for optimal performance is a challenging task. This is primarily due to possible conflicting objectives, various tasks that should be considered, and the highly non-linear behavior that is involved. This work proposes an enhanced version of the concept-based design space exploration (C-DSE) approach for the design of manipulators. According to the C-DSE approach, prior to the search, the designers divide the set of feasible solutions into meaningful subsets, which are termed concepts. The design space exploration involves a simultaneous search for optimal solutions within each of the pre-defined concepts. This enhanced framework integrates the following: (1) kinematics, dynamics, and control co-design, and the simultaneous optimization of manipulator morphology and controller parameters; (2) surrogate-assisted optimization using Gaussian process (GP) and neural network (NN) models to reduce computational cost; (3) approximately 30 performance metrics spanning kinematic, dynamic, structural, control, and task performance domains; (4) task-aware feasibility verification applying a multi-level hierarchy; (5) a generative AI integration pathway using diffusion models and LLM-guided concept generation (proposed in this preliminary investigation). The results demonstrate a 95.7% reduction in high-fidelity function evaluations (50,000 to 2150), corresponding to a 23.3 times reduction in evaluation count and a 6.6 times reduction in wall-clock computation time (25 h to 3.8 h). Co-design yields up to a 35% improvement in energy efficiency and a 28% reduction in tracking error compared to sequential morphology-only optimization.

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A review of vehicle wheel misalignment detection techniques

(2026-07) Mashigo, KI; Ayomoh, MK; Erasmus, Louwrence D; Nenzhelele, TG

Wheel (mis)alignment is one of the factors influencing vehicle safety, tire wear, and energy efficiency. While alignment procedures are well established in automotive workshops, recent advances in sensing, connectivity, and data-driven methods have led to renewed academic interest. This goes against existing research, which remains fragmented around vehicle types and methodologies. This study conducts a scoping review of wheel alignment monitoring and detection methods, with a focus on passenger vehicles. Guided by PRISMA-ScR, 453 studies were identified, of which 386 were excluded and 13 were duplicates and thus removed, resulting in a small number remaining for thematic analysis. Three dominant methodological approaches emerged: (i) traditional measurement methods, (ii) sensor-based vehicle dynamics analysis, and (iii) data-driven methods employing machine learning and vehicle telemetry. The findings revealed limited research on vehicle applications, especially for intelligent, integrated, and scalable alignment technologies and real-time, in-service monitoring applications. Other challenges included data quality, calibration, and cost-effectiveness. Therefore, the development of an integrated real-time wheel misalignment detection and reporting framework grounded in systems engineering and enterprise architecture principles is proposed.

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A comprehensive analysis of identity theft: Definitions, types, and impacts

(2026-05) Ntshangase, Cynthia S; Steyn, AS

Identity theft is a complex and evolving phenomenon spanning physical, digital, algorithmic, and hybrid domains. This paper presents a systematic literature review following PRISMA guidelines to consolidate definitions, identify major and emerging subtypes, and assess impacts on individuals, organisations, and society. The study proposes a comprehensive definition that unifies fragmented and subtype‑specific descriptions in the literature and explicitly encompasses document‑based, child, offline, familial, criminal, synthetic, biometric, and algorithmic identity theft. We clarify that our bibliometric analysis reflects research attention rather than real‑world incidence and explain the practical implications of this distinction. To enhance applied value, we discuss Africa‑specific identity‑management challenges, including persistent identity document fraud, and the rise of synthetic identities, and outline how the taxonomy supports national ID authorities, policy makers, financial institutions, and fraud‑prevention bodies in South Africa and across the continent. Benefits include improved incident‑response categorisation, more comprehensive compliance checklists, enhanced risk assessments, and clearer cross‑sector communication. The review highlights a research focus bias toward financial theft and calls for further empirical work on underexplored subtypes (e.g., familial, child, algorithmic, deceased). We conclude with future research that triangulates bibliometric signals with incident statistics and operational data to inform resilient identity‑management frameworks.

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Prediction of doped silicon phases for enhanced lithium-ion battery anodes: Exploring the superior potential of C, N, and F doping

(2026-07) Singoa, S; Phoshoko, Katlego W; Mogashoa, T; Ngoepe, P; Ledwaba, R

Silicon-based anodes are promising candidates for next-generation lithium-ion batteries owing to their high theoretical capacity, natural abundance, and environmental compatibility. However, their practical implementation is limited by severe volume expansion during lithiation and delithiation, resulting in particle pulverization, loss of electrical contact, and instability of the solid electrolyte interphase (SEI) layer. Doping has emerged as an effective strategy to mitigate these challenges and improve the structural and electrochemical performance of silicon anodes. In this study, the effects of carbon, nitrogen, and fluorine doping on silicon were investigated using the cluster expansion method. Several ordered phases, including SiC, SiF2, SiF5, SiN, SiN2, and SiN5, were predicted to be the most thermodynamically stable structures along the DFT ground-state line. SiN exhibited the most balanced overall performance, as indicated by thermodynamic, mechanical, and dynamical stability, along with semiconducting behaviour and a band gap of 1.76 eV. In contrast, SiN2 displayed semi- metallic conductivity and superior ductility (Pugh’s ratio =2.48, Poisson’s ratio =0.32), although phonon calculations indicated vibrational instability. Carbon doping produced the dynamically stable SiC phase with an enlarged band gap of 2.31 eV but increased brittleness, while fluorine-doped phases exhibited favourable electronic properties but poor mechanical and vibrational stability. The results demonstrate that dopant selection strongly influences the structural, electronic, mechanical, and vibrational properties of silicon, with nitrogen doping offering the most promising route for developing durable silicon-based lithium-ion battery anodes.