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Review Article
Blending Data-Driven Surrogates with Physics - Based Topology Optimization: A Critical Review of Machine Learning - Accelerated Design in Fibre - Reinforced Polymer and Concrete Structures
Girmay Mengesha Azanaw*
Issue:
Volume 10, Issue 3, September 2025
Pages:
80-93
Received:
10 May 2025
Accepted:
29 May 2025
Published:
28 July 2025
Abstract: Blending data driven surrogates with physics based topology optimization holds the promise of revolutionizing the design of fibre reinforced polymer (FRP) composites and concrete structures by dramatically reducing computational cost while preserving-or even enhancing-solution quality. This critical review synthesizes developments from last decade in which machine learning (ML) models such as deep neural networks, Gaussian processes, and ensemble learners have been trained to approximate finite element analyses within iterative optimization loops. The author investigates the applications of Fiber Reinforced Polymer (FRP) composites, wherein the exigencies of continuous fiber orientation and constraints imposed by additive manufacturing necessitate the employment of high-fidelity yet efficient computational solvers. Additionally, The author explore the domain of concrete structures, wherein the inherent heterogeneity, prevalence of cracking, and considerations of durability present distinctive challenges for modeling. By conducting a comprehensive literature review utilizing databases such as Scopus, Web of Science, IEEE Xplore, and MDPI, alongside stringent inclusion criteria, we extract and analyze algorithmic selections, training data configurations, performance metrics (including prediction error and speed-up factors), and outcomes pertaining to manufacturability. The findings indicate that workflows driven by neural surrogate models can achieve accelerations of up to 50 times while maintaining deviations of less than 5% from full-order models; however, limitations in generalizability across various loading scenarios persist. The author delineate critical deficiencies, including the scarcity of benchmark datasets, restricted transfer learning across diverse material systems, and integration challenges with Computer-Aided Design (CAD) and Finite Element Analysis (FEA) frameworks, and The author propose avenues for future research which encompass hybrid physics-based machine learning frameworks and real-time optimization. By elucidating best practices as well as existing challenges, this review offers a strategic roadmap for researchers and practitioners aiming to exploit machine learning-accelerated topology optimization in the advancement of next-generation composite and concrete design.
Abstract: Blending data driven surrogates with physics based topology optimization holds the promise of revolutionizing the design of fibre reinforced polymer (FRP) composites and concrete structures by dramatically reducing computational cost while preserving-or even enhancing-solution quality. This critical review synthesizes developments from last decade ...
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Research Article
Groundwater Quality Investigation in the Coastal Aquifer of Limbe, South West Cameroon
Ewanoge Mesumbe,
Alice Magha Mufur*,
Mathias Fru Fonteh
Issue:
Volume 10, Issue 3, September 2025
Pages:
94-109
Received:
25 March 2025
Accepted:
10 June 2025
Published:
30 July 2025
Abstract: Coastal aquifers are vital fresh water reservoirs that could be affected by seawater intrusion, thereby polluting the water resources. This study investigated the current status of subsurface water in Limbe-Cameroon, focusing on aquifer hydrochemical characteristics. Groundwater samples were obtained from nine boreholes and measurements were conducted on the following physicochemical parameters; pH, electrical conductivity (EC), and total dissolved solids (TDS) and major ions (cations and anions). The results showed that most of the sampled boreholes were in the permissible limits of the World Health Organization (WHO) guidelines, except for a few samples. 11.11% of the pH values, 11.11% of the EC values and 11.11% of the TDS values the WHO recommended limits. Major ion concentrations were below WHO prescribed levels in all analysed samples. The water quality index (WQI) indicated that 44.44% of the samples were of good quality water with water quality values varying from 26-50, 11.11% were classified as poor-quality water and another 11.11% of the samples were unsuitable for drinking purposes. The hydrochemical facies were principally Ca-HCO3 and Ca-Mg-Cl-SO4 water types. Irrigation water quality indices such as sodium adsorption ratio (SAR), Magnesium Hazard (MH), soluble sodium percentage (SSP) indicated that groundwater in Limbe is suitable for irrigation. These higher values signify the possiblity of salt water intrusion in the study area and highlights the critical need for sustainable groundwater management in Limbe to prevent further degradation from seawater intrusion and protect the freshwater resources in the region.
Abstract: Coastal aquifers are vital fresh water reservoirs that could be affected by seawater intrusion, thereby polluting the water resources. This study investigated the current status of subsurface water in Limbe-Cameroon, focusing on aquifer hydrochemical characteristics. Groundwater samples were obtained from nine boreholes and measurements were conduc...
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Research Article
Magnetic Anomalies Induced by Sources with Unknown Geometry
Lady Mireille Razafindranaivo*
Issue:
Volume 10, Issue 3, September 2025
Pages:
110-116
Received:
24 July 2025
Accepted:
4 August 2025
Published:
20 August 2025
Abstract: This research paper addresses the challenges of interpreting magnetic anomalies arising from subsurface sources with unknown or complex geometries, a common issue in geophysical exploration when geological structures deviate from standard, idealized shapes. Traditional inversion methods often rely on geometric assumptions, leading to ambiguities when faced with natural, irregular sources. The study proposes an integrated, geometry-agnostic workflow combining nonparametric equivalent layer modeling, Bayesian Markov Chain Monte Carlo (MCMC) uncertainty quantification, and convolutional neural network (CNN) classification. Synthetic magnetic data generated from amorphous and fractal bodies serve as the basis for validating the method. The equivalent layer inversion reconstructs broad magnetization distributions without the need for explicit geometric constraints, while Bayesian MCMC provides probabilistic estimates and quantifies uncertainty in source parameters such as depth and magnetic moment. This probabilistic approach acknowledges the inherent non-uniqueness of the inverse problem. Additionally, a CNN trained on synthetic datasets can classify magnetic anomalies into source shape categories (bulky, elongated, irregular) with associated uncertainty, enhancing interpretive confidence in complex cases. The study further analyzes sensitivity to noise and magnetization direction variability, demonstrating that these factors critically affect both inversion accuracy and classification performance. Results from synthetic experiments underscore the importance of integrating uncertainty analysis and automated learning in early-stage exploration scenarios, especially when geological information is limited or ambiguous. The proposed framework is shown to enhance the reliability and objectivity of magnetic anomaly interpretation, with future directions involving multi-physics integration and scalable 3D analysis for large regional surveys.
Abstract: This research paper addresses the challenges of interpreting magnetic anomalies arising from subsurface sources with unknown or complex geometries, a common issue in geophysical exploration when geological structures deviate from standard, idealized shapes. Traditional inversion methods often rely on geometric assumptions, leading to ambiguities wh...
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Methodology Article
Environmental Assessment of Heavy Metals Contamination and Radionuclides Exposure in Automotive, Industrial, and Residential Areas in Gboko, Nigeria
Agaku Raymond Msughter*,
Shiada Msugh Stephen,
Bem Timothy Terngu,
Nyijime Simon Ayila,
Aba James Aondolumun
Issue:
Volume 10, Issue 3, September 2025
Pages:
117-129
Received:
11 July 2025
Accepted:
28 July 2025
Published:
21 August 2025
Abstract: This study assessed heavy metal contamination and radionuclide exposure in automobile, industrial, and residential areas in Gboko, Nigeria. The concentration of heavy Metals in the soil of these areas was assessed to determine the presence and activity levels of radionuclides. The evaluation showed the potential health risks associated with exposure to these contaminants and suggested possible remediation and policy recommendations. The study used Atomic Absorption Spectrometry, and soil samples were air dried, while the equipment used to evaluate heavy metals was the Lovibond Tintometer model MD 600. The study used a model equation to analyze the data. Findings revealed that Heavy metal exposure varied across land-use areas, with lead (Pb) levels highest in residential zones (HQ: 0.171) and cadmium (Cd) posing the greatest concern overall, especially in residential areas where the HQ approached 0.380. Chromium (Cr) exposure was most significant in industrial zones, though all hazard quotients remained below hazardous thresholds, while elevated zinc (Zn) levels in automotive workshops stayed within safe limits; radiation levels from Ra-226, Th-232, and K-40 were minimal, with the highest dose in Industrial 1 due to Ra-226 (0.5 Bq/kg) resulting in a TED of 0.2420 mSv/y and ELCR of 0.0847. Nonetheless, all measured values were well below international safety limits, indicating that current heavy metal and radionuclide contamination does not pose significant health risks in the study areas. Proactive environmental monitoring, especially in high-activity zones, is recommended to reduce pollution and safeguard public health.
Abstract: This study assessed heavy metal contamination and radionuclide exposure in automobile, industrial, and residential areas in Gboko, Nigeria. The concentration of heavy Metals in the soil of these areas was assessed to determine the presence and activity levels of radionuclides. The evaluation showed the potential health risks associated with exposur...
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Research Article
Examining the Integration of Geographic Information Systems for Land Rights Confirmation in the Republic of Benin: A Comparative Analysis Using RTK NTRIP Data
Issue:
Volume 10, Issue 3, September 2025
Pages:
130-140
Received:
24 August 2024
Accepted:
18 September 2024
Published:
19 September 2025
Abstract: Geodetic sciences play a pivotal role in catalyzing socio-economic development and exerting a profound influence on our daily lives. These sciences proffer a multitude of methodologies for obtaining geographic coordinates of land parcels, thereby posing a precision challenge that is integral to effective land management and dispute mitigation. In a broader context, particularly within the unique landscape of Benin, where land is increasingly becoming a valuable commodity, the imperative to optimize land databases is pronounced. Attaining precision in coordinates stands out as a critical factor for effective land management, offering a proactive approach to mitigate potential land disputes. To streamline the process and reduce expenses associated with obtaining land titles for parcels, there is a need to explore strategies that efficiently minimize costs incurred by the array of stakeholders involved in the procedural framework. The focal point of this research is the exploration of the utilization of coordinates derived from openly accessible Geographic Information Systems in the formulation of boundary plans during the verification of land rights. Subsequent to this exploration, the acquired results are systematically compared with coordinates derived through direct field surveys employing the RTK NTRIP methodology. The outcomes infer that, notwithstanding the cadastre.bj website providing coordinates with a precision of four decimal places and being intricately linked to permanent stations, field surveys, despite their elevated cost, persist as the reliable modality for procuring coordinates with centimeter-level accuracy.
Abstract: Geodetic sciences play a pivotal role in catalyzing socio-economic development and exerting a profound influence on our daily lives. These sciences proffer a multitude of methodologies for obtaining geographic coordinates of land parcels, thereby posing a precision challenge that is integral to effective land management and dispute mitigation. In a...
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Case Report
Feasibility Study for Wind Data Analysis Across Nigeria's 36 States and the Federal Capital Territory, Abuja
Issue:
Volume 10, Issue 3, September 2025
Pages:
141-157
Received:
16 August 2025
Accepted:
1 September 2025
Published:
25 September 2025
Abstract: In Nigeria, nearly 136.5 million people lack access to clean electricity, representing approximately 61.2% of the total population (According to the National Bureau of Statistics). This study presents key information on wind speed distribution across the country's 36 states, aiming to provide statistical recommendations for wind turbine deployment throughout the federation. Fifteen years of wind data and five years of hourly data from the Nigerian Meteorological Agency (NIMET) were analyzed using the standard deviation method of the Weibull distribution and GIS mapping techniques. The wind energy analysis reveals distinct wind patterns and average speeds across various regions of Nigeria, which influence the feasibility of stand-alone wind energy projects. In the Northwest region, an average wind speed of 4.2 m/s, a shape parameter (k) of 6.77, and a scale parameter (c) of 3.06 indicate moderate wind speeds with a steady distribution, particularly in states such as Sokoto and Gusau. The Northeast region exhibits an average wind speed of 3.5 m/s, with a shape parameter (k) of 5.86 and a scale parameter (c) of 2.88; some locations, like Damaturu, experience wind speeds up to 4 m/s. While the form parameter suggests relatively stable wind patterns, the Southwest region shows comparatively low wind potential, with a shape parameter (k) of 6.46, a scale parameter (c) of 2.25, and an average wind speed of 2.17 m/s. Similarly, the Southeast region has low but stable wind conditions, with an average wind speed of approximately 2.00 m/s and shape and scale parameters of 6.35 and 2.05, respectively. In conclusion, the prospects for wind energy projects appear marginally better in the Northwest and Northeast regions, especially in areas with higher wind speeds. The generally low wind speeds observed in most regions underscore the need for hybrid energy systems that integrate solar and wind power to provide a reliable and sustainable energy source.
Abstract: In Nigeria, nearly 136.5 million people lack access to clean electricity, representing approximately 61.2% of the total population (According to the National Bureau of Statistics). This study presents key information on wind speed distribution across the country's 36 states, aiming to provide statistical recommendations for wind turbine deployment ...
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Review Article
Mineralogical and Geochemical Characterization of the Zarnouski Felsic Suites, Anorogenic Damagaram-Mounio Province
Lawali Idi Chamsi*,
Nouhou Halitt,
Abdourhamane Touré Amadou
Issue:
Volume 10, Issue 3, September 2025
Pages:
158-167
Received:
28 August 2025
Accepted:
9 September 2025
Published:
25 September 2025
Abstract: The Zarnouski complex is located 80 km northeast of the Zinder pluton, in the province of Damagaram-Mounio, halfway between the more recent granites of the Aïr and those of Nigeria to the south. The aim of this study is to present the results of the mineralogical and geochemical characterisation of the Zarnouski felsic suites. It is a prime target for determining: (i) the nature of the rocks and (ii) tracing variations in the major elements controlling the mechanisms of magmatic differentiation. The methodological approach used is multidisciplinary, combining petrographic analysis, radiometric analysis and geochemistry of major elements. Two alkaline and hyperalkaline lineages are highlighted. The small elliptical Zarnouski pluton, consists of quartz-syenite [330 ± 3 Ma, (87Sr/86Sr)0 = 0.7100] cut by aegyrin-granite [302 ± 9 Ma, (87Sr/86Sr)0 = 0.7157]. The geochemical results obtained show that these rocks have high silica and alkalis contents. Indeed, using geochemical classification diagrams on rock typology coupled with calculated alkalinity indices, two magmatic lineages were highlighted. The first lineage comprises a petrographic sequence ranging from augite-syenite (K+Na: 0.30) to quartz-syenite (K+Na: 0.28) and biotite-granite, rhyolite (K+Na: 0.25), with an alkalinity index (AI) varying from 0.94 to 0.99. Hyperalkaline rocks are microsyenite (AI: 1.13; K+Na: 0.33) and riebeckite-granites (AI: 1.06 to 1.11; K+Na: 0.25-0.26). The relationship between alumina and alkalis, coupled with the decrease in CaO, FeOt and MgO, has allowed us to propose a divergent differentiation from syenite, producing an alumina-deficient fraction (riebeckite-granite) and an aluminous fraction represented by biotite-granite. The presence of Fe2+-rich ferromagnesian minerals (Fe2+/Fe3+>1) at the beginning and annite, Fe3+ [biotite-granite: (Fe2+/Fe3+)< 1] towards the end of crystallization indicates that magma influx was relatively reduced. This study suggests that the rocks studied were formed from magma that underwent significant differentiation/fractional crystallisation (DI: 81.75 to 94.76) and that alkali-rich mantle sources play a key role in their genesis. A divergent differentiation of syenite, producing an alumina-deficient fraction (riebeckite granite) and an alumina-rich fraction represented by biotite granites, is proposed for the Zarnouski rocks.
Abstract: The Zarnouski complex is located 80 km northeast of the Zinder pluton, in the province of Damagaram-Mounio, halfway between the more recent granites of the Aïr and those of Nigeria to the south. The aim of this study is to present the results of the mineralogical and geochemical characterisation of the Zarnouski felsic suites. It is a prime target ...
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