Research Articles (Civil Engineering)

Permanent URI for this collectionhttp://hdl.handle.net/2263/1701

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Performance of low-cost fiber optic cables as leak detection sensors for water pipelines in unsaturated soil
(Elsevier, 2024) Jacobsz, Schalk Willem; sw.jacobsz@up.ac.za
Large volumes of potable water are lost from leaks in water distribution systems around the world. Such leaks may go undetected for a long time. A passive means of leak detection can be implemented by burying a suitable fiber optic cable in the pipe trench with water distribution pipes when they are installed. Water leaking from pipes into the ground results in a temperature change at the leak location. Leaks into unsaturated soil also cause changes in the bulk density and strength of the soil, resulting in significant soil deformation. Brillouin Frequency Shift (BFS) in optical fibers is sensitive to changes in both temperature and mechanical strain, allowing fiber optic cables to act as efficient leak detection sensors. Purpose-made fiber optic cables may be expensive, but telecommunication grade cables generally have a low cost and are readily available around the world. This paper investigates the performance of five different fiber optic cables, including communication grade fiber optic cables, to act as leak detection sensors in unsaturated ground. It was found that the most efficient leak detection sensors are flexible tight-buffered fiber optic cables.
New predictive models for the computation of reinforced concrete columns shear strength
(MDPI, 2025-01) Ioannou, Anthos I.; Galbraith, David; Bakas, Nikolaos; Markou, George; Bellos, John; u19027436@tuks.co.za
The assessment methods for estimating the behavior of the complex mechanics of reinforced concrete (RC) structural elements were primarily based on experimental investigation, followed by the collective evaluation of experimental databases from the available literature. There is still a lot of uncertainty in relation to the strength and deformability criteria that have been derived from tests due to the differences in the experimental test setups of the individual research studies that are being fed into the databases used to derive predictive models. This research work focuses on structural elements that exhibit pronounced strength degradation with plastic deformation and brittle failure characteristics. The study’s focus is on evaluating existing models that predict the shear strength of RC columns, which take into account important factors including the structural element’s ductility and axial load, as well as the contributions of specific resistance mechanisms like that of concrete, transverse, and longitudinal reinforcement. Significantly improved predictive models are proposed herein through the implementation of machine learning (ML) algorithms on refined datasets. Three ML models, LREGR, POLYREG-HYT, and XGBoost-HYT-CV, were used to develop different predictive models that were able to compute the shear strength of RC columns. According to the numerical findings, POLYREG-HYT- and XGBoost-HYT-CV-derived models outperformed other ML models in predicting the shear strength of rectangular RC columns with the correlation coefficient having a value R greater than 99% and minimal errors. It was also found that the newly proposed predictive model derived a 2-fold improvement in terms of the correlation coefficient compared to the best available equation in international literature.
Extended monitoring of earth pressures behind a 90 m integral bridge
(American Society of Civil Engineers, 2025-04) Morley, Douglas G.; Skorpen, Sarah Anne; Adendorff, Jurie F.; Kearsley, Elsabe P.; Jacobsz, Schalk Willem; Madabhushi, Gopal S.P.; sw.jacobsz@up.ac.za
Despite the popularity of integral bridges, long-term field data are required to better understand the soil strain ratcheting behavior that occurs with thermal cycles. This work presents over 6 years of field data collected from the Van Zylspruit Bridge, a 90-m-long integral bridge in South Africa. Sensors recording temperature, abutment movement, earth pressure, and soil water content were used to understand bridge behavior. Results show only a small increase in earth pressure over time, far less than that expected from physical modeling. One explanation for this may be the smaller-than-expected thermal movements recorded. Further possibilities were investigated through the small-scale modeling of a 1.5-m RC abutment, from which it was found that the starting position of the abutment and concrete drying shrinkage are both unlikely to contribute to the pressure buildup, while soil water content may play a part through the suctions generated. Based on these findings, the strain ratcheting of earth pressures in the field appears to be less severe than modeling efforts would suggest.
Use of Rayleigh and Love waves in seismic surface wave testing
(South African Institution of Civil Engineering, 2025-03) Islam, Mohammed Shariful; Heymann, Gerhard; gerhard.heymann@up.ac.za
Seismic surface wave tests are widely used in geotechnical engineering due to their non- invasive and cost-effective approach in obtaining important soil parameters such as the small strain shear modulus (G 0) by measuring shear wave velocity (Vs). While conventional tests focus on measuring Rayleigh waves due to their easy generation and detection in the field, Love waves are often overlooked due to challenges in generating and detecting them. This study investigated the utilisation of both Rayleigh and Love waves to obtain shear wave velocity profiles using experimental and synthetic data. Two methods were explored for generating Love waves – using a horizontal harmonic source, and also employing a horizontal impact source. Signal processing code was developed to analyse the surface wave signals and to calculate dispersion data. By conducting discrete and joint inversions with the experimental and synthetic dispersion data, the variation in the shear wave velocity profiles was evaluated. The findings demonstrated that employing both Rayleigh and Love waves in joint inversion reduced the variation in the shear wave velocity profile compared to using Rayleigh waves alone, but only when Love wave signals with low noise levels were available.
New predictive models for the computation of reinforced concrete columns shear strength
(MDPI, 2024-12-24) Ioannou, Anthos I.; Galbraith, David; Bakas, Nikolaos; Markou, George; Bellos, John; u19027436@tuks.co.za
The assessment methods for estimating the behavior of the complex mechanics of reinforced concrete (RC) structural elements were primarily based on experimental investigation, followed by the collective evaluation of experimental databases from the available literature. There is still a lot of uncertainty in relation to the strength and deformability criteria that have been derived from tests due to the differences in the experimental test setups of the individual research studies that are being fed into the databases used to derive predictive models. This research work focuses on structural elements that exhibit pronounced strength degradation with plastic deformation and brittle failure characteristics. The study’s focus is on evaluating existing models that predict the shear strength of RC columns, which take into account important factors including the structural element’s ductility and axial load, as well as the contributions of specific resistance mechanisms like that of concrete, transverse, and longitudinal reinforcement. Significantly improved predictive models are proposed herein through the implementation of machine learning (ML) algorithms on refined datasets. Three ML models, LREGR, POLYREG-HYT, and XGBoost- HYT-CV, were used to develop different predictive models that were able to compute the shear strength of RC columns. According to the numerical findings, POLYREG-HYT- and XGBoost-HYT-CV-derived models outperformed other ML models in predicting the shear strength of rectangular RC columns with the correlation coefficient having a value R greater than 99% and minimal errors. It was also found that the newly proposed predictive model derived a 2-fold improvement in terms of the correlation coefficient compared to the best available equation in international literature.
Short term ageing of asphalt binder in thin asphalt layers
(Elsevier, 2024-03) O'Connell, Johan; Maina, J.W. (James); Steyn, Wynand Jacobus Van der Merwe
The effects of ageing on pavement performance are significant, particularly in terms of fatigue cracking. South Africa has the 10th longest road network in the world, requiring innovative approaches to road construction due to severe budget constraints. Innovative solutions such as thin asphalt concrete layers for surfacing, result in unique ageing rates of the layers, which, in general, have a higher incidence of fatigue cracking than, for example, thicker asphalt concrete layers used in other parts of the world. The objective of this paper is to evaluate how ageing mechanisms affect various asphalt binder properties, and whether they affect them to the same extent or not. Furthermore, the objective of the paper is also to determine the accuracy of the Rolling Thin Film Oven Test (RTFOT) in simulating short-term ageing in the field. The RTFOT provides a relatively good indication of short-term ageing, according to this multi-decade ageing study, and the effect on the asphalt binder properties used as ageing indices depends on the specific property chosen for comparison before and after ageing.
Is first mile behaviour similar to last mile behaviour? A case study on a rapid rail system in South Africa
(Routledge, 2025) Watts, Daniel; Venter, C.J. (Christoffel Jacobus); Hayes, Gary; christo.venter@up.ac.za
First and last mile behaviours to and from public transport are rarely studied together, limiting insights into preference differences between access and egress trips. This paper addresses this gap through a case study of an urban rapid rail system in South Africa. Data are from an online stated preference survey conducted amongst train passengers, in which mode choices for the access and egress trips during the morning peak are captured. Nested logit choice models for access and egress trips differ both in nesting structure and the relative size of coefficients. Values of travel and walk time are three times larger for the egress than for the access trip, suggesting that time-saving strategies are more important on the last mile than the first mile part of a commute trip. We explore the impacts of these differences by modelling hypothetical improvement scenarios to access and egress conditions.
Technology foresight for the South African road transport sector by 2035
(AOSIS, 2024-08-30) Rust, Frederik C.; Sampson, Leslie R.; Cachia, Adriana A.; Verhaeghe, Benoit M.J.A.; Fourie, Helena S.; Smit, Michelle A.; Hoffman, Alwyn; Steyn, Wynand Jacobus Van der Merwe; Venter, Karien; Lefophane, Samuel
BACKGROUND : Foresight can be used to define futuristic orientated research and development (R&D) that is required to position the road transport sector for a challenging future. OBJECTIVES : To develop a set of futuristic R&D projects that could be added to a balanced SANRAL R&D portfolio to position SANRAL and the transport sector for the future on a 15-year horizon. METHOD : Inputs into and ranking of the drivers, trends and technologies that will impact the transport sector were obtained from interviews with eminent thinkers, participants in workshops and a survey leading to five potential future scenarios. Qualitative and quantitative data analysis yielded several key solutions (KSs) and key interventions (KIs) to position the sector. This was complemented with the novel use of technology trees to analyse the linkages between new and existing knowledge and to identify gaps in knowledge and subsequently the identification of key R&D opportunities. RESULTS : Through backcasting from the desired future scenario as well as using 412 stakeholder inputs, 12 KSs and 61 KIs were defined and ranked. The top 30, most futuristic KIs were analysed using 18 hierarchical technology trees to define R&D opportunities. CONCLUSION : The analysis emphasised the importance of new technologies such as data science, machine learning, smart transport and advanced materials to position the sector. CONTRIBUTION : The use of a novel, structured technology foresight approach that utilises scenario development combined with hierarchical technology trees was demonstrated. To position the road transport sector for a challenging future, 12 new thematic KSs and 61 KIs were developed.
Application of laterite-based geopolymer mortar for masonry bedding
(Trans Tech, 2024-12) Nuru, Zeyneb Kemal; Kearsley, Elsabe P.; Elsaigh, Walied A.; elsabe.kearsley@up.ac.za
This paper explores the production and properties of geopolymer cement mortar using laterite soils. The aim was to evaluate the laterite-based geopolymer mortars for masonry bedding applications. The testing programme encompassed three series of mixes tested to determine setting times, flowability, flexural strength and compressive strength. Two types of sands were used including standard sand and natural sand. The effect of water-to-laterite ratios, activating agent concentration, and cement-to-sand ratio were established. The properties of standard cement paste, and mortar were used as a reference. The study found that geopolymer mortar made from laterite meets the requirements for masonry bedding.
Life cycle assessment of an avocado : grown in South Africa-enjoyed in Europe
(Springer, 2024-11) Blaauw, Sheldon Alfred; Broekman, Andre; Maina, J.W. (James); Steyn, Wynand Jacobus Van der Merwe; Haddad, William A.
Please read abstract in article.
Big data generation and comparative analysis of machine learning models in predicting the fundamental period of steel structures considering soil-structure interaction
(World Scientific Publishing, 2024-11) Van der Westhuizen, Ashley Megan; Bakas, Nikolaos P.; Markou, George; george.markou@up.ac.za
The computing of the fundamental period of structures during seismic design is well documented in design codes but is mainly dependent on the height of the structure, which is considered to be the most influential parameter. It is, however, important to consider a phenomenon called the soil–structure interaction (SSI), as this has been found to have a detrimental effect, especially for buildings founded on soft soils. A pilot research project foresaw the use of machine learning (ML) algorithms trained on relatively limited datasets for the development of a more accurate and objective fundamental period formula. Therefore, a dataset that consists of 98,308 fundamental period data points was created through the use of a High-Performance Computer (HPC), which is the largest dataset of its kind. The HPC results were then used to train, test, and validate different ML algorithms. It was found that XGBoost-HYT-CV with hyperparameter tuning performed the best with a correlation of 99.99% and a mean average percentage error (MAPE) of 0.5%. Furthermore, the XGBoost-HYT-CV model outperformed all under-study ML models when using an additional dataset that consisted of out-of-sample building geometries and soil properties, with a resulting MAPE of 9%. Finally, irregular buildings were also used to test the performance of the proposed predictive models.
Using machine learning algorithms to develop a predictive model for computing the maximum deflection of horizontally curved steel I-beams
(MDPI, 2024-08) Ababu, Elvis; Markou, George; Skorpen, Sarah Anne; george.markou@up.ac.za
Horizontally curved steel I-beams exhibit a complicated mechanical response as they experience a combination of bending, shear, and torsion, which varies based on the geometry of the beam at hand. The behaviour of these beams is therefore quite difficult to predict, as they can fail due to either flexure, shear, torsion, lateral torsional buckling, or a combination of these types of failure. This therefore necessitates the usage of complicated nonlinear analyses in order to accurately model their behaviour. Currently, little guidance is provided by international design standards in consideration of the serviceability limit states of horizontally curved steel I-beams. In this research, an experimentally validated dataset was created and was used to train numerous machine learning (ML) algorithms for predicting the midspan deflection at failure as well as the failure load of numerous horizontally curved steel I-beams. According to the experimental and numerical investigation, the deep artificial neural network model was found to be the most accurate when used to predict the validation dataset, where a mean absolute error of 6.4 mm (16.20%) was observed. This accuracy far surpassed that of Castigliano’s second theorem, where the mean absolute error was found to be equal to 49.84 mm (126%). The deep artificial neural network was also capable of estimating the failure load with a mean absolute error of 30.43 kN (22.42%). This predictive model, which is the first of its kind in the international literature, can be used by professional engineers for the design of curved steel I-beams since it is currently the most accurate model ever developed.
Studying transfers in informal transport networks using volunteered GPS data
(Elsevier, 2025-04) Ankunda, G.; Venter, C.J. (Christoffel Jacobus); u21742040@tuks.co.za
Multimodal integration is an important issue in public transport systems due to its influence on both passenger experience and overall network efficiency. In most countries in the global South, achieving integration is particularly problematic because of the informal nature of most public transport. Decentralised service planning and demand responsiveness lead to often uncoordinated, highly variable service patterns, which are not optimised from a passenger perspective. Efforts to promote integration are also hampered by a lack of planning data on routes, service frequencies, and transfer locations. This research asks whether GPS data supplied by passengers as they move through the network can be used to help form a better understanding of the extent and quality of the transfer experience. The data was collected in the City of Tshwane, South Africa, among informal minibus-taxi passengers. Post-processing involved the use of a machine learning algorithm to identify in-vehicle, wait and walk segments, which were used to identify transfers between one vehicle and another. The results showed that many transfers are spatially efficient with short walk and wait times, but that a minority of transferring passengers may experience very long transfers. Transfers encompass a diverse range of behaviours including pacing, shopping and browsing, and typically involve much more walking than waiting. Transfers also occur across a wide range of locations, but tend to be concentrated in certain nodes and along street segments. Strategies to improve transfer facilities as well as general walkability might be targeted at such locations. The study demonstrated that volunteered GPS data is a promising source of information to help planners understand the transfer experience in multimodal networks in data-poor environments.
Active control of properties of fresh and hardening concrete
(RILEM Technical Letters, 2024-09) De Schutter, Geert; Abidi, Imene; Korda, Eleni; Boshoff, W.P. (Billy); Olonade, Kolawole Adisa; Snoeck, Didier; Muthukrishnan, Shravan; Zhang, Yiyuan; Tao, Yaxin; Ghodke, Swapnil Balasaheb; Mohan, Manu Kurungod; Yardimci, Mert Yücel; Jiao, Dengwu; Sanjayan, Jay
Concrete mixtures have an optimized mix design in view of attaining desired properties. However, after mixing, during further processing, it is typically not possible to further adjust the performance of the fresh and hardening concrete. A new and emerging approach is to actively control the concrete properties by means of responsive particles or polymers triggered by an externally applied signal. Active control of properties of concrete refers to the concept of on- demand changes of one or more properties of the concrete after mixing by triggering a response to one or more of the constituents using a specific trigger signal (e.g. thermal, chemical, electrical, magnetic...). The on-demand control of properties can focus on the processing stage (including e.g. pumping, casting, 3D printing), the curing and hardening stage (including e.g. control of capillary pressure, shrinkage, setting, and hardening) and even on the hardened stage during service life (e.g. active corrosion control, active crack healing...). Addressing specific obstacles in cementitious environments, ensuring responsive material stability, controlling signal applicability, cost, logistics, and on-site safety is crucial for successful implementation. A RILEM technical committee has been initiated in 2023, working on the concept of Active Control of Properties of Concrete (RILEM TC 317-ACP). The committee will focus on active control of properties of fresh and hardening concrete. This paper gives a short introduction to scope and activities of TC 317-ACP.
Improvements to the hydraulic performance of culverts under inlet control conditions by optimisation of inlet characteristics
(MDPI, 2024-06) De Jager, Leon; Van Dijk, Marco
With renewed interest in the optimisation of the hydraulic performance of new and existing culverts, particularly relevant to South Africa’s evolving road network and anticipated climate-induced rainfall changes, this research investigated the benefit of angled wingwall and headwall combinations and considered the installation of a ventilation device in order to improve culvert performances. Through experimental modelling at the University of Pretoria Water Laboratory, the angled wingwall and headwall combinations demonstrated significant flow improvements compared to square inlets. It was also demonstrated that a ventilation device could cause flow through culverts to flow under inlet control conditions where it would otherwise have flowed under outlet control conditions. Additionally, the study proposes design coefficient adjustments for square inlet culverts operating under inlet control conditions. The proposed improvements can be applied during design stages, but the findings also propose prefabricated inlet elements as cost-effective solutions for existing culverts, thereby facilitating quick upgrades without the need for lengthy road closures while potentially enabling benefits for pedestrian traffic. Ultimately, this study underscores the potential of innovative and novel design modifications to enhance culvert performance, offering sustainable and economical alternatives to conventional replacement practices while advancing hydraulic engineering resilience in response to evolving infrastructural and environmental demands.
Difficulties monitoring short-term ageing in thin surfacing layers using asphalt concrete
(Elsevier, 2024-12) O'Connell, Johan; Steyn, Wynand Jacobus Van der Merwe; Maina, J.W. (James); james.maina@up.ac.za
Ageing has a profound effect on pavement performance, especially regarding cracking. Due to budgetary constraints, South Africa has pioneered the use of thin asphalt concrete layers. The research described in this paper is based on a short-term ageing study in South Africa, using data generated over a period of 6 years. During this time, polymer modified asphalt binders were increasingly employed in road construction, and rheological analyses from the dynamic shear rheometer were increasingly used to characterize asphalt binders. This study compared the complex shear modulus to the softening point as an ageing index property used to monitor the extent of short-term ageing of the recovered asphalt binder from newly laid asphalt concrete. The asphalt binder properties from 20 constructions sites were evaluated, whereby the recovered binder from the site shortly after construction was evaluated against the asphalt binder properties obtained in the laboratory after the rolling thin film oven treatment. The results indicate that the recovery process leads to a deterioration in the repeatability for the complex shear moduli obtained from recovered asphalt binders. The lower repeatability prevents meaningful conclusions from being made. Furthermore, the work shows that although the Rolling Thin Film Oven Test may be a good predictor of short-term ageing when using softening point as an ageing index property, it is only valid for unmodified asphalt binders in South Africa.
Spalling of concrete in fire-an overview and local relevance
(South African Institution of Civil Engineering, 2023-06) Van der Merwe, Johann E.; vandermerwe.johann@up.ac.za
Concrete has traditionally been considered as a material with favourable fire resistance. The development of modern concretes with low permeability has, however, resulted in the increased occurrence of spalling when exposed to fire. Recent fire damage in South Africa during the riots in July 2021 resulted in such damage. This paper presents an overview of explosive spalling of concrete in fire, recent local observations, and developments in the field. It is shown that various (often interrelated) factors influence the susceptibility of concrete to spall in fire, and that much research is still needed to fully understand the phenomenon and, specifically, how to accurately predict its occurrence. Recent observations in South Africa support conclusions in the literature that, as an accidental loading case or as life-safety performance criteria, overall structural integrity is rarely compromised. However, as the use of higher concrete grades increases, the relevance of this risk should be considered by practising engineers.
Experimental comparison of active seismic surface wave tests on shallow and deep bedrock sites
(South African Institution of Civil Engineering, 2023-09) Ntaote, Mosito; Heymann, Gerhard; gerhard.heymann@up.ac.za
Active seismic surface wave tests are tests during which signals are generated by artificial sources such as sledgehammers, drop weights and fixed or variable frequency shakers. A number of active seismic surface wave tests have become popular in the geotechnical industry. Interestingly, different surface wave tests are popular in different regions of the world, presumably because the tests require different equipment, expertise and numerical analysis techniques. Few studies have been done to compare seismic surface wave tests directly. This study investigated the performance of three active seismic surface wave tests, namely the spectral analysis of surface waves (SASW), multi-channel analysis of surface waves (MASW) and continuous surface wave (CSW) tests. This paper reports the performance of the three tests with regard to repeatability, susceptibility to near-field effects, and maximum and minimum measurement depths at both a shallow and a deep bedrock site.
Advanced numerical modelling of the nonlinear mechanical behaviour of a laterally loaded pile embedded in stiff unsaturated clay
(South African Institution of Civil Engineering, 2023-06) Braun, Kirsten Theresia; Bakas, N.; Markou, George; Jacobsz, Schalk Willem; sw.jacobsz@up.ac.za
Capturing and understanding the ultimate limit state behaviour of reinforced concrete piles embedded in soil requires the use of advanced tools or the performance of expensive tests. An experiment was performed where reinforced concrete piles embedded in a stiff unsaturated clay profile were load-tested on-site. However, even though in-situ experiments can provide engineers with valuable insight, their cost and time limitations come with restrictions, especially when dealing with a parametric investigation on the soil’s material properties, the size of the piles, or the piles’ material properties. The objective of this research work was to numerically model the nonlinear mechanical behaviour of laterally loaded full-scale piles through detailed 3D modelling, and perform an in-depth parametric investigation to provide answers to unknown factors that the actual physical experiment could not answer. Furthermore, this work serves as a pilot project that will be used to pave the way in developing multiple soilstructure interaction models that will be used to generate a dataset that helps the creation of predictive models through machine learning algorithms. For the needs of this research work, the reinforced concrete piles were discretised with 8-noded isoparametric hexahedral elements that accounted for cracking through the smeared crack approach. Steel reinforcement bars and stirrups were simulated as embedded rebar elements, while the soil domain was also discretised through 8-noded hexahedral elements. Most of the required material properties assumed during the nonlinear analyses were defined according to relevant laboratory experiments. According to the numerical investigation, it was found that the proposed numerical model has the ability to reproduce the experimental results with high accuracy, while providing in-depth insight on the failure mechanisms for both the soil and reinforced concrete domains.
Centrifuge modelling of ultra-thin high strength steel fibre reinforced concrete pavements
(ICE Publishing, 2023-01) Smit, Martha S.; Kearsley, Elsabe P.; phia.smit@up.ac.za
Ultra-thin continuously reinforced concrete pavement (UTCRCP) is an innovative pavement type that consists of a 50 mm high strength steel fibre reinforced concrete (HS-SFRC) layer overlain on a pavement substructure. The thickness results in a flexural stiffness significantly smaller than for conventional concrete pavements. In this paper, the conceptual understanding of the response of UTCRCP to traffic loading was investigated using centrifuge modelling. Simplified pavement models were subjected to a bidirectional moving axle load. The results indicated that axle loading, and not single wheel loading, should be used to investigate the response of UTCRCP as there is significant interaction in substructure deformation caused by the wheels on the ends of an axle. Due to the flexural toughness of the highly reinforced concrete layer, a gap forms between the ultra-thin HS-SFRC overlay and its substructure. Brittle, cemented bases between the HS-SFRC overlay and subgrade should be used with caution, as the flexible nature of the layers above and below the stabilised layer may result in rapid degeneration of the brittle layer.

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