E.H. Mathews’s research while affiliated with Stellenbosch University and other places

Steel manufacturing is critical for industrial development and contributes greatly to the world’s energy consumption. A worldwide oversupply of steel has led to increased competition in the market, requiring developing countries to function on the same level as developed countries. Since energy use contributes between 20 and 40% of steel production costs, a reduction in energy consumption will result in decreased production costs, and increased competitiveness. This study therefore focuses on the development and application of an integrated approach to reduce energy costs in steel production planning. This is a new solution, as a review of existing research indicated that there is a lack of an integrated steel production planning model and application thereof on marginally profitable facilities. The key novelty lies in the integration aspect of the solution — both in terms of integrating different initiatives and different sections of such a facility. The proposed approach provides an opportunity to adapt outdated production planning methods without the use of capital, and simultaneously address resistance from personnel at these marginally profitable facilities in developing countries. The new cost model focuses on the identification, evaluation, comparison, prioritisation, implementation, and integration of steel production planning initiatives. The integration determines the effect that individual initiatives have on each other, and dynamically prioritises solutions by combining theoretically quantified benefits with practical constraints. Two initiatives were implemented on a South African facility, with an estimated cost benefit of US$0.83 million per annum (approximately R13.3 million per annum).

Frontiers requested research on how a systems approach can explore the mechanisms of cardiovascular complications in Covid-19. The focus of this paper will thus be on these detailed mechanisms. It will elucidate the integrated pathogenic pathways based on an extensive review of literature. Many severe Covid-19 cases and deaths occur in patients with chronic cardiovascular comorbidities. To help understand all the mechanisms of this interaction, Covid-19 complications were integrated into a pre-existing systems-based coronary heart disease (CHD) model. Such a complete model could not be found in literature. A fully integrative view could be valuable in identifying new pharmaceutical interventions, help understand how health factors influence Covid-19 severity and give a fully integrated explanation for the Covid-19 death spiral phenomenon seen in some patients. Covid-19 data showed that CHD hallmarks namely, Hypercoagulability, Hypercholesterolemia, Hyperglycemia/Hyperinsulinemia, Inflammation and Hypertension have an important effect on disease severity. The pathogenic pathways that Covid-19 activate in CHD were integrated into the CHD model. This fully integrated model presents a visual explanation of the mechanism of interaction between CHD and Covid-19 complications. This includes a detailed integrated explanation of the death spiral as a result of interactions between Inflammation, endothelial cell injury, Hypercoagulability and hypoxia. Additionally, the model presents the aggravation of this death spiral through the other CHD hallmarks namely, Hyperglycemia/Hyperinsulinemia, Hypercholesterolemia, and/or Hypertension. The resulting model further suggests systematically how the pathogenesis of nine health factors (stress, exercise, smoking, etc.) and seven pharmaceutical interventions (statins, salicylates, thrombin inhibitors, etc.) may either aggravate or suppress Covid-19 severity. A strong association between CHD and Covid-19 for all the investigated health factors and pharmaceutical interventions, except for β-blockers, was found. It is further discussed how the proposed model can be extended in future to do computational analysis to help assess the risk of Covid-19 in cardiovascular disease. With insight gained from this study, recommendations are made for future research in potential new pharmacotherapeutics. These recommendations could also be beneficial for cardiovascular disease, which killed five times more people in the past year than Covid-19.

The weather directly impacts ventilation systems, especially large industrial systems found in underground mines. Underground mine ventilation systems have high cost implications that add to the financial strains and uncertainties of future mining operations. In addition, the dynamic nature of underground ventilation systems makes the accurate prediction of underground conditions extremely difficult using traditional steady-state methods. Therefore, improved prediction methods of dynamic underground environmental conditions are needed to ensure cost-effective ventilation systems. This paper investigates simulating the sensitivity that underground ventilation systems have to fluctuating ambient conditions. Simulation software was applied to a case study on a gold mine in South Africa. The results showed that transient software can now be applied to entire mine ventilation systems, and can improve predicting the underground environment because of fluctuating ambient conditions.

The South African energy crisis harms the economy. Tax incentives are intended to help, but rules for incentives must be understood by all stakeholders for taxpayers to be encouraged to invest. Section 12L (S12L) is relatively new legislation that allows a tax deduction for verified year-on-year energy efficiency savings in South Africa. Concurrent benefits are excluded from this tax incentive, to prevent a double reward for the same activity. Although the prevention of double benefits is commonly addressed in the field of measurement and verification (M&V), non-technical guidelines are not available. This is a critical shortcoming since multiple professions (tax, audit and legal) need to understand the technical M&V requirements of S12L. This study reviews the current legislation and interpretations of concurrent benefits in terms of S12L. It shows that multiple energy-related incentives are utilised by industries and that, therefore, it must be determined if different programmes overlap, so as to create concurrent benefits with S12L. It is then critical to correctly apply M&V practice to ensure exclusion of concurrent benefits. This study also provides a simplified methodology to evaluate concurrency, based on the S12L regulatory requirements and standard M&V methods. Three case studies show how concurrency can occur and how M&V practice is applied to exclude double benefits. The test for concurrency is shown to reduce to the following question: Is the same energy saving funded twice? The tests must be done to ensure no double benefit occurs.

Many coal-fired power plants (CFPPs) face special challenges such as ageing infrastructure, neglected equipment maintenance, and reduced funding. To assist with cost-effective decision-making, an integrated, semi-empirical thermohydraulic simulation model for a CFPP was developed. The model was calibrated with actual measurements to ensure accurate predictive maintenance schedules. This model was then integrated with economics and maintenance models. Such a fully comprehensive investigation could not be found in literature. As condensers have an important impact on maximum generation output, the simulation model was used to provide new insight into the cost implications associated with delayed or premature maintenance of a condenser. The results of the thermohydraulic simulation were verified against measured plant data and was within 5% error. The model was then utilised to determine the most efficient predictive maintenance schedule for the condensers of a 60 MW and 350 MW unit. Results showed that, when applying the new predictive maintenance schedule, considerable savings can be realised. When extrapolated to the entire South African power utility fleet, the potential savings are over R900 million¹ (USD 63 million) per annum. The most important contribution of this paper is that the approach described here can be used to investigate the effect on plant performance and economic viability of any change to any component in any CFPP in a truly industrial scenario.

The rapid growth and expansion of the Internet, as well as technical advances in the area of sensor technology, allow for the interconnection of physical objects for the purpose of achieving collective goals, which paves the way for the Fourth Industrial Revolution. The Industry 4.0 paradigm is a relatively new concept that still requires detailed investigation and discussion. Standards, technologies, and overall guidelines need to be presented; thus this review paper aims to address key questions to provide some clarity on navigating the tide of Industry 4.0. The key enabling technologies, and the extent to which these technologies can be applied in industry to achieve the fundamental goals of Industry 4.0, are presented and discussed. Current challenges that hinder Industry 4.0 adoption in the South African mining sector are discussed, and a short discussion on the way forward is presented. In brief, this article aims to present a detailed roadmap for the implementation of Industry 4.0 methods in the South African mining sector. From the literature, a digital framework and toolbox have been compiled to serve as a roadmap for the way forward in successful Industry 4.0 adoption. The proposed framework and toolbox are presented, with a theoretical case study.

The Carbon Tax on greenhouse gas (GHG) emissions, set to help transition South Africa towards a low-carbon economy, induces several uncertainties. Liable parties, as well as national bodies (e.g. the South African Revenue Service, SARS), are at risk due to the lack of published guidance. Such uncertainties and risks can be managed or mitigated by introducing assurance mechanisms focused on the different key structures within the process. This paper presents an assurance-centered reporting framework developed to document and support all decisions affecting the values submitted to SARS. The framework merges several international and national best practice auditing assurance standards together with the technical and legal requirements of carbon tax. Assurance is thereby provided by a transparent and traceable process presented in such a manner that it can be easily audited by independent parties. The developed framework assures the (1) dataset constructed and used in (2) GHG quantification methods to (3) report the results for industrial case studies. Several practical assurance mechanisms are identified and applied within each structure to address the associated uncertainties. Aggregating these mechanisms ultimately provides holistic assured results that are likely to pass all levels of scrutiny.

Data quality is fundamental in quantifying and reporting industrial-scale energy consumption. A narrow focus on isolated aspects of data quality can lead to inconsistent levels of rigour in dataset evaluation and selection. In this paper, a data quality framework is therefore developed to holistically evaluate if a dataset provides a fair representation of the underlying energy system. The developed framework is based on three core aspects of data quality, namely accuracy, integrity and relevance. The framework emphasizes the use of traceability pathways to test data integrity and relevance. Quantitative and qualitative comparisons are proposed as practical options to test and evaluate multiple data sources. Based on the framework, a dataset can either be validated for reporting purposes or discarded based on the lack of data quality assurance. The framework is applied to six isolated case studies. The results indicate that discrepancies relating to data integrity and relevance can significantly impact reporting functions. If left unchecked, these quantifiable discrepancies could result in data-based errors amounting to R1240 million (at R0.95/kWh) if viewed within the context of the Section 12L energy efficiency tax incentive. This highlights the role of holistic data quality evaluation to avoid propagation of erroneous data into reporting functions.