Falling film evaporation over heated vertical surfaces is a well-established heat and mass transfer mechanism with applications in evaporators, thermal management systems, desalination units, and chemical process equipment. While numerous experimental and numerical studies have addressed this configuration, further high-resolution experimental data remain necessary to improve the understanding of local thermal behavior and to support the validation of predictive models. The present work provides a detailed experimental investigation of heat transfer and evaporation characteristics of a falling water film flowing over a vertically oriented plate subjected to a uniform heat flux.

The experimental setup is based on a metallic vertical plate of practical dimensions, uniformly heated by a copper heating element coated with a silicone layer to ensure homogeneous heat flux distribution. A distinctive feature of this study lies in the high spatial resolution of surface temperature measurements, achieved using an array of 32 negative temperature coefficient (NTC) thermistors distributed along the plate. This measurement approach enables precise monitoring of local temperature variations associated with film thinning, flow development, and evaporation processes. The system is carefully insulated, and heat losses from the rear surface and plate edges are minimized to ensure that the supplied thermal power is predominantly transferred to the liquid film.

Experiments are conducted for a range of liquid mass flow rates and imposed heat flux densities representative of practical operating conditions. The results demonstrate that increasing the imposed heat flux density significantly intensifies the evaporation process. In particular, at an imposed heat flux density of q = 2200 W·m⁻², the evaporation efficiency of the system reaches 54% for a liquid mass flow rate of Γ₀ = 2 kg·h⁻¹·m⁻¹, while it decreases to 39% when the mass flow rate is increased to Γ₀ = 3 kg·h⁻¹·m⁻¹. These quantitative results clearly indicate that lower mass flow rates promote thinner liquid films, leading to enhanced heat transfer and higher evaporation efficiency. Furthermore, the combined effect of low mass flow rates and high heat flux densities results in a substantial improvement in the overall thermal and evaporative performance of the system.

The originality of this work resides in the combination of a well-controlled uniform heat flux boundary condition with high-resolution surface temperature measurements over a plate of practical dimensions, providing reliable experimental data that remain limited in the existing literature. The findings offer new insights into local heat transfer and evaporation mechanisms in falling film flows and provide valuable reference data for the design, optimization, and validation of thermal systems and numerical models involving falling film evaporation.

High-temperature thermal storage and material processing applications demand efficient solar energy conversion with minimal thermal losses. Traditional concentrated solar power (CSP) receiver designs suffer from relatively large surface areas with significant convective and radiative losses, limiting practical operating temperatures and system scalability. This work presents a novel concentrated solar thermal (CST) architecture integrating a one-meter diameter PMMA Fresnel lens with an optical light pipe-based receiver, designed to achieve high concentration ratios while minimizing receiver surface area and associated thermal losses.

The system design is for high concentration ratios, in the order of 1000×, enabling large focal flux densities in the order of MW/m² and receiver temperatures exceeding 1000°C. The Fresnel lens, with a 1000 mm diameter aperture and over 80% optical efficiency, focuses incident solar radiation onto a compact coupling area (20 mm diameter), substantially reducing surface area-dependent thermal losses compared to lower-concentration systems, such as traditional parabolic troughs, and providing advantages over receiver designs susceptible to high convective and radiation losses.

The light pipe functions as an integrated thermal transport and energy storage medium, enabling enhanced energy conversion and control for both instantaneous thermal processes (material heating, melting, sintering) and sensible/latent heat storage for thermal buffering. The compact receiver geometry facilitates integration with high-temperature thermal storage materials, creating a unified thermal processing and storage system.

Performance analysis includes optical characterization of the Fresnel lens and light pipe coupling, as well as thermocouple-based temperature measurements to verify receiver heat transfer. Preliminary experimental results demonstrate the feasibility of achieving high temperature processing or storage under optimal operating conditions, with potential for further improvement through receiver optimization and system refinement.

This architecture offers significant scalability advantages through modular lens arrays and cost reduction potential via polymer Fresnel lens mass production, positioning it as a viable pathway for small-to-medium scale CSP applications where compact, high-temperature performance is commercially critical.

Packed rock-bed thermal energy storage (TES) systems represent a robust and economically attractive solution for large-scale solar energy storage, enabling enhanced efficiency, dispatchability, and operational flexibility of solar thermal power plants. This study presents an in-depth computational fluid dynamics (CFD) investigation of an air–rock packed-bed TES system, in which air is used as the heat transfer fluid (HTF). A two-phase local thermal non-equilibrium (LTNE) model is implemented within a porous media framework, with distinct energy conservation equations solved for the fluid and solid phases and interphase convective heat transfer explicitly modeled through appropriate closure correlations. The governing mass, momentum, and energy equations are numerically solved using a finite-volume approach and rigorously validated against experimental measurements reported in the literature. A systematic parametric study is performed to evaluate the influence of rock particle diameter on flow distribution, interphase heat transfer coefficients, pressure drop, thermocline evolution, and global storage performance during charging and discharging processes. The results demonstrate that particle size exerts a first-order control on the coupled thermal–hydraulic behavior of the packed bed. Specifically, smaller particle diameters significantly increase the specific surface area and enhance interphase convective heat transfer, resulting in steeper axial temperature gradients, thinner and more stable thermoclines, faster thermal front propagation, and improved utilization of the storage volume. These effects lead to higher energy storage capacity, increased charging effectiveness, and improved thermal efficiency; however, they are accompanied by a marked increase in pressure losses and pumping power requirements due to reduced bed permeability and higher flow resistance. In contrast, larger particle diameters promote higher bed permeability and more uniform velocity fields, thereby substantially reducing pressure drop and pumping energy consumption, but they exhibit lower heat transfer coefficients, delayed solid-phase thermal response, increased thermal dispersion, and broader temperature fronts, which degrade thermal stratification and limit effective energy recovery. The analysis further reveals that the optimal particle size represents a compromise between maximizing thermal performance and minimizing hydraulic losses, and that this trade-off becomes increasingly critical at higher operating temperatures and mass flow rates. Overall, the results provide detailed physical insight into the role of particle size in thermal and hydraulic performance and offer valuable CFD-based guidelines for the optimal design and scaling of packed-bed thermal energy storage systems for solar thermal applications.

Extractive Heterogeneous Azeotropic Distillation (EHAD) is a separation technique designed for non-ideal mixtures exhibiting azeotropic behaviour, capable of achieving separations that are difficult or impossible to achieve with conventional distillation. Unlike conventional extractive distillation, which typically requires external entrainers, the distinguishing feature of this study is the exclusive use of water as an auto-entrainer, eliminating the need for additional chemicals, simplifying operational procedures, and enhancing the sustainability of the process. A defining characteristic of EHAD is the relatively small temperature difference between the top and bottom of the distillation column. This narrow thermal profile governs heat and mass transfer, directly influences entropy generation, and affects overall thermodynamic efficiency, while providing a suitable basis for energy integration and process intensification.

The applicability and performance of EHAD are investigated through a case study involving the separation and recycling of a quaternary mixture of water, ethanol, ethyl acetate, and methyl ethyl ketone from the waste stream of a printing firm, representing a complex system with multiple azeotropes. A rigorous process simulation is conducted using Aspen modelling software in conjunction with detailed entropy generation and exergy analyses to evaluate thermodynamic performance, identify inefficiencies within the configurations, and quantify losses throughout the process. Process-intensification strategies, including heat integration and heat-pump coupling, are explored to reduce energy consumption and minimize thermodynamic irreversibilities. Entropy generation analysis is used to determine dominant sources of energy degradation, while exergy analysis quantifies thermodynamic losses and allows for the calculation of exergy efficiency across different configurations.

Results indicate that energy integration reduces the total energy demand by approximately 57% compared to non-integrated operation, significantly lowering both entropy generation and exergy destruction. The overall exergy efficiency of the integrated EHAD process reaches 35%, demonstrating the thermodynamic advantages of the approach. The findings highlight that using water as an auto-entrainer enables EHAD to achieve energy-efficient, thermodynamically optimized separation of complex azeotropic mixtures, offering strong potential for sustainable industrial applications in the chemical and pharmaceutical sectors.

Decarbonising the built environment has emerged as a critical pathway for mitigating climate change impacts, particularly in developing economies with rapidly growing construction activities. Despite the availability of diverse decarbonisation strategies, their effective implementation within the architecture, engineering and construction (AEC) sector remains uneven and insufficiently understood. This study aims to determine the strategic approaches for promoting the implementation of building decarbonisation initiatives in South Africa, drawing on descriptive evidence from built environment professionals. A descriptive research design was adopted, utilising structured questionnaire data collected from professionals across the AEC disciplines. Descriptive statistical techniques, including frequency distributions and mean score rankings, were employed to examine construction professionals’ perceptions of key strategic measures that can enhance the uptake of building decarbonisation practices. The findings indicate that ease of access to green financing options, implementing energy efficiency upgrades, promoting the use of green rating tools, using building energy management systems, and raising public awareness are perceived as the most effective strategies for accelerating building decarbonisation. These strategies place strong emphasis on financial support mechanisms, institutional frameworks, and behavioural change as critical enablers of decarbonisation in the built environment. In conclusion, the study demonstrates that successful building decarbonisation extends beyond technological availability and is strongly influenced by supportive financial structures, regulatory alignment, and stakeholder awareness. This study contributes to the growing body of knowledge on building decarbonisation by providing empirically grounded, practitioner-focused insights into implementation strategies rather than relying solely on technological solutions. The findings offer practical guidance for policymakers, industry leaders, and regulatory institutions seeking to operationalise decarbonisation objectives within the built environment. It is therefore recommended that policymakers strengthen green financing frameworks, embed decarbonisation requirements within building regulations, and promote industry-wide capacity-building initiatives. From a practical standpoint, industry stakeholders are encouraged to mainstream energy management practices and actively utilise green rating systems to guide low-carbon decision making. Future research should explore integrating these strategic approaches with quantitative performance-based assessments, longitudinal studies, and sector-specific case studies to further validate and refine building decarbonisation pathways in South Africa and comparable developing economies.

Hybrid solar–thermal energy harvesting—Solar–thermal hybrid energy harvesting systems are a vital development in renewable energy technology, in that they have the ability to produce electrical power and potentially useful thermal energy simultaneously in the same footprint. The conflicting performances of these mechanical apparatus can be highly limited by inefficient heat transfer and ineffective transport of the working mass of liquids and gases, resulting in photovoltaic thermal degradation and high-level exergy loss. The goal of the proposed study is to optimize the heat and mass transport processes that occur in a hybrid solar–thermal mechanical system to make the most out of energy recovery and to guarantee long-term system performance reliability. The governing equations of continuity, momentum, and energy conservation were written in the form of three-dimensional numerical modeling based on the finite volume method (FVM). The genetic algorithm used was the Multi-Objective Genetic Algorithm (MOGA), which was applied to obtain the optimum geometry parameters, that is, analysis of the effects of variable cross-section microchannels on the attributes of the flow and thermal boundary layer disruption. According to the optimization results, at a Reynolds number of 2000, the suggested microchannel geometry raised the average Nusselt number by 43.5% when compared to a smooth channel configuration. As a result, the photovoltaic component's effective operating temperature dropped by 12.6°C, corresponding to a 9.3% increase in relative electrical efficiency. The hybrid system's highest thermal efficiency, net energy gain (76.8%), satisfied the acceptable 16.3% increase in pumping power requirements due to friction penalties. The results of the experiment indicate with no doubt that the optimization of the mass transport processes is a critical component of the facilitation of the high-quality thermal regulation. The results of the experiment indicate without doubt that the optimization of the mass transport processes is a critical component of the facilitation of high-quality thermal regulation. This optimization policy has presented a technically effective channel for the creation of high-grade, high-efficiency industrial solar collector equipment and has laid strong groundwork regarding the development of renewable energy technology that is sustainable and poly-generational.

1. Introduction

This work falls within the scope of ‘Energy and Environment. Sustainable Transition’ because it focuses on converting renewable biogas into methanol and synthetic fuels through integrated processes, contributing directly to industrial decarbonisation and the transition to more sustainable energy systems. The main objective is to develop a methanol production model in a pilot plant, integrated with a steam methane reforming (SMR) unit, fed with biogas from anaerobic digestion processes of organic waste, thus enabling the production of H₂ from renewable sources.

In addition, the integration of a synthesis gas purification stage is proposed, which will not only allow the stream to be adapted for methanol synthesis, but also enable its possible recovery in a Fischer–Tropsch plant for the production of liquid hydrocarbons. In this way, the proposed system is conceived as a flexible platform for converting biogas into fuels and chemical products, whose technical and economic viability can be evaluated using the model developed.

2. Methods

The analysis was carried out using Aspen HYSYS software (Aspen Technology, Inc.), widely used in the industry for chemical process simulation. The methodology included the following stages:

Process definition: all plants were designed with preliminary calculations of conversions, efficiencies and methanol yields, standardised for a pilot capacity of approximately 2 kg/h of CH3OH and 1.5 kg/h of petrol.

The methanol plant was modelled using a plug flow reactor under conditions determined to meet the following requirements:

3H_2(g) + CO_2(g) → H₂O + CH₃OH

The SMR was modelled as a tubular conversion reactor for the steam methane reforming reaction and two equilibrium reactors for the water gas shift reaction:

CH_4(g) + H₂O_(g) → CO_(g) + 3H_2(g)

CO_(g) + H₂O_(g) → CO_2(g) + H_2(g)

This scheme allows the H₂/CO ratio of the synthesis gas to be adjusted according to the requirements of the subsequent synthesis stages.

The Fischer–Tropsch plant was modelled based on representative reaction conditions for the synthesis of hydrocarbons from synthesis gas, considering the overall reactions for the formation of paraffins and olefins:

Paraffins : (2n+1) H₂ + n CO → C_nH_2n+2 + n H₂O

Olefins : 2n H₂ + n CO → C_nH_2n + n H₂O

The model allows the conversion of synthesis gas into a mixture of liquid hydrocarbons such as synthetic fuels to be represented, highlighting the role of the Fischer–Tropsch process as a complementary route to methanol synthesis for the valorisation of reformed biogas.

Integration of units and economic estimation: the necessary equipment was integrated to ensure continuity of operation and cushion fluctuations in biogas flow. A preliminary assessment of the most relevant costs of the system was also initiated, considering both capital expenditure (CAPEX) and operating expenditure (OPEX).

3. Results

The HYSYS simulation showed that integrating a methanol plant with a biogas-fed SMR unit is technically feasible, provided that suitable equipment and thermal and compression strategies are used to ensure operational stability. The energy balance shows that SMR is highly demanding in terms of thermal energy, although it has CH₄ to H₂ conversion efficiencies of over 70%. Its integration with the methanol plant makes it possible to easily achieve production rates of around 2 kg/h of CH₃OH.

Furthermore, the results indicate that the same synthesis gas purification system can be used both for methanol synthesis and to feed the Fischer–Tropsch plant, which increases the versatility of the process scheme. In this sense, the Fischer–Tropsch process appears to be a complementary alternative for transforming synthesis gas into liquid hydrocarbons, expanding the range of products that can be obtained from biogas as a raw material.

From an economic point of view and for both systems, the most relevant equipment in terms of CAPEX is the reformer, the conversion and plug flow reactors, and the purification system. In terms of OPEX, the costs associated with biogas supply and thermal energy input are noteworthy. However, this production method has an advantage in terms of the specific cost of hydrogen (€/kg H₂), due to the lower relative cost of the renewable raw material.

4. Conclusions

The study confirms the technical feasibility of integrating a pilot methanol plant of up to 2 kg/h with a methane reforming plant fuelled by biogas. Simulations show that this configuration can be cost-competitive and also offers high operational flexibility by allowing the synthesis gas to be converted into both methanol and synthetic fuels using Fischer–Tropsch technology.

Although urban structures are essential to achieving sustainability, resilience, and public safety objectives, energy performance and structural integrity are still predominantly evaluated using discrete analytical frameworks. This fragmented approach limits holistic lifecycle decision making and reduces the effectiveness of retrofit strategies. Digital twin (DT) technology, supported by Internet of Things (IoT) sensing, Building Information Modeling (BIM), and data-driven analytics, offers a promising paradigm for integrated building performance assessment. However, despite the rapid growth of DT applications, there remains a lack of consolidated evidence on the joint implementation, validation, and operationalization of energy and structural assessment within unified DT frameworks. Unlike prior reviews that primarily focus on single-domain applications, this study presents a systematic review and research gap analysis of DT-based approaches for integrated energy and structural performance evaluation of buildings.

A systematic literature review was conducted following PRISMA guidelines. A total of 1,248 records were identified from Scopus, Web of Science, and IEEE Xplore using structured keyword combinations including “digital twin,” “BIM,” “energy performance,” “structural health monitoring,” and “building assessment” for the period 2015–2025. After removing duplicates (n = 312) and applying title–abstract screening (n = 936), 214 articles were assessed for full-text eligibility, resulting in 82 studies included in the final synthesis. The selected studies were analyzed using a combined thematic and quantitative synthesis framework covering DT architectures, BIM integration, energy simulation techniques, structural analysis approaches, sensor-data assimilation, and validation strategies.

The results indicate that, while 68% of studies focus on energy performance optimization and 54% on structural health monitoring, only 17% propose partially integrated frameworks, and fewer than 8% demonstrate fully interoperable co-simulation environments. Data exchange between energy and structural domains remains limited, with only 12% of studies enabling bidirectional coupling. Validation practices are largely scenario-based (approximately 70%), with minimal real-time or long-term field validation. Furthermore, only 9% of studies address district- or network-scale DT implementations. Key methodological challenges include BIM standardization, interoperability across simulation platforms, uncertainty quantification, lifecycle scalability, and computational efficiency.

This review advances beyond existing surveys by providing one of the first quantitatively grounded and integration-focused syntheses explicitly addressing the coupling of energy and structural domains within DT frameworks, alongside a structured evaluation of interoperability mechanisms and validation maturity levels. The findings highlight that integrated digital twin development remains an emerging research frontier. Future progress depends on AI-driven surrogate modeling, robust IoT-enabled real-time data synchronization, cloud-based co-simulation infrastructures, and multi-objective optimization frameworks. This study establishes a comprehensive evidence base and research agenda to support the development of scalable, lifecycle-aware, and resilient digital twins for sustainable and structurally robust built environments.

Introduction: The accuracy and real-time performance of drone-based defect detection on solar panels are critical to the operation and maintenance (O&M) efficiency, fault early-warning capability, power generation reliability, and emergency decision-making responsiveness of photovoltaic (PV) power plants. As solar farms expand in scale and complexity, automated inspection solutions have surged. Traditional manual or semi-automated methods are increasingly inadequate due to high labor costs, inconsistent diagnostics, and limited coverage. Efficient and robust defect identification thus becomes a cornerstone of intelligent PV system management, enabling proactive maintenance and maximizing energy yield over the plant’s lifetime.

Methods: This study adopts YOLOX—an advanced deep learning-based object detection algorithm—to automatically identify defects in PV modules from large-scale UAV aerial imagery. The model is specifically trained to detect five core defect types: Broken Glass, Diode Failure, Hot Spots, Obscured panels, and Potential-Induced Degradation (PID) Effect. By integrating baseline PV module databases, complex scene adaptation models, and morphology-differentiated recognition algorithms, YOLOX effectively captures both intrinsic fault mechanisms and context-specific distribution patterns. The model leverages its powerful feature extraction and high-precision localization capabilities to suppress common disturbances such as image noise, inter-module shadows, uneven illumination, and strong glare, ensuring reliable detection across diverse environments.

Results: Experimental evaluations confirm that YOLOX maintains high detection accuracy under challenging real-world conditions—including overcast skies, rainy weather, low-light nighttime scenarios, and large-scale PV arrays. The algorithm provides precise spatial coordinates of defects. Comparative tests demonstrate that YOLOX outperforms models like YOLOv5 and Faster R-CNN in both detection precision and inference speed, particularly in scenes with partial occlusion or reflective glare. Its ability to adapt to varying installation types further enhances its practical applicability.

Conclusions: The desgined approach significantly enhances the automation, precision, and intelligence of PV plant O&M by enabling rapid fault localization, dynamic repair prioritization, and accurate energy loss quantification. By providing structured outputs that link defect location and severity, YOLOX supports data-driven decision-making in routine operations and emergency inspections. This study confirms the feasibility, robustness, and practical applicability of YOLOX for real-world solar farm inspection, offering a scalable and efficient solution for next-generation intelligent photovoltaic management systems.

Smart mobility is often assessed through congestion relief and travel-time indicators, but urban managers operate within a coupled system in which transport operations, digital infrastructure, and energy goals shape one another. The coupling becomes harder to ignore as electrification expands and as cities are asked to report carbon outcomes alongside service reliability in reporting cycles. Analytics-enabled control may lower energy use indirectly when stop-start driving is reduced, average speeds are stabilised, and bus operations become more predictable, which changes traction energy demand and idling losses. At the same time, sensors, communications, and cloud-edge processing draw power continuously, and their lifecycle costs are borne by transport agencies even when energy reporting focuses on vehicles alone.

This study treats city-scale intelligent transportation platforms as an energy-aware urban service system and examines how energy considerations are translated into management practice. A comparative case-study design is applied to Hangzhou, Singapore, and Kuala Lumpur, where different delivery logics (platform-centric public–private delivery, government-led reliability management, and multi-agency coordination under compound risks) have been used to scale data-driven operations. Evidence is triangulated from policy documents, implementation reports, and peer-reviewed studies, and it is interpreted with attention to indicator definitions, baselines, and reporting scope.

What makes similar tools produce different energy and service outcomes? Three management mechanisms are traced. One concerns the local performance regime: which targets are set (delay, reliability, energy or CO2), how objectives are weighted, and how distributional effects are checked when reported gains concentrate on selected corridors or user groups. Another concerns lifecycle governance for digital infrastructure. Low-latency operation is often supported through edge deployment near intersections, yet distributed hardware increases power draw and maintenance work, especially when models must be monitored and updated under drift. A third mechanism concerns coordination with energy actors, since EV charging peaks, pricing, and demand response can be affected by routing and signal policies that shift load in time and place.

Reported differences are interpreted through these managerial conditions, while recurring constraints are acknowledged. Metric heterogeneity, vendor dependency, and limited independent benchmarking reduce cross-city comparability and make causal claims difficult to sustain when evaluation windows and definitions vary.