Search Results (1,019)

Power boiler tubes are exposed to severe operating conditions that lead to wall thinning and material degradation. Reliable assessment of tube wall thickness is therefore essential for ensuring safe and efficient boiler operation. This exploratory laboratory study investigates the applicability of active thermography combined with analytical and machine learning (ML) approaches for non-contact wall thickness estimation in power boiler tubes. Experimental investigations were performed on a single boiler tube specimen with artificially introduced wall-thickness reductions. Thermal responses were recorded using an infrared camera under both heating and cooling excitation conditions. Based on the acquired thermographic data, analytical models and machine learning algorithms were developed to estimate tube wall thickness. The machine learning approach was implemented using Random Forest and Support Vector Regression models and compared with conventional analytical modeling techniques. For separately analyzed and relatively homogeneous measurement series, the machine learning models produced lower descriptive errors than the analytical models, with the estimated three-RMSE error envelope decreasing from 0.51 mm to 0.17 mm. However, when heating and cooling datasets were aggregated, the analytical models achieved lower root mean square error values and demonstrated greater stability than the machine learning methods. These findings indicate that model performance strongly depends on the size, characteristics, and homogeneity of the available training data. Owing to the limited number of independent measurement series, the reported results should be interpreted as a small-sample feasibility assessment rather than as evidence of the general superiority of machine learning modeling. The results support the potential of active thermography for non-contact assessment of boiler tube wall thickness under controlled laboratory conditions. Further validation using additional specimens, grouped cross-validation, and physics-based synthetic data is required before the methodology can be considered for industrial implementation. Full article

Enhanced circular tubes are widely employed in shell-and-tube heat exchangers, power-generation condensers, chemical reactors, refrigeration systems, and air-cooled heat exchangers, where improved convective performance can reduce the heat-transfer area required for a specified thermal duty. Helical screw tapes (HSTs) are passive inserts that promote sustained swirling motion and enhance convective heat transfer within such tubes. Although helical screw tapes and multiple-insert arrangements have been investigated previously, the combined thermohydraulic and second-law effects of increasing the number of co-rotating HSTs under fixed geometric ratios remain insufficiently quantified. In this investigation, turbulent airflow in a heated round tube was numerically investigated to examine the effect of tape number on heat transfer, pressure drop, thermal performance, total entropy generation (S_total), and exergy destruction (Ex_D). Six HST configurations containing one to six tapes were examined over a Reynolds-number range of Re = 5000–20,000 in a circular tube with an inner diameter of D_T = 31 mm, which was also adopted as the characteristic length for the Reynolds number, Nusselt number, and friction factor. The helical pitch P, screw diameter D_s, tape width W, and tape thickness t were 60 mm, 30 mm, 4.5 mm, and 0.2 mm, respectively, giving a pitch ratio of P/D_s = 2.0 and a width ratio of W/D_s = 0.15. A plain tube (PT) served as the baseline case. The results show that increasing the number of tapes intensifies swirl flow and enhances heat transfer but also leads to a continuous increase in pressure loss. For the optimum three-tape arrangement, the Nusselt number is increased by 126.0–158.8% and the thermal performance factor by 4.5–19.5% relative to the plain tube, while the total entropy generation and exergy destruction are simultaneously reduced by 7.9–61.0%. Among the configurations examined, HST-P2.0-W0.150-3, comprising three tapes at a pitch ratio of P/D_s = 2.0 and a width ratio of W/D_s = 0.15, achieved the best overall performance by delivering the highest thermal performance factor and the lowest total entropy generation and exergy destruction among the HST cases. Full article

Degraded industrial sites in arid and semi-arid regions often suffer from loose surface substrates, weak water-retention capacity, high wind-erosion risk, and poor early vegetation establishment. Combining photovoltaic (PV) deployment with ecological utilization may improve near-surface habitats by shading, reducing wind speed, and regulating soil heat and moisture. This study investigated an ash storage yard of a coal-fired power plant in Ordos, Inner Mongolia, China, by comparing soil temperature, soil moisture, and near-surface wind-speed responses under three representative fixed PV tilt angles of 36°, 43°, and 50°, together with the corresponding early plant-growth suitability. A multi-physics model coupling near-surface airflow, water-vapor transport, and porous-media hydrothermal migration was established. A Gaussian suitability function combined with AHP-CRITIC weighting was used to construct a model-based comprehensive growth index (CGI) from soil temperature and moisture, while short-term field monitoring was used to validate afternoon soil hydrothermal trends. Among the three scenarios, the 36° configuration produced the widest horizontal heat–moisture-affected zone and the highest CGI values for alfalfa and Elymus nutans, reaching 0.7741 and 0.6875, respectively. Relative to the outside reference area, the rear PV zone reduced the near-surface wind speed by 33–40% and increased the plant heights of alfalfa and Elymus nutans by 49.4% and 37.8%, respectively. A first-order PVsyst assessment showed that the 43° configuration achieved the highest specific energy yield of 1814 kWh kWp⁻¹ year⁻¹, whereas the annual grid-connected output at 36° was only 0.59% lower. These findings indicate that the 36° configuration may provide a favorable compromise between early vegetation establishment and photovoltaic electricity generation among the tested scenarios. By linking renewable-energy production with microenvironment regulation and early vegetation establishment, the proposed framework provides a decision basis for the multifunctional and sustainable reuse of degraded industrial land. Nevertheless, the results represent a site-specific, single-season assessment and should not be interpreted as a universal optimum. Full article

PV/T collectors and Air Source Heat Pump (ASHP) are widely studied for building heating, but solar intermittency and ASHP low-temperature frosting limit their large-scale deployment. A novel PV/T-ASHP coupled heating system is proposed to cut building carbon emissions and relieve ASHP performance degradation in cold zones. Circulating water cools PV/T panels to boost power generation, and the warmed water preheats ASHP evaporator inlet air to reduce frosting and defrosting frequency. With a Xi’an office building as the research object, validated TRNSYS 18.0 models are established for comparative analysis with conventional systems and cross-climate evaluation in Xi’an, Beijing, Shanghai and Chengdu. Results show the new system lifts PV/T combined efficiency by 17.56%, reduces energy consumption by 19.9%, and achieves an average COP of 3.2. Across climate zones, its COP rises 11.5–24.6% and 50-year carbon emissions fall 16.4–26.2%, supporting low-carbon heating promotion for office buildings. Full article

Magnetothermally responsive nanocarriers represent a promising platform for spatio-temporally controlled drug delivery by combining alternating magnetic field (AMF)-induced heating with thermally triggered cargo release. Among the available architectures, magnetite-core/mesoporous-silica-shell (Fe₃O₄@mSiO₂) nanoparticles functionalized with thermoresponsive polymer gatekeepers are particularly attractive. These systems integrate a magnetic heat source, a mesoporous drug reservoir, and temperature-dependent control of pore accessibility. This review examines the fundamental principles of magnetic hyperthermia, including heat-generation mechanisms, specific absorption rate (SAR), intrinsic loss power (ILP), AMF parameters and safety, and the interplay between Néel and Brownian relaxation. It also critically discusses core–shell synthesis and architecture, drug-loading strategies, PNIPAM-, PNVCL-, and other LCST-type gatekeepers, and the physicochemical characterization required to validate the complete nanocarrier. Evidence for combined magnetic hyperthermia and chemotherapy is assessed together with hemocompatibility, immunogenicity, oxidative stress, biodistribution, degradation, long-term retention, and clearance. Although promising magnetothermal release and therapeutic effects have been reported, evidence remains dominated by in vitro studies, with limited in vivo validation. Current clinical experience concerns locally administered iron-oxide hyperthermia rather than complete thermoresponsive Fe₃O₄@mSiO₂ drug-delivery systems. Translation will require standardized magnetothermal and release testing, reproducible scale-up, validated sterilization and endotoxin control, component-resolved pharmacokinetics, and integrated development of the nanocarrier and AMF applicator. Full article

To improve the antifouling and self-cleaning performance of 3003 aluminum alloy, a fluorine-free water-repellent surface was fabricated by combining nanosecond laser texturing with subsequent heat treatment. The effects of scanning speed, laser power, pulse frequency, and scanning interval on surface wettability were systematically investigated. Under the optimal conditions of 2700 mm/s, 6 W, 35 kHz, and 20 μm, the surface achieved a maximum static water contact angle of 154.3 ± 0.8°. Surface characterization showed that laser processing generated hierarchical micro-/nano-scale structures, while heat treatment promoted surface chemical evolution associated with enhanced hydrophobicity. The highly water-repellent behavior resulted from the synergistic effect of hierarchical roughness and heat-treatment-induced surface chemical changes. The fabricated surface exhibited effective self-cleaning performance, achieving a SiO₂ removal efficiency of 98.8% under the specified test conditions. In addition, relatively high water repellency was retained after repeated water-impact and tape-peeling tests. These results demonstrate that nanosecond laser texturing combined with heat treatment provides a simple and environmentally friendly strategy for fabricating water-repellent AA3003 surfaces for antifouling and surface-protection applications. Full article

Rapid growth in artificial intelligence, machine learning, and high-performance computing has substantially increased data centre rack power densities, resulting in higher heat generation and more demanding cooling requirements. As water remains widely used in many cooling systems, understanding the relationship between cooling technologies and water consumption is essential for improving cooling efficiency and sustainability. This paper presents a survey of reported water usage effectiveness (WUE) across 83 data centre entries, providing a combined dataset that links WUE with heat-rejection categories. The reported data shows that 23 of these data centres exceed 0.4 L/kWh, which is a sustainability target specified by the Climate Neutral Data Centre Pact for new data centres in water-stressed regions using potable water. Dry facilities employing closed-loop liquid cooling require essentially no water, while evaporative systems typically report water usage effectiveness values up to 2.5 L/kWh. Reported WUE is a facility-level operational metric, set by the proportion of the IT heat load rejected by evaporation, which depends on the heat-rejection topology, ambient wet-bulb conditions, and operating set points. A higher server-side heat transfer coefficient permits a higher coolant supply temperature for a given chip temperature limit, widening the range of ambient conditions under which heat can be rejected without evaporative assistance. Server-side heat transfer is therefore an enabling condition for low WUE rather than a determinant of it. One-dimensional heat transfer models are developed to estimate heat transfer coefficients for different server-level cooling mechanisms widely used for cooling servers within data centres, including air cooling, single-phase immersion cooling, direct liquid cooling, and two-phase immersion cooling. Air cooling, with the lowest heat transfer coefficient, remains widely used in small-scale facilities, whereas direct liquid cooling and two-phase immersion cooling achieve coefficients up to three orders of magnitude higher and are increasingly deployed in high-density installations. These coefficients are used to derive an equivalent evaporative water demand, an upper-bound estimate of the water that would be evaporated in rejecting the heat each mechanism removes; it shares the units of reported WUE but describes thermal capability rather than facility water consumption. Full article

This paper develops a measurable unified electric–thermal energy indicator for converter-dominated microgrids, containing virtual synchronous generator (VSG) and virtual asynchronous machine (VAM) dynamics. The principal contribution comprises the scalar energy indicator $H_{\Sigma }$ and its normalized margin ${\eta }_{\mathrm{stab}}$; together, they combine active-power–frequency, reactive-power–voltage, thermal-flow, current-boundary, and electric–thermal coupling information obtained from point-of-common-coupling measurements and thermal states. A bounded event-triggered thermal–electric action is used only as a secondary demonstration of how the indicator can support current-constrained coordination; it is not proposed as a replacement for the inner VSG controller. Local positive-definiteness, dissipation, invariant-sublevel-set, and two-time-scale conditions are derived in an explicitly defined operating domain. The framework was evaluated in a three-phase Simulink/Simscape model using a 26-run matrix of disturbance and parameter cases, together with three severe-case baselines and four reduced-order channel-isolation cases. For voltage-sag depths of 5–20%, the event increase in $H_{\Sigma }/H_{\mathrm{crit}}$ rose from 0.137 to 0.385. In the severe 20% combined case, bounded coordination increased the minimum margin from 0.048 to 0.138, with 0.0897 kWh of heat-load reduction; however, its trajectory was identical to that of the matched current-threshold trigger, so no controller-performance superiority is claimed. Omitting $H_{qv}$, $H_{th}$, $H_{lim}$ and $H_{cpl}$ eliminated 100.0%, 99.7%, 90.8% and 87.3%, respectively, of the corresponding event-window sensitivity. Under deep-current saturation, the limiter gain fell to 0.466 and ${\eta }_{\mathrm{stab}}$ reached zero, numerically identifying a boundary beyond which the local stability guarantee must not be extrapolated. Full article

Kelp is a high-moisture, flexible, sheet-like marine biomass whose drying behavior is strongly affected by the coupled effects of radiative heating, convective vapor removal, internal moisture migration, tissue shrinkage, curling, and material overlap. Traditional sun drying and hot-air drying remain widely used but are limited by long processing cycles, environmental dependence, high energy consumption, and inconsistent product quality. With the development of infrared heating, heat-pump dehumidification, Internet of Things (IoT)-enabled sensing, fifth-generation (5G) mobile communication, multiphysics simulation, and digital control, kelp drying is progressively shifting toward monitored, model-assisted, and intelligent processing. This review critically summarizes recent advances in kelp and related seaweed drying, with particular emphasis on infrared-assisted heat and mass transfer, drying kinetics, coupled computational fluid dynamics–finite element method (CFD–FEM) simulation, quality evaluation, and intelligent control. Representative published studies demonstrate the engineering potential of these approaches. In a suspended infrared-array kelp drying system, an infrared power density of 1.2 kW m−2 combined with an air velocity of 3 m s−1 maintained the drying temperature at approximately 55–62 °C, while relative humidity decreased from about 80% to 20–30%. Under these conditions, the Page model achieved R² = 0.987 and RMSE = 0.019, the rehydration ratio exceeded 94%, and the total color difference remained below ΔE = 6.5. A recent CFD–FEM–MATLAB workflow further reported a composite operating-condition index of J = 0.4535, with mapped mean and maximum kelp surface temperatures of 62.23 and 63.57 °C, respectively. These quantitative results indicate that the key challenge in infrared kelp drying is not simply to increase heat input, but to coordinate radiation distribution, airflow organization, internal moisture transport, structural response, and quality preservation. Future research should therefore focus on experimentally validated heat–mass-transfer models, adaptive sensing and control, multi-objective optimization, and pilot-scale verification under realistic production conditions. Full article

The power injections variability due to volatile renewable energy sources and large dynamic loads (e.g., Plug-in Electric Vehicles and Heat Pumps) may cause excessive voltage fluctuations and power system instability. To mitigate these problems, accurate load profiles are needed to support both grid operation and planning. However, real load profiles are not always readily and fully available due to technical and privacy constraints, limiting their applicability and the possibility of extrapolating consumption patterns for prospective studies. Synthetic load profile generation offers a practical alternative to address these limitations, while preserving data privacy and accessibility. This paper presents a deep learning framework that combines Wasserstein Generative Adversarial Networks with Gradient Penalty (WGAN-GP) to produce artificial, but data-driven seasonal weekly load profiles (SWLP). The training process for each cluster uses separate WGANs, which implement the Wasserstein loss function together with gradient penalty to ensure stable training, while preventing mode collapse. The quality of the synthetic profiles is evaluated using statistical and distribution-based metrics. The proposed WGAN-GP achieved an average Wasserstein distance of 0.042 with a pattern correlation coefficient of about 0.98 with respect to the real load profiles derived from an Irish residential dataset. In comparison, the WGAN without gradient penalty returned am averageWasserstein distance of 0.352, while a Variational Autoencoder (VAE) used as a benchmark achieved an average Wasserstein distance of 0.108 with a pattern correlation coefficient of 0.92. Mean profile comparisons and load distribution analyses showed a good agreement between real and synthetic data across all identified consumption-pattern clusters. These results demonstrate the capability of the proposed framework to generate SWLPs preserving the statistical and temporal characteristics of real electricity consumption data. Full article

This study investigates the integration of CO₂/H₂S separation and internal power generation in power- and biomass-to-liquid (PBtL) and fuel-assisted PBtL (FAPBtL) processes to enhance carbon efficiency and reduce external electricity demand. Four configurations (PBtL, FAPBtL-recycle, FAPBtL-purge, and Purge-to-Fuel (Purge-tF)) are evaluated through detailed mass and energy balances, thermal integration analysis, and techno-economic assessment. Reintegration of separated CO₂ eliminates carbon losses in the acid gas removal unit, increasing carbon efficiencies to approximately 98% for PBtL and Purge-tF, 97% for FAPBtL-recycle, and 79% for FAPBtL-purge. Increasing the carbon efficiency from 91% to 98%, for PBTL, comes from capturing 85% of the CO₂ downstream of the acid gas removal unit. In parallel, integration of a supercritical two-step reheat Rankine cycle with preheating enables the recovery of high-temperature process heat, increasing cycle efficiency from 42% to 55% and generating up to 61 MW of internal power. Although CO₂/H₂S separation introduces additional capital and energy requirements, the combined integration of carbon recycling and heat-to-power recovery improves overall system performance. The Purge-tF configuration achieves the lowest net production cost of 2.60 €/kg_fuel (2.11 €/L_fuel). Sensitivity analysis confirms electricity price as the dominant economic driver. The results demonstrate that strategic integration of carbon recycling and advanced heat recovery can substantially improve both the carbon utilization and economic viability of biomass-based synthetic fuel production. Full article

The transition towards circular economy models is driving the transformation of wastewater treatment plants (WWTPs) from energy-intensive facilities into resource recovery systems capable of generating renewable energy. In this context, this study developed an integrated mass and energy balance methodology to assess sludge production, anaerobic digestion performance, biomethane recovery, and electricity generation in a full-scale urban WWTP. The proposed framework integrates the water treatment line, sludge processing line, and energy recovery system, combining primary and secondary sludge management with biogas upgrading and combined heat and power (CHP) generation. Representative operating parameters from the scientific literature were applied to a facility treating 204,000 m³ d⁻¹ and serving approximately 425,000 population equivalents. The results showed that primary sludge accounted for approximately 70% of the volatile solids fed to the anaerobic digester. Methane production was estimated at 1.12 × 10³ kg CH₄ d⁻¹, corresponding to a biogas production of 2.40 × 10³ m³ d⁻¹. Under two alternative valorisation scenarios, the maximum recovered biomethane flow was 1.48 × 10³ m³ d⁻¹, whereas the maximum annual electricity generation potential through CHP was 1.9 × 10⁶ kWh. These findings highlight the potential of integrated sludge valorisation strategies to enhance renewable energy recovery and support the transition of WWTPs towards energy-efficient and low-carbon resource recovery facilities. Full article

Combined cooling, heating, and power (CCHP) tri-generation systems can greatly improve comprehensive energy utilization efficiency thanks to their energy-cascade utilization concept. However, traditional fossil-fuel-based CCHP systems still suffer from intensive carbon emissions, hindering their further development in the current low-carbon scenario. To solve this issue, a new low-carbon CCHP system (LC-CCHP) integrating a calcium-looping, sorption-enhanced steam methane reforming (CL-SE-SMR) unit, a lithium bromide absorption chiller, and a hydrogen gas turbine is proposed in this work, and the corresponding system model is built to evaluate its performance. The proposed system features an innovative architecture that integrates carbon capture directly into the reforming process, which simultaneously enables a high hydrogen yield and low carbon-capture penalty. Moreover, instead of the widely used thermodynamic equilibrium assumption, a detailed kinetic model is employed for the CL-SE-SMR unit, which provides more realistic predictions and greater reference value for practical engineering applications. Then, multi-objective optimization is conducted using a particle swarm optimization algorithm to identify the optimal operating conditions. It is found that the proposed system performs best at a steam-to-carbon molar ratio of 4.37, a calcium-to-carbon mass ratio of 6.23, an air-equivalency molar ratio of 1.39 for a hydrogen gas turbine and a reaction temperature of 600 °C for SE-SMR. Under these operating conditions, the system can achieve a carbon-capture rate of 89.2%, an exergy efficiency of 45.7%, an energy efficiency of 95.4%, and a levelized cost of exergy of 0.109 $/kWh. Full article

Resilience and adaptation to extreme climate events have become an urgent necessity. As cities grow denser, increasing numbers of people are exposed to water scarcity, flooding, and power grid disruptions. Immediate action is required to safeguard human lives and property. Residential buildings exert a significant environmental impact throughout their operational phase, contributing to air, land, and water pollution. A more sustainable and proactive approach to building management is essential to reduce the consumption, processing, and disposal of natural resources. This article explores the potential for biogas production from decentralised/on-site wastewater treatment systems through the co-digestion of blackwater (BW) and kitchen waste (KW) for existing residential buildings located in densely populated urban areas using hybrid grids. It addresses the importance of wastewater source separation, the use of BW and KW blends to achieve the best biogas production, and the environmental, economic and social aspects of these systems’ implementation. An extensive literature review and state-of-the-art analysis were conducted to assess the potential, main challenges, and research directions in this field. The results indicate that decentralised anaerobic systems can be technically feasible, reducing grid energy dependence, optimising water use, and valorising digestate as fertiliser—fully aligned with the EU’s Green Deal and the UN Sustainable Development Goals regarding sustainability and circularity. However, few studies address the feasibility of BW (vacuum toilet) and KW co-digestion for combined heat and power generation in hybrid grids. Further pilot- and full-scale research is therefore needed to increase system reliability and social acceptance. Full article

The growing integration of variable renewable energy sources (VRES) challenges power system flexibility and may cause curtailment due to excess capacity, grid constraints, or operational and market factors. Power-to-Heat (PtH) technology can mitigate these issues by coupling electricity and district heating sectors, providing additional flexibility and supporting decarbonisation. This study develops a long-term generation capacity expansion model that integrates PtH and district heating system (DHS) operation to achieve balanced VRES penetration. The model includes DHS heat demand balances and links electricity and heat via thermal power plants, combined heat and power (CHP) plants, and PtH units. The methodology is applied to Ukraine’s Integrated Power System and district heating demand through 2040, employing typical daily load profiles discretised into six four-hour segments. Results demonstrate the feasibility of deploying PtH electric boilers during the non-heating season, when high RES and base load nuclear generation create surplus electricity. These boilers convert excess wind and solar power into thermal energy for district heating, displacing natural gas-fired technologies and simultaneously decarbonising electricity and heat supply. Full article