Search Results (200)

High-frequency (h. f.) harmonic distortion (HD) of advanced SiGe heterojunction bipolar transistor (HBT)-based power cells (PwCs), featuring optimized metallization interconnections between individual HBTs, was investigated. Single tone input power (P_in) excitations at 1, 2, 5, and 10 GHz frequencies were employed. The output power (P_out) of the fundamental tone and its harmonics were analyzed in both the frequency and time domains. A rapid increase in the third harmonic of P_out was observed at input powers exceeding −8 dBm for a fundamental frequency of 10 GHz in two different PwC technologies. This increase in the third harmonic was analyzed in terms of nonlinear current waveforms, the nonlinearity of the HBT p-n junction diffusion capacitances, substrate current behavior versus P_in, and avalanche multiplication current. To assess the RF power performance of the PwCs, scalar and vectorial load-pull (LP) measurements were conducted and analyzed. Under matched conditions, the SiGe PwCs demonstrated good linearity, particularly at high frequencies. The key power performance of the PwCs was measured and simulated as follows: input power 1 dB compression point (P_{in_1dB}) of −3 dBm, transducer power gain (G_T) of 15 dB, and power added efficiency (PAE) of 50% at 30 GHz. All measured data were corroborated with simulations using the compact model HiCuM L2. Full article

The global shift towards the use of renewable energy is essential to ensure sustainable development, and geothermal energy stands out as a suitable option that can support various cascading projects. Spent geothermal water (SGW) requires proper treatment to ensure that it does not become an environmental burden. Typically, companies often face the dilemma of choosing between discharging spent geothermal water (SGW) into surface waters or injecting it into rock masses, and the economic and environmental impacts of the decision made determines the feasibility of geothermal plant development. In this study, we aimed to comprehensively assess the technical, economic, and environmental feasibility of SGW injection into rock masses. To this end, we employed a comprehensive analytical approach using the Chochołów GT-1 geothermal injection borehole in Poland as a reference case. We also performed drilling and hydrogeological testing, characterized rock samples in the laboratory, and corrected hydrodynamic parameters for thermal lift effects to ensure accurate aquifer characterization. The results obtained highlight the importance of correcting hydrogeological parameters for thermal effects, which if neglected can lead to a significant overestimation of the calculated hydrogeological parameters. Based on our analysis, we developed a framework for assessing SGW injection feasibility that integrates detailed hydrogeological and geotechnical analyses with environmental risk assessment to ensure sustainable geothermal resource exploitation. This framework should be mandatory for planning new geothermal power plants or complexes worldwide. Our results also emphasize the need for adequate SGW management so as to ensure that the benefits of using a renewable and zero-emission resource, such as geothermal energy, are not compromised by the low absorption capacity of rock masses or adverse environmental effects. Full article

Variable-speed reciprocating compressors (VSRCs) have been increasingly used in domestic refrigeration due to their ability to modulate cooling capacity and reduce energy consumption. A detailed understanding of performance-limiting factors such as volumetric and exergetic inefficiencies is essential for optimizing their operation. An experimentally validated simulation model was developed using GT-SUITE to analyze a VSRC operating with R-600a across speeds from 1800 to 6300 rpm. Volumetric inefficiencies were quantified using a stratification methodology, while an exergy-based approach was adopted to assess the main sources of thermodynamic inefficiency in the compressor. Unlike traditional energy analysis, exergy analysis reveals where and why irreversibilities occur, linking them directly to power consumption and providing a framework for optimizing design. Results reveal that neither volumetric nor exergy efficiency varies monotonically with compressor speed. At low speeds, exergetic losses are dominated by the electrical motor (up to 19% of input power) and heat transfer (up to 13.5%). Conversely, at high speeds, irreversibilities from fluid dynamics become critical, with losses from discharge valve throttling reaching 5.8% and bearing friction increasing to 6.5%. Additionally, key volumetric inefficiencies arise from piston–cylinder leakage, which causes up to a 4.5% loss at low speeds, and discharge valve backflow, causing over a 5% loss at certain resonant speeds. The results reveal complex speed-dependent interactions between dynamic and thermodynamic loss mechanisms in VSRCs. The integrated modeling approach offers a robust framework for diagnosing inefficiencies and supports the development of more energy-efficient compressor designs. Full article

Gas turbine (GT) modeling and optimization have been widely studied at the design level but still lacks focus on real-world operational cases. The concept of a digital twin (DT) allows for the interaction between operation data and the system dynamic performance. Among many DT studies, only a few focus on GT for thermal power plants. This study proposes a digital twin prototype framework including the following modules: process modeling, parameter estimation, and performance optimization. Provided with real-world power plant operational data, key performance parameters such as turbine inlet temperature (TIT) and specific fuel consumption (SFC) were initially unavailable, therefore necessitating further calculation using thermodynamic analysis. These parameters are then used as a target label for developing artificial neural networks (ANNs). Three ANN models with different structures are developed to predict TIT, SFC, and turbine power output (GTPO), achieving high R² scores of 94.03%, 82.27%, and 97.59%, respectively. Physics-informed neural networks (PINNs) are then employed to estimate the values of the air–fuel ratio and combustion efficiency for each time index. The PINN-based estimation resulted in estimated values that align with the literature. Subsequently, an unconventional method of detecting alarms by using conformal prediction were also proposed, resulting in a significantly reduced number of alarms. The developed ANNs are then combined with particle swarm optimization (PSO) to carry out performance optimization in real time. GTPO and SFC are selected as the primary metrics for the optimization, with controllable parameters such as AFR and a fine-tuned inlet guide vane position. The results demonstrated that GTPO could be optimized with the application of conformal prediction when the true GTPO is detected to be higher than the upper range of GTPO obtained from the ANN model with a conformal prediction of a 95% confidence level. Multiple PSO variants were also compared and benchmarked to ensure an enhanced performance. The proposed PSO in this study has a lower mean loss compared to GEP. Furthermore, PSO has a lower computational cost compared to RS for hyperparameter tuning, as shown in this study. Ultimately, the proposed methods aim to enhance GT operations via a data-driven digital twin concept combination of deep learning and optimization algorithms. Full article

Access to clean and sustainable energy technologies is critical for all nations, particularly developing countries in Africa. Ghana has committed to ambitious greenhouse gas emission reduction targets, aiming for 10% and 20% variable renewable energy integration by 2030 and 2070, respectively. This study explores potential pathways for Ghana to achieve its renewable energy production targets amidst a growing energy demand. An open-source energy modelling tool was used to assess four scenarios accounting for current policies and additional alternatives to pursue energy transition goals. The scenarios include Business as Usual (BAU), Government Target (GT), Renewable Energy (REW), and Net Zero (NZ). The results indicate that total power generation and installed capacity would increase across all scenarios, with natural gas accounting for approximately 60% of total generation under the BAU scenario in 2070. Total electricity generation is projected to grow between 10 and 20 times due to different electrification levels. Greenhouse gas emission reduction is achievable with nuclear energy being critical to support renewables. Alternative pathways based on clean energy production may provide cost savings of around USD 11–14 billion compared to a Business as Usual case. The findings underscore the necessity of robust policies and regulatory frameworks to support this transition, providing insights applicable to other developing countries with similar energy profiles. This study proposes a unique contextualized open-source modelling framework for a data-constrained, lower–middle-income country, offering a replicable approach for similar contexts in Sub-Saharan Africa. Its novelty also extended towards contributing to the knowledge of energy system modelling, with nuclear energy playing a crucial role in meeting future demand and achieving the country’s objectives under the Paris Agreement. Full article

Nowadays, there are many studies that have been conducted in order to reduce the emissions of modern reciprocating engines without, at the same time, having a negative impact on the performance characteristics. One method to accomplish that is by using ethanol-supplemented fuels instead of conventional gasoline. On the other side of the spectrum, spark timing is one of the most important parameters that affects the combustion mechanism inside a reciprocating engine and is basically controlled by the ignition advance of the engine. Therefore, the main purpose of this study is to investigate the effect of spark timing alteration on the performance characteristics and emissions of a modern reciprocating, naturally aspirated, aircraft SI engine (i.e., ROTAX 912s), operated under four different engine operating points (i.e., combination of engine speed and throttle opening), by using ethanol-supplemented fuel. The implementation of the aforementioned method is achieved through the use of an advanced simulating software (i.e., GT-POWER), which provides the user with the possibility to completely design a piston engine and parameterize it, by using a comprehensive single-zone phenomenological model, for any operating conditions in the entire range of its operating points. The predictive ability of the designed engine model is evaluated by comparing the results with the experimental values obtained from the technical manuals of the engine. For all test cases examined in the present work, the results are affiliated with important performance characteristics, i.e., brake power, brake torque, and brake-specific fuel consumption, as well as specific NO and CO concentrations. Thus, the primary objectives of this study were to examine and evaluate the results of the combination of using ethanol-supplemented fuel instead of gasoline and the alteration of the spark timing, to asses their effects on the basic performance characteristics and emissions of the aforementioned type of engine. By examining the results of this study, it is revealed that the increase in the ethanol concentration in the gasoline–ethanol fuel blend combined with the increase in the ignition advance might be an auspicious solution in order to meliorate both the performance and the environmental behavior of a naturally aspirated SI aircraft piston engine. In a nutshell, the outcoming results of this research show that the combination of the two methods examined may be a valuable solution if applied to existing reciprocating SI engines. Full article

Mineralogical variability exerts a profound influence on the flotation performance of Platinum Group Metal (PGM) ores, particularly those from the Platreef deposit, where complex associations and textures influence recovery, grade, and kinetics. This study integrates the Mode of Occurrence (MOC) and mineral associations into a modified Kelsall flotation kinetics model, optimized using a Particle Swarm Optimization (PSO) algorithm, to improve prediction accuracy. Batch flotation tests were conducted on eight samples from two lithologies—Pegmatoidal Feldspathic Pyroxenite (P-FPX) and Feldspathic Pyroxenite (FPX)—with mineralogical characterization performed using MLA, QEMSCAN, and XRD. PGMs in liberated (L) and sulfide-associated (SL) forms accounted for up to 90.6% (FPX1), exhibiting high fast-floating fractions (θ_f = 0.77–0.84) and fast flotation rate constants (K_f = 1.45–1.78 min⁻¹). In contrast, PGMs locked in silicates (G class) showed suppressed kinetics (K_f < 0.09 min⁻¹, K_s anomalies up to 8.67 min⁻¹) and were associated with lower recovery (P-FPX3 = 83.25%) and increased model error (P-FPX4 = 57.3). FPX lithologies achieved the highest cumulative recovery (FPX4 = 90.35%) and the best concentrate grades (FPX3 = 116.5 g/t at 1 min), while P-FPX1 had the highest gold content (10.45%) and peak recovery (94.37%). Grade-recovery profiles showed steep declines after 7 min, particularly in slow-floating types (e.g., P-FPX2, FPX2), with fast-floating lithologies stabilizing above 85% recovery at 20 min. The model yielded R² values above 0.97 across all samples. This validates the predictive power of MOC-integrated flotation kinetics for complex PGM ores and supports its application in geometallurgical plant design. Model limitations in capturing complex locked ore textures (SAG, G classes) highlight the need for reclassification based on floatability indices and further integration of machine learning methods. Full article

This study proposes a data-driven optimization framework to enhance emission control performance in diesel engine selective catalytic reduction (SCR) systems under transient operating conditions. A one-dimensional SCR model was constructed in GT-Power, and simulation datasets were generated using experimentally measured inputs from the World Harmonized Transient Cycle (WHTC), with representative emission responses obtained by varying fixed ammonia-to-NOx (A/N) ratios. Building on these datasets, a hybrid prediction model combining Long Short-Term Memory (LSTM) networks and multi-head attention mechanisms was developed to accurately forecast SCR outlet NH₃ leakage and NOx emissions. The model exhibited high predictive accuracy, achieving R² values exceeding 0.977 and low RMSE across training, validation, and test sets. Based on the model predictions, a constrained dynamic multi-objective optimization strategy was implemented to adaptively adjust ammonia dosing, aiming to simultaneously minimize NH₃ leakage and NOx emissions. The optimized NH₃ injection profiles were validated through reapplication in the GT-Power simulation environment. Compared to the baseline fixed-ratio control strategy, the proposed approach reduced NH₃ leakage and NOx emissions by 34.40% and 11.15%, respectively, as determined for the transient segment of the WHTC cycle. These results demonstrate the effectiveness of integrating physics-based simulation, deep learning prediction, and dynamic optimization for improving aftertreatment adaptability and emission compliance in real-world diesel engine applications. All reported values are based on a single simulated WHTC cycle without statistical uncertainty analysis. Full article

Accelerating the low-carbon transition of China’s coal-fired power sector is essential for advancing national sustainability goals and fulfilling global climate commitments. This study introduces an integrated, data-driven analytical framework to facilitate the sustainable transformation of the coal power sector through coordinated unit-level retirements, new capacity planning, and targeted retrofits. By combining a comprehensive unit-level database with a multi-criteria evaluation framework, the analysis incorporates environmental, technical, and economic factors into decision-making for retirement scheduling. Scenario analyses based on the China Energy Transformation Outlook (CETO 2024) delineate both baseline and ideal carbon neutrality pathways. Optimization algorithms are employed to identify cost-effective retrofit strategies or portfolios, minimizing levelized carbon reduction costs. The findings reveal that cumulative emissions can be reduced by 10–14.9 GtCO₂ by 2060, with advanced technologies like CCUS and co-firing contributing over half of retrofit-driven mitigation. The estimated transition cost of 6.2–6.7 trillion CNY underscores the scale of sustainable investment required. Sensitivity analyses further highlight the critical role of reducing green hydrogen costs to enable deep decarbonization. Overall, this study provides a robust and replicable planning tool to support policymakers in formulating strategies that align coal power sector transformation with long-term sustainability and China’s carbon neutrality commitments. Full article

With the extensive construction of high-voltage power grid projects in complex mountainous terrains, rainfall-induced slope instability poses a significant threat to the safety of transmission tower foundations. This study focuses on a power transmission and transformation project in Huizhou City, Guangdong Province. Using MIDAS GTS NX 2019 (v1.2), an unsaturated seepage-mechanics coupling model was established to systematically investigate the influence of slope ratios (1:0.75, 1:1, and 1:1.25) on slope stability under rainfall conditions and the reinforcement effects of anti-slide piles. The results demonstrate that slope ratios significantly govern slope responses. For steep slopes (1:0.75), post-rainfall matrix suction loss reached 43.2%, peak displacement attained 74.49 mm, and the safety factor decreased by 12.5%. In contrast, gentle slopes (1:1.25) exhibited superior stability. Anti-slide piles effectively controlled displacement growth (≤9.15%), but pile bending moments increased markedly with steeper slope ratios, accompanied by a notable expansion of the plastic zone at the slope toe. The study reveals a destabilization mechanism characterized by “seepage–strength degradation–displacement synergy” and recommends engineering practices adopting slope ratios of 1:1–1:1.25, combined with anti-slide piles (spacing ≤ 1.5 m) and dynamic drainage measures. These findings provide critical guidance for the design of transmission tower slopes in mountainous regions. Full article

This study presents a comprehensive dynamic model of a small-scale, solar-powered hydraulic gas compression energy storage system tailored for renewable energy applications. Addressing the intermittency of renewable energy sources, the model incorporates mass, momentum, and energy conservation principles and is implemented using GT-Suite simulation software v2025.0. The system, based on a liquid piston mechanism, was analyzed under both adiabatic and isothermal compression scenarios. Validation against experimental data showed maximum deviations under 10% for pressure and 5 °C for temperature. Under ideal isothermal conditions, the system stored up to 8 MJ and recovered 6.1 MJ of energy, achieving a round-trip efficiency of 76.3%. In contrast, adiabatic operation yielded 52.6% efficiency due to thermal losses. Sensitivity analyses revealed the importance of heat transfer enhancement, with performance varying by over 15% depending on spray cooling intensity. These findings underscore the potential of thermally integrated hydraulic systems for efficient, scalable, and cost-effective energy storage in distributed renewable energy networks. Full article

This study developed a microporous silica nanosilver antioxidant material (GT-Ag@MSN) from waste photovoltaic (PV) cells by incorporating plant polyphenols in the in situ synthesis. The biosynthesized GT-Ag@MSN had an average size of 296.5 nm, a pore size of 1.96 nm, and an Ag loading of 1.45%. The material was further evaluated through antibacterial tests, antioxidant capacity tests, and a reducing power assay. GT-Ag@MSN exhibited a minimum inhibitory concentration (MIC) of 20 mg/mL for Escherichia coli and Staphylococcus aureus, and a minimum bactericidal concentration (MBC) of 50 mg/mL for both of them, which will need further efforts to improve the performance. However, GT-Ag@MSN exhibited a notable 1,1-Diphenyl-2-picrylhydrazyl (DPPH) scavenging ability of 74.7 ± 1.6% at a concentration of 250 μg/mL, and its reducing power in the range of 10–100 mg was greater than that of ascorbic acid at 10–100 μg/mL. This study proposes a new waste-to-wealth strategy that utilizes purified silicon and silver from recycling used PV modules, encouraging the advancement of PV waste recycling and reuse technology. Full article

Sweet potato (Ipomoea batatas (L.) Lam.; SP) flour enhances food nutrition and bioactivity while functioning as a thickening/gelling agent. This study investigated the impact of two drying methods [hot-air (75 °C/20 h) and freeze-drying (−41–30 °C/70 h)] on the physical–functional properties of flours from three SP varieties: Bonita (white-fleshed), Bellevue (orange-fleshed), and NP1648 (purple-fleshed). Particle size, morphology, water/oil absorption capacities (WAC/OAC), bulk density, swelling power (SwP), water solubility (WS), foaming/emulsifying properties, least gelation concentration (LGC), and gelatinisation temperature (GT) were analysed. Both the drying method and variety significantly influenced these properties. Hot-air-dried flours exhibited bimodal particle distribution, compact microstructure, and aggregated starch granules, yielding higher WAC (≈3.2 g/g) and SwP (≈3.6 g/g). Freeze-dried flours displayed smaller particles, porous microstructure, and fragmented granules, enhancing OAC (≈3.0 g/g) and foaming capacity (≈17.6%). GT was mainly variety-dependent, increasing as Bellevue (74.3 °C) < NP1648 (78.5 °C) < Bonita (82.8 °C), all exceeding commercial potato starch (68.7 °C). NP1648 required lower LGC (10% vs. 16% for others). All flours exhibited high WS (24–39.5%) and emulsifying capacity (≈44%). These results underscore the importance of selecting the appropriate drying method and variety to optimise SP flour functionality for targeted food applications. Freeze-dried flours might suit aerated/oil-retentive products, while hot-air-dried flours could be ideal for moisture-sensitive formulations. Full article

In this paper, a novel technical route, namely combining the low-pressure exhaust gas recirculation (LP-EGR) and variable compression ratio (VCR), is proposed to address the inferior fuel economy for marine dual-fuel engines of low-pressure gas injection in diesel mode. To validate the applicability of the proposed technical route, firstly, a zero-dimensional/one-dimensional (0-D/1-D) engine simulation model with a predictive combustion model DI-Pulse is established using GT-Power. Then, parametric investigations on two LP-EGR schemes, which is implemented with either a back-pressure valve (LP-EGR-BV) or a blower (LP-EGR-BL), are performed to qualitatively identify the combined impacts of exhaust gas recirculation (EGR) and compression ratio (CR) on the combustion process, turbocharging system, and nitrogen oxides (NOx)-brake specific fuel consumption (BSFC) trade-offs. Finally, an optimization strategy is formulated, and an optimization program based on response surface methodology (RSM)–particle swarm optimization (PSO) is designed with the aim of improving fuel economy while meeting Tier III and various constraint conditions. The results of the parametric investigations reveal that the two LP-EGR schemes exhibit opposite impacts on the turbocharging system. Compared with the LP-EGR-BV, the LP-EGR-BL can achieve a higher in-cylinder pressure level. NOx-BSFC trade-offs are observed for both LP-EGR schemes, and the VCR is confirmed to be a viable approach for mitigating the penalty on BSFC caused by EGR. The optimization results reveal that for LP-EGR-BV, compared with the baseline engine, the optimized BSFC decreases by 10.16%, 11.95%, 10.32%, and 9.68% at 25%, 50%, 75%, and 100% maximum continuous rating (MCR), respectively, whereas, for the LP-EGR-BL scheme, the optimized BSFC decreases by 10.11%, 11.93%, 9.93%, and 9.58%, respectively. Furthermore, the corresponding NOx emissions level improves from meeting Tier II regulations (14.4 g/kW·h) to meeting Tier III regulations (3.4 g/kW·h). It is roughly estimated that compared to the original engine, both LP-EGR schemes achieve an approximate reduction of 240 tons in annual fuel consumption and save annual fuel costs by over USD 100,000. Although similar fuel economy is obtained for both LP-EGR schemes, LP-EGR-BV is superior to LP-EGR-BL in terms of structure complexity, initial cost, maintenance cost, installation space requirement, and power consumption. The findings of this study provide meaningful theoretical supports for the implementation of the proposed technical route in real-world engines. Full article

The increasing demand for efficient and environmentally friendly diesel engines necessitates advanced simulation tools, with Gamma Technologies’ GT-POWER emerging as a leading software suite for this purpose. This review paper examines the capabilities of GT-POWER for modelling diesel engines, exploring its fundamental principles, user interface, modelling techniques, and simulation capabilities, alongside comparisons with other formidable simulation tools. Moreover, various case studies from the literature are presented to illustrate its application. While there are some shortfalls within the context of GT-POWER, such as the need for further exploration of underutilized areas, the current focus on primarily 1D and multi-zone modelling requires expansion. Coupling GT-POWER with other simulation software for multiphysics analyses—such as CFD for combustion, structural analysis for component stress, fluid flow, and heat transfer—offers significant potential; however, this integration remains largely unexploited. Despite its limitations, the results consistently reveal the software’s versatility in optimizing engine performance across diverse applications, including component design, alternative fuel evaluations, and integration with various technologies such as MATLAB/Simulink, Artificial Neural Networks, and Python. The consistent findings across multiple studies further confirm GT-POWER’s effectiveness as a leading simulation tool for advancing diesel engine technology. Ultimately, this study bridges the gap between theoretical understanding and practical application, making it a valuable resource for researchers and engineers in the field of internal combustion engine optimization. Full article