Publications

In recent years there has been great interest in Wankel-type rotary engines which are one of the most suitable power sources for unmanned aerial vehicle (UAV) applications due to their high power-to-size and power-to-weight ratios. The purpose of the present study was to investigate the potential of a hydrogen enrichment strategy for the improvement of the performance and reduction of the emissions of Wankel engines. The main motivation behind this study was to make Wankel engines which are already very advantageous for UAV applications even more advantageous by applying the hydrogen enrichment technique. In this study hydrogen addition was implemented in a spark-ignition rotary engine model operating at a constant engine speed of 6000 rpm. The mass fraction of hydrogen in the intake gradually increased from 0% to 10%. Simulation results revealed that addition of hydrogen to the fuel accelerated the flame propagation and increased the burning speed of the fuel the combustion temperature and the peak pressure in the working chamber. These phenomena had a very positive effect on the performance and emissions of the Wankel engine. The indicated mean effective pressure (IMEP) increased by 8.18% and 9.68% and the indicated torque increased by 6.15% and 7.99% for the 5% and 10% hydrogen mass fraction cases respectively compared to those obtained with neat gasoline. In contrast CO emissions were reduced by 33.35% and 46.21% and soot emissions by 11.92% and 20.06% for 5% and 10% hydrogen additions respectively. NOx emissions increased with the application of the hydrogen enrichment strategy for the Wankel engine.

Countries with high energy demand but limited renewable energy potential are planning to meet part of their future energy needs by importing green hydrogen. For potential exporting countries in addition to sufficient renewable resources industrial preconditions are also relevant for the successful implementation of green hydrogen production value chains. A list of 36 “Green H2 Products” needed for stand-alone hydrogen production plants was defined and their economic complexity was analyzed using international trade data from 1995 to 2019. These products were found to be comparatively complex to produce and represent an opportunity for countries to enter new areas of the product space through green diversification. Large differences were revealed between countries in terms of industrial preconditions and their evolution over time. A detailed analysis of nine MENA countries showed that Turkey and Tunisia already possess industrial know-how in various green hydrogen technology components and perform only slightly worse than potential European competitors while Algeria Libya and Saudi Arabia score the lowest in terms of calculated hydrogen-related green complexity. These findings are supported by statistical tests showing that countries with a higher share of natural resources rents in their gross domestic product score significantly lower on economic and green complexity. The results thus provide new perspectives for assessing the capabilities of potential hydrogen-producing countries which may prove useful for policymakers and investors. Simultaneously this paper contributes to the theory of economic complexity by applying its methods to a new subset of products and using a dataset with long-term coverage.

Industries across the world are making the transition to net-zero carbon emissions as government policies and strategies are proposed to mitigate the impact of climate change on the planet. As a result the use of hydrogen as an energy source is becoming an increasingly popular field of research particularly in the aviation sector where an alternative green renewable fuel to the traditional hydrocarbon fuels such as kerosene is essential. Hydrogen can be stored in multiple ways including compressed gaseous hydrogen cryo-compressed hydrogen and cryogenic liquid hydrogen. The infrastructure and storage of hydrogen will play a pivotal role in the realisation of large-scale conversion from traditional fuels with safety being a key consideration. This paper provides a review on previous work undertaken to study the characterisation of both unignited and ignited hydrogen jets which are fundamental phenomena for the utilisation of hydrogen. This includes work that focuses on the near-field flow structure dispersion in the far-field ignition and flame characteristics with multi-physics. The safety considerations are also included. The theoretical models and computational fluid dynamics (CFD) multiphase and reactive flow approaches are discussed. Then an overview of previous experimental work is provided before focusing the review on the existing computational results with comparison to experiments. Upon completion of this review it is highlighted that the complex near-field physics and flow phenomena are areas lacking in research. The near-field flow properties and characteristics are of significant importance with respect to the ignition and combustion of hydrogen.

Hybrid electric vehicles are currently one of the most effective ways to increase the efficiency and reduce the pollutant emissions of internal combustion engines. Green hydrogen produced with renewable energies is an excellent alternative to fossil fuels in order to drastically reduce engine pollutant emissions. In this work the author proposes the implementation of a hydrogen-fueled engine in a hybrid vehicle; the investigated hybrid powertrain is the power-split type in which the engine two electric motor/generators and the drive shaft are coupled together by a planetary gear set; this arrangement allows the engine to operate independently from the wheels and thus to exploit the best efficiency operating points. A set of numeric simulations were performed in order to compare the gasoline-fueled engine with the hydrogen-fueled one in terms of the thermal efficiency and total energy consumed during a driving cycle. The simulation results show a mean engine efficiency increase of around 17% when fueled with hydrogen with respect to gasoline and an energy consumption reduction of around 15% in a driving cycle.

In order to adopt water electrolyzers as a main hydrogen production system it is critical to develop inexpensive and earth-abundant catalysts. Currently both half-reactions in water splitting depend heavily on noble metal catalysts. This review discusses the proton exchange membrane (PEM) water electrolysis (WE) and the progress in replacing the noble-metal catalysts with earth-abundant ones. The efforts within this field for the discovery of efficient and stable earth-abundant catalysts (EACs) have increased exponentially the last few years. The development of EACs for the oxygen evolution reaction (OER) in acidic media is particularly important as the only stable and efficient catalysts until now are noble-metal oxides such as IrOx and RuOx. On the hydrogen evolution reaction (HER) side there is significant progress on EACs under acidic conditions but there are very few reports of these EACs employed in full PEM WE cells. These two main issues are reviewed and we conclude with prospects for innovation in EACs for the OER in acidic environments as well as with a critical assessment of the few full PEM WE cells assembled with EACs.

This study presents methodology for the evaluation of appropriateness of a hydrogen generator for gas production in multiple distributed plants based on renewable energy sources. The general idea is to form hydrogen clusters integrated with storage and transportation. The paper focuses on the financial viability of the plants presenting the results of economic evaluation together with sensitivity analysis for various economic factors. The analyzed case study proves that over a wide range of parameters alkaline electrolyzers show favorable economic characteristics however a PEM-based plant is more resilient to changes in the price of electricity which is the main cost component in hydrogen generation. The study is enriched with an experimental investigation of low-pressure storage methods based on porous metal hydride tanks. The effectiveness of the tanks (β) compared to pressurized hydrogen tanks in the same volume and pressure is equal to β = 10.2. A solution is proposed whereby these can be used in a distributed hydrogen generation concept due to their safe and simple operation without additional costly equipment e.g. compressors. A method for evaluation of the avoided energy consumption as a function of the effectiveness of the tanks is developed. Avoided energy consumption resulting from implementing MH tanks equals 1.33 – 1.37 kWh per kilogram of hydrogen depending on the number of stages of a compressor. The methods proposed in this paper are universal and can be used for various green hydrogen facilities.

High-accuracy gas dispersion models are necessary for predicting hydrogen movement and for reducing the damage caused by hydrogen release accidents in chemical processes. In urban areas where obstacles are large and abundant computational fluid dynamics (CFD) would be the best choice for simulating and analyzing scenarios of the accidental release of hydrogen. However owing to the large computation time required for CFD simulation it is inappropriate in emergencies and real-time alarm systems. In this study a non-linear surrogate model based on deep learning is proposed. Deep convolutional layer data-driven autoencoder and batch normalized deep neural network is used to analyze the effects of wind speed wind direction and release degree on hydrogen concentration in real-time. The typical parameters of hydrogen diffusion accidents at hydrogen refuelling stations were acquired by CFD numerical simulation approach and a database of hydrogen diffusion accident parameters is established. By establishing an appropriate neural network structure and associated activation function a deep learning framework is created and then a deep learning model is constructed. The accuracy and timeliness of the model are assessed by comparing the results of the CFD simulation with those of the deep learning model. To develop a dynamic reconfiguration prediction model for the hydrogen refuelling station diffusion scenario the algorithm is continuously enhanced and the model is improved. After training is finished the model's prediction time is measured in seconds which is 105 times quicker than field CFD simulations. The deep learning model of hydrogen release in hydrogen refuelling stations is established to realize timely and accurate prediction and simulation of accident consequences and provide decision-making suggestions for emergency rescue and personnel evacuation which is of great significance for the protection of human life health and property safety.

Power-to-gas technology can be used to convert excess power from renewable energies to hydrogen by means of water electrolysis. This hydrogen can serve as “chemical energy storage” and be converted back to electricity or fed into the natural gas grid. In the presented study a leak in a household pipe in a single-family house with a 13 KW heating device was experimentally investigated. An admixture of up to 40% hydrogen was set up to produce a scenario of burning leakage. Due to the outflow and mixing conditions a lifted turbulent diffusion flame was formed. This led to an additional examination point and expanded the aim and novelty of the experimental investigation. In addition to the fire safety experimental simulation of a burning leakage the resulting complex properties of the flame namely the lift-off height flame length shape and thermal radiation have also been investigated. The obtained results of this show clearly that as a consequence of the hydrogen addition the main properties of the flame such as lifting height flame temperature thermal radiation and total heat flux densities along the flame have been changed. To supplement the measurements with thermocouples imaging methods based on the Sobel gradient were used to determine the lifting height and the flame length. In order to analyze the determined values a probability density function was created.

To solve the problems of low utilization of biomass and uncertainty and intermittency of wind power (WP) in rural winter an interval optimization model of a rural integrated energy system with biogas fermentation and electrolytic hydrogen production is constructed in this paper. Firstly a biogas fermentation kinetic model and a biogas hydrogen blending model are developed. Secondly the interval number is used to describe the uncertainty of WP and an interval optimization scheduling model is developed to minimize daily operating cost. Finally a rural integrated energy system in Northeast China is taken as an example and a sensitivity analysis of electricity price gas production and biomass price is conducted. The simulation results show that the proposed strategy can significantly reduce the wind abandonment rate and improve the economy by 3.8–22.3% compared with conventional energy storage under optimal dispatch.

The main purpose of this paper is the techno-economic analysis of hydrogen production from biogas via steam reforming in a pilot plant. Process flow modeling based on mass and energy balance is used to estimate the total equipment purchase and operating costs of hydrogen production. The pilot plant installation produced 250.67 kg/h hydrogen from 1260 kg/h biomethane obtained after purification of 4208 m3/h biogas using a heat and mass integration process. Despite the high investment cost the plant shows a great potential for biomethane reduction and conversion to hydrogen an attractive economic path with ecological possibilities. The conversion of waste into hydrogen is a possibility of increasing importance in the global energy economy. In the future such a plant will be expanded with a CO2 reduction module to increase economic efficiency and further reduce greenhouse gases in an economically viable manner.