Thermostat-assisted continuously-tempered Hamiltonian Monte Carlo for Bayesian learning

We propose a new sampling method, the thermostat-assisted continuously-tempered Hamiltonian Monte Carlo, for Bayesian learning on large datasets and multimodal distributions. It simulates the Nos\'e-Hoover dynamics of a continuously-tempered Hamiltonian system built on the distribution of interest. A significant advantage of this method is that it is not only able to efficiently draw representative i.i.d. samples when the distribution contains multiple isolated modes, but capable of adaptively neutralising the noise arising from mini-batches and maintaining accurate sampling. While the properties of this method have been studied using synthetic distributions, experiments on three real datasets also demonstrated the gain of performance over several strong baselines with various types of neural networks plunged in

The study of a novel magnetic crankshaft

This paper introduces a revolutionary mechanism, the Four-Translator Magnetic Crankshaft (FTMC), designed to address inherent limitations of the Magnetic Lead Screw (MLS) in energy storage and driving efficiency. The FTMC combines features of the MLS and a traditional cross crankshaft, enabling efficient energy conversion between continuous rotatory motions and reciprocating linear motions. The study presents the FTMC's working principle, theoretical calculations, 3D finite element analysis (FEA) validation, and comprehensive performance analyses. The FTMC's rotor, featuring a unique magnet array, allows for continuous rotation while the four translators reciprocate with a 90-degree phase difference. This breakthrough resolves the energy storage challenge faced by MLS, leading to enhanced efficiency and frequency. The paper explores the FTMC's static and dynamic performance, demonstrating its superiority in achieving 4.6 times higher reciprocating speeds or 93.3 % lower driving torque compared to the same-sized MLS in the limiting case. Furthermore, the study proposes an innovative assembly design with a 2-air gap topology, addressing potential radial attraction issues and reducing translator mass. The anticipated performance under ideal conditions, based on 3D FEA results, showcases the FTMC's ability to transmit about 1.4 kW power with efficiencies exceeding 75 % at rated load angles and 30 Hz driving frequencies. Theoretical insights into the FTMC's capabilities open promising avenues for future research and prototyping. Experimental validation is recommended to confirm the mechanism's maximum driving ability, offering significant advancements in Magnetic Lead Screw and high-speed magnetic drive systems. Future studies should focus on prototype manufacturing and controllable load test bench design to validate the presented theoretical analysis

A distributed renewable power system with hydrogen generation and storage for an island

This study aimed to find a distributed renewable power system with hydrogen generation and storage to meet the current Isle of Rum's energy demands. Five different systems (Case 2–6) were evaluated compared to the current power system (Case 1), with the inclusion of a hydrogen generation and storage subsystem acting as an energy storage medium in Case 3, 4, 5 and 6. Case 2 exhibited a 96.2% reduction in diesel consumption. Case 3 and 4 achieved a fully renewable generation mix through the addition of a hydrogen subsystem comprised of a 28 kW PEM electrolyser, 120 kg compressed storage and modified gen-set. Case 5 and 6 also achieved a fully renewable generation mix, meeting the domestic heating and full heating demands of the island respectively through the integration of heat pumps. Economic analysis showed that Case 2 exhibited the lowest cost, with a LCOE of £3.02/kWh, a 43% reduction from Case 1. Both Case 3 and Case 4 also had a lower LCOE than Case 1 of £5.02/kWh and £4.37/kWh respectively. This shows that the hydrogen subsystem designed can be an economically viable option despite its currently high CAPEX. Both Case 5 and 6 had the highest CAPEX of all systems, due to the additional generation technology required to meet the additional heating demand. However, they achieved the lowest LCOE at £1.86/kWh and £0.76/kWh, due to the high efficiency exhibited by the heat pumps used for the heating load

Applications of Oxyhydrogen, Direct Water Injection, and Early-Intake Valve Closure Technologies on a Petrol Spark Ignition Engine—A Path towards Zero-Emission Hydrogen Internal Combustion Engines

This study investigates the performance of a 4-MIX engine utilizing hydrogen combustion in pure oxygen, water injection, and the application of the early-intake valve closure (EIVC) Miller cycle. Transitioning from a standard petrol–oil mix to hydrogen fuel with pure oxygen combustion aims to reduce emissions. Performance comparisons between baseline and oxyhydrogen engines showed proportional growth in the energy input rate with increasing rotational speed. The oxyhydrogen engine exhibited smoother reductions in brake torque and thermal efficiency as rotational speed increased compared to the baseline, attributed to hydrogen’s higher heating value. Water injection targeted cylinder and exhaust temperature reduction while maintaining a consistent injected mass. The results indicated a threshold of around 2.5 kg/h for the optimal water injection rate, beyond which positive effects on engine performance emerged. Investigation into the EIVC Miller cycle revealed improvements in brake torque, thermal efficiency, and brake specific fuel consumption as early-intake valve closure increased. Overall, the EIVC model exhibited superior energy efficiency, torque output, and thermal efficiency compared to alternative models, effectively addressing emissions and cylinder temperature concerns

Can Negative Travel Habits Hinder Positive Travel Behavioural Change under Beijing Vehicle Restrictions?

Given the rapid development of large cities, the residents faced with pressure both at work and in their personal lives tend to solidify their choice of transport modes and form personal travel habits, which in turn leads to higher requirements for urban traffic management. Based on the modified Theory of Planned Behaviour, the structural equation method is employed to explore people’s travel behaviour. It is found that policy attitude, perceived behaviour control, and subjective norms comprehensively affect the residents’ travel intentions under the Vehicle Restrictions in place in Beijing. The residents without private cars display a stronger intention to change their travel choices under the policies. When considering the mediating effect of travel habits between travel intention and travel choice, the impact of the restrictive policies is weakened. Compared with lower-income people, those with higher incomes demonstrate more stable travel habits in response to the effects of the restrictions. The higher the income, the greater the dependence on private cars exhibited by the residents. To summarize, people’s travel habits weaken to some extent the effects of the restrictive policies. Such policies should be created with the explicit aim of gradually changing the people’s habits.</p

Can Negative Travel Habits Hinder Positive Travel Behavioural Change under Beijing Vehicle Restrictions?

Given the rapid development of large cities, the residents faced with pressure both at work and in their personal lives tend to solidify their choice of transport modes and form personal travel habits, which in turn leads to higher requirements for urban traffic management. Based on the modified Theory of Planned Behaviour, the structural equation method is employed to explore people’s travel behaviour. It is found that policy attitude, perceived behaviour control, and subjective norms comprehensively affect the residents’ travel intentions under the Vehicle Restrictions in place in Beijing. The residents without private cars display a stronger intention to change their travel choices under the policies. When considering the mediating effect of travel habits between travel intention and travel choice, the impact of the restrictive policies is weakened. Compared with lower-income people, those with higher incomes demonstrate more stable travel habits in response to the effects of the restrictions. The higher the income, the greater the dependence on private cars exhibited by the residents. To summarize, people’s travel habits weaken to some extent the effects of the restrictive policies. Such policies should be created with the explicit aim of gradually changing the people’s habits.</p

A Study of AI Population Dynamics with Million-agent Reinforcement Learning

We conduct an empirical study on discovering the ordered collective dynamics obtained by a population of intelligence agents, driven by million-agent reinforcement learning. Our intention is to put intelligent agents into a simulated natural context and verify if the principles developed in the real world could also be used in understanding an artificially-created intelligent population. To achieve this, we simulate a large-scale predator-prey world, where the laws of the world are designed by only the findings or logical equivalence that have been discovered in nature. We endow the agents with the intelligence based on deep reinforcement learning (DRL). In order to scale the population size up to millions agents, a large-scale DRL training platform with redesigned experience buffer is proposed. Our results show that the population dynamics of AI agents, driven only by each agent's individual self-interest, reveals an ordered pattern that is similar to the Lotka-Volterra model studied in population biology. We further discover the emergent behaviors of collective adaptations in studying how the agents' grouping behaviors will change with the environmental resources. Both of the two findings could be explained by the self-organization theory in nature.Comment: Full version of the paper presented at AAMAS 2018 (International Conference on Autonomous Agents and Multiagent Systems