Research on Energy Transmission Mechanism of the Electro-Hydraulic Servo Pump Control System

The electro-hydraulic servo pump control system (EHSPCS) is a volume control system that uses a permanent magnet synchronous motor (PMSM) with a fixed displacement pump to directly drive and control the hydraulic cylinder. The energy transmission law of the system is very complicated due to the transformation of electrical, mechanical and hydraulic energy as well as other energy fields, and qualitative analysis of the energy transfer efficiency is difficult. Energy transfer analysis of the EHSPCS under different working conditions and loads is proposed in this paper. First, the energy flow transfer mechanism was analyzed, and the mathematical and energy transfer models of the key components of the system were established to explore the energy characteristic state transition rule. Second, a power bond diagram model was built, its state equation and state matrix were deduced, and a system simulation model was built. Finally, combined with the EHSPCS experimental platform, simulation experiments were carried out on the dynamic position following and steady-state position holding conditions of the system, and the variation rules of the power of each energy characteristic state and the system energy transfer efficiency under different loads were obtained. The research results provide a foundation for the study of power matching and energy-saving mechanism of the EHSPCS.

Designing a Bonus-Malus system reflecting the claim size under the dependent frequency–severity model

In the auto insurance industry, a Bonus-Malus System (BMS) is commonly used as a posteriori risk classification mechanism to set the premium for the next contract period based on a policyholder's claim history. Even though the recent literature reports evidence of a significant dependence between frequency and severity, the current BMS practice is to use a frequency-based transition rule while ignoring severity information. Although Oh et al. [(2020). Bonus-Malus premiums under the dependent frequency-severity modeling. Scandinavian Actuarial Journal 2020(3): 172–195] claimed that the frequency-driven BMS transition rule can accommodate the dependence between frequency and severity, their proposal is only a partial solution, as the transition rule still completely ignores the claim severity and is unable to penalize large claims. In this study, we propose to use the BMS with a transition rule based on both frequency and size of claim, based on the bivariate random effect model, which conveniently allows dependence between frequency and severity. We analytically derive the optimal relativities under the proposed BMS framework and show that the proposed BMS outperforms the existing frequency-driven BMS. Later, numerical experiments are also provided using both hypothetical and actual datasets in order to assess the effect of various dependencies on the BMS risk classification and confirm our theoretical findings.

Analysis of node2vec random walks on networks

Random walks have been proven to be useful for constructing various algorithms to gain information on networks. Algorithm node2vec employs biased random walks to realize embeddings of nodes into low-dimensional spaces, which can then be used for tasks such as multi-label classification and link prediction. The performance of the node2vec algorithm in these applications is considered to depend on properties of random walks that the algorithm uses. In the present study, we theoretically and numerically analyse random walks used by the node2vec. Those random walks are second-order Markov chains. We exploit the mapping of its transition rule to a transition probability matrix among directed edges to analyse the stationary probability, relaxation times in terms of the spectral gap of the transition probability matrix, and coalescence time. In particular, we show that node2vec random walk accelerates diffusion when walkers are designed to avoid both backtracking and visiting a neighbour of the previously visited node but do not avoid them completely.

Modelling Land Cover Changes in Peri-Urban Areas: A Case Study of George Town Conurbation, Malaysia

Drastic growth of urban populations has caused expansion of peri-urban areas—the transitional zone between a city and its hinterland. Although urbanisation may bring economic opportunities and improve infrastructure in an area, uncontrolled urban expansion towards peri-urban areas will negatively impact the environment and the community living within the area. Malaysia, for example, has become one of the most urbanised countries in East Asia. However, cities in Malaysia are relatively small and less densely populated compared with other cities in East Asia. This indicates that urban expansion has been sprawling towards peri-urban areas, and not being controlled and properly managed. To ensure urban expansions occur sustainably, urban growth boundary (UGB) can potentially be used as a mechanism to contain and limit urban expansion, and allow urban growth to be planned to achieve sustainable development. A scientific approach is essential to determine an UGB that allows future growth to be predicted and taken into consideration. Potentially, urban spatial models have been widely used to plan and predict future urban expansions. George Town Conurbation, the second largest urban conurbation in Malaysia, has been chosen as the study area in this study. This study aims to demonstrate the application of a GIS-Cellular Automata model, known as FutureSim, which was developed to simulate land cover changes and generate a designated UGB for this area. The model was developed based on the transition rule derived from land cover changes, from 2010 to 2018, and then used to predict future land cover changes under two different planning scenarios—compact growth and urban sprawl scenarios. With the accuracy of the model exceeding 74%, FutureSim was used to predict land cover change until 2030. The model can potentially be used to assist planners and policymakers to make decisions on the allocation of sustainable land use and planning for rapidly developing regions.

On the effect of detwinning-induced plasticity in compressive cyclic loading of NiTi shape memory alloys

A new inelastic mechanism, detwinning-induced plasticity (DIP), is proposed to model the response of NiTi SMAs to cyclic loading, based on thermodynamic considerations. DIP is incorporated into a constitutive framework for NiTi SMA. The constitutive framework also includes well established inelastic mechanisms of phase transformation,transformation-induced plasticity, residual martensite, and detwinning. The model is constructed at the single crystal scale using the framework of thermodynamics and a crystal plasticity formulation. An explicit scale-transition rule is adopted for the simulation of polycrystalline materials, allowing direct comparison of the model predictions with published experimental test data. Thermodynamic considerations result in a strong contribution of DIP for cyclic loading regimes where compressive stress occurs during part of the loading cycle. However, the contribution of DIP is negligible for cyclic loading regimes that result exclusively in tensile stress. This predicted dependence of DIP on compression, but not on tension, is strongly supported by experimental cyclic loading results. Inclusion of DIP results in improved prediction of experimentally observed NiTi SMAs behavior, including strain-controlled cyclic compression-unloading and cyclic tension-unloading tests and stress-controlled cyclic tension-compression and tension-unloading tests. During the first loading cycle the contribution of DIP is not significant in any loading regimes. However, in cases where compressive stress occurs during part of the loading cycle, DIP contributes strongly to the material response from the second cycle onwards. In strain-controlled cyclic compression-unloading tests DIP leads to a less negative peak stress and a more negative residual strain following several loading cycles. In stress- controlled tension-compression cyclic loading DIP leads to a reduction of peak and residual strains.

ANT COLONY OPTIMIZATION PARAMETER SELECTION FOR SHORTEST PATH PROBLEM

The shortest path problem has been studied to be solved through diverse deterministic and also stochastic approaches such as Ant Colony Optimization. One of the most challenging issues with the implication of Ant Colony Optimization to solve the shortest path problem is parameter selection and tuning which is found crucial to improve the computational performance of problem-solving. To tune parameters, it is vital to observe the response of each parameter to different values and study their effect on the final results. In this research, two experiments are designed and conducted to study the behavior of parameters in terms of generated results and computational performance. In the first experiment, evaporation, updating, and transition rule parameters are studied by iterative execution of shortest path generation between nodes considering different parameter values. In the second experiment, the number of initial ants is studied. Inspecting the results, it is observed that to avoid premature stagnation decreasing α value is recommended. On the other hand, ρ is observed to be considered for tuning of speed and number of diffusions of the algorithm. Moreover, it is realized that a high Q value would result in more correct results. Inspecting the initial number of ants, a threshold is realized where increasing the number of ants over this threshold would drastically result in more optimized paths.

Modelling Consciousness within Mental Monism: An Automata-Theoretic Approach

Models of consciousness are usually developed within physical monist or dualistic frameworks, in which the structure and dynamics of the mind are derived from the workings of the physical brain. Little attention has been given to modelling consciousness within a mental monist framework, deriving the structure and dynamics of the mental world from primitive mental constituents only—with no neural substrate. Mental monism is gaining attention as a candidate solution to Chalmers’ Hard Problem on philosophical grounds, and it is therefore timely to examine possible formal models of consciousness within it. Here, I argue that the austere ontology of mental monism places certain constraints on possible models of consciousness, and propose a minimal set of hypotheses that a model of consciousness (within mental monism) should respect. From those hypotheses, it would be possible to construct many formal models that permit universal computation in the mental world, through cellular automata. We need further hypotheses to define transition rules for particular models, and I propose a transition rule with the unusual property of deep copying in the time dimension.

Fundamentals

The physical and structural fundamentals of polymorphism are introduced, including a review of the phase rule and the thermodynamic relations in polymorphs. The latter are used to introduce energy–temperature diagrams, leading to the definition of the concepts enantiotropism and monotropism describing the thermodynamic relationships between and among polymorphs with appropriate examples. The alternate representation of phase diagram in terms of pressure and temperature is also presented. These lead to a number of rules regarding the relationships between polymorphs and ways to understand and predict some important physical properties: the heat-of-transition rule, the heat-of-fusion rule, the entropy-of-fusion rule, the heat-capacity rule, the density rule, and the infrared rule. Structural aspects include the distinction between crystal form and crystal habit and methods for characterizing and comparing structures in polymorphic systems. Current developments are discussed that deal with the ramifications of nanoscale situations on structural concepts and thermodynamic relationships.

Modelling Consciousness within Mental Monism: An Automata-Theoretic Approach

Models of consciousness are usually developed within physical monist or dualistic frameworks, in which the structure and dynamics of the mind derive from the workings of the physical world (in particular, the brain). Little attention has been given to modeling within a mental monist framework, deriving the structure and dynamics of the mental world from primitive mental constituents only. Mental monism is gaining attention as a candidate solution to Chalmers’ Hard Problem, and it is therefore timely to examine possible formal models of consciousness within it. Here, we propose a minimal set of hypotheses that any credible model of consciousness (within mental monism) should respect. From those hypotheses, it is feasible to construct many formal models that permit universal computation in the mental world, through cellular automata. We need further hypotheses to define transition rules for particular models, and we propose a transition rule with the unusual property of deep copying in the time dimension. In conclusion, we hope to dispel the notion that mental monism requires a deus ex machina, by showing that a parsimonious set of assumptions can yield a naturalistic and computationally potent mental world.