Sharif Digital Repository

The aim of this research is the optimisation of full-toroidal continuously variable transmission (CVT) in conjunction with the fixed ratio (FR) mechanism, while the optimisation objective is to minimise fuel consumption (FC) of the vehicle in the new European driving cycle. After the dynamic analysis of the power train, a computer model is developed to simulate contact between CVT elements and consequently calculate its efficiency. Then an algorithm is presented to calculate FC of the vehicle in the driving cycle. Then, an optimisation using particle swarm optimisation on the CVT geometry and FR mechanism (which is embedded between CVT and final drive) is carried out to minimise FC. It is... 

In this paper, we propose a hybrid algorithm including Genetic Algorithm (GA), Ant Colony Optimisation (ACO), and Simulated Annealing (SA) metaheuristics for increasing the contrast of images. In this way, contrast enhancement is obtained by global transformation of the input intensities. Ant colony optimisation is used to generate the transfer functions which map the input intensities to the output intensities. Simulated annealing as a local search method is utilised to modify the transfer functions generated by ant colony optimisation. And genetic algorithm has the responsibility of evolutionary process of antsE characteristics. The employed fitness function operates automatically and... 

This paper presents the scheduling optimisation of cargo trains by hybrid computer simulation (CS) and genetic algorithm. Scheduling cargo trains is based on the timetable of passenger trains that have priority in relation to cargo trains. System modelling is accomplished by Visual SLAM by considering time limitations, queue priority and limited station lines. Time limitations define that a cargo train is permitted to travel from station i to j if scheduled passenger trains have completed the travel from station i to j. Queue priority means that passenger trains have priority over cargo trains. In addition, each station has a limited storage track. In addition, all repair, maintenance,... 

Bayesian regularised genetic neural network (BRGNN) has been used for modelling the inhibition activity of 141 biphenylalanine derivatives as integrin antagonists. Three local pattern search (PS) methods, simulated annealing and threshold acceptance were combined with BRGNN in the form of a hybrid genetic algorithm (HGA). The results obtained revealed that PS is a suitable method for improving the ability of BRGNN to break out from the local minima. The proposed HGA technique is able to retrieve important variables from complex systems and nonlinear search spaces for optimisation. Two models with 8-3-1 artificial neural network (ANN) architectures were developed for describingα 4β 7 and α 4β... 

This paper addresses the problem of optimal state-feedback design for a class of non-linear systems. The method is applicable to all non-linear systems which can be linearised using the method of state-feedback linearisation. The alternative is to use linear optimisation techniques for the linearised equations, but then there is no guarantee that the original non-linear system behaves optimally. The authors use feedback linearisation technique to linearise the system and then design a state feedback for the feedback-linearised system in such a way that it ensures optimal performance of the original non-linear system. The method cannot ensure global optimality of the solution but the global... 

The concept of smart grid (SG) has been introduced to improve the operation of the power systems. In modern structures of power systems, different reasons prompt researchers to suggest integrated analysis of multi-carrier energy systems. Considering synergy effects of the couplings between different energy carriers and utilising intelligent technologies for monitoring and controlling of energy flow may change energy system management in the future. In this paper, we propose a new solution which is entitled smart energy hub (SEH) that models a multi-carrier energy system in a SG. SEH solutions allow homeowners to manage their energy consumption to reduce their electricity and gas bill. We... 

Delay in communication wires causes design iterations in system-on-chip. Latency-insensitive design copes with this issue by encapsulating each core in a shell wrapper and inserting buffers in the wires to separate the design of core from that of communication wires. Scheduling-based latency-insensitive protocol is a methodology which employs shift registers for periodic clock gating of blocks instead of the shell wrappers. In many cases, the bit sequences inside the shift registers are too long and therefore consume a large area. This study presents a heuristic algorithm that optimises the bit sequences and produces them with shorter lengths compared with the existing method. The algorithm... 

This research proposes a new method for optimisation of a power generation system based on exergy fuel cost and external social cost of air pollution. A thermodynamic model is provided to estimate the outlet mass flow rates of CO2, CO, NO and NO2 for a gas turbine based on maximising the first and second law efficiencies and minimising the objective function. Results show that inclusion of the external social cost of air pollution increases the optimum excess air ratio if temperature constraint due to metallurgical consideration is disregarded. Otherwise external social cost of air pollution is independent of optimised conditions  

The first step in the accepted methods of overhead transmission line insulation coordination is to specify a reliability criterion, and then based on this constraint the most economic insulation design is sought. While the objective of an optimal insulation design method is to find an insulation design that minimises the total cost (the sum of the installation cost, operational cost and cost of failure), each of the cost components can be determined on a per-year basis taking into account the equipment's lifetimes. In this paper, through application of ATP software and realising the total cost of different transmission line designs, a set of alternative insulation designs using various surge... 

In this paper, a new interaction prediction approach for hierarchical control of non-linear large-scale systems is presented. The proposed approach uses a new gradient-type coordination scheme which is robust with respect to the parameters' variation, and also has a good convergence rate. In classical coordination strategies, which can be divided into the gradient-type and substitution-type approaches, it is not possible to improve the robustness and the convergence rate at the same time, since by increasing one the other decreases. The proposed approach has the main advantages of the gradient-type algorithms in being independent of the parameter's variation and also the initial guess of the... 

In this study, hydrogen generation is maximised by optimising the size and the operating conditions of an electrolyser (EL) directly connected to a photovoltaic (PV) module at different irradiance. Due to the variations of maximum power points of the PV module during a year and the complexity of the system, a nonlinear approach is considered. A mathematical model has been developed to determine the performance of the PV/EL system. The optimisation methodology presented here is based on the particle swarm optimisation algorithm. By this method, for the given number of PV modules, the optimal sizeand operating condition of a PV/EL system areachieved. The approach can be applied for different... 

Lead-acid battery is a storage technology that is widely used in photovoltaic (PV) systems. Battery charging and discharging profiles have a direct impact on the battery degradation and battery loss of life. This study presents a new 2-model iterative approach for explicit modelling of battery degradation in the optimal operation of PV systems. The proposed approach consists of two models: namely, economic model and degradation model which are solved iteratively to reach the optimal solution. The economic model is a linear programming optimisation problem that calculates the optimal hourly battery use profile based on an assumed value of the battery degradation cost. The degradation model,... 

The authors propose asynchronous level crossing (LC) A/D converters for low redundancy voice sampling. They propose to utilise the family of iterative methods with adaptive thresholding (IMAT) for reconstructing voice from non-uniform LC and adaptive LC (ALC) samples thereby promoting sparsity. The authors modify the basic IMAT algorithm and propose the iterative method with adaptive thresholding for level crossing (IMATLC) algorithm for improved reconstruction performance. To this end, the authors analytically derive the basic IMAT algorithm by applying the gradient descent and gradient projection optimisation techniques to the problem of square error minimisation subjected to sparsity. The... 

The dynamic nature of today’s manufacturing industry, which is caused by the intense global competition and constant technological advancements, requires systems that are highly adaptive and responsive to demand fluctuations. Reconfigurable manufacturing systems (RMS) enable such responsiveness through their main characteristics. This paper addresses the problem of RMS configuration design, where the demand of a single product varies throughout its production life cycle, and the system configuration must change accordingly to satisfy the required demand with minimum cost. A two-phased method is developed to handle the primary system configuration design and the necessary system... 

The assessment of the hypnotic state of the brain is crucial to the process of an operation under general anaesthesia. A noninvasive method of quantifying depth of anaesthesia is through analysis of electroencephalogram (EEG). Among number of works done in the field, no single algorithm has been found exhibiting a precise measure in all of the hypnotic states. One can categorise algorithms as either a state-quantifier or a trend measure. State-quantifier algorithms can discriminate between different hypnotic states such as awake, light sedation, deep anaesthesia, etc. On the other hand, trend measure algorithms are employed to specify the short-term changes in hypnotic brain conditions,... 

Wireless body area network (WBAN) is composed of miniaturised sensors that operate in the vicinity of the human body for recording the vital physiological signals and wirelessly transmitting them to a central hub for further processing. In this study, a statistical approach is applied to an experimental channel data set to extract the models for the squared channel gain that best describe the characteristics of the transmission medium between the sensors and the central hub. The derived models are then utilised to investigate the error rate performance of WBAN sensors. On the basis thereof, an optimisation problem is formed for which the cost function is the symbol error rate (SER) metric.... 

The privatization of distribution systems has resulted in the development of multiple-microgrid (multiple-MG) systems where each microgrid independently operates its local resources. Moreover, the high integration of independent distributed energy sources could lead to operational issues such as grid congestion in future distribution systems. Therefore, this paper provides a transactive-based energy management framework to operate multiple-MG distribution systems; while, alleviating grid congestion in a decentralized manner. In this respect, alternating direction method of multipliers (ADMM) is considered to develop an operational framework that copes with distributed nature of multiple-MG... 

Federated learning (FL) and split learning (SL) are state-of-the-art distributed machine learning techniques to enable machine learning without accessing raw data on clients or end devices. However, their comparative training performance under real-world resource-restricted Internet of Things (IoT) device settings, e.g., Raspberry Pi, remains barely studied, which, to our knowledge, have not yet been evaluated and compared, rendering inconvenient reference for practitioner. This work firstly provides empirical comparisons of FL and SL in real-world IoT settings regarding learning performance and on-device execution overhead. Our analyses demonstrate that the learning performance of SL is... 

The short-term expansion planning of the private utilities, as well as the emerging technologies such as photovoltaic panels (PVs), plug-in hybrid electric vehicles (PHEVs), cryptocurrency mining, and storage elements spread, make the long-term load estimation of distribution transformers (DTs) noticeably imprecise. In response, the number of overload and underload transformers is growing in recent years. The utilities normally analyse the loading of their DTs annually to determine the DTs, which should be replaced. It is a common practice for utilities to relocate these DTs to reduce the investment needed to purchase new transformers. Therefore, the utility needs a systematic algorithm to... 

The aim of this paper is to develop a simulation framework to minimise the cost associated with commercial greenhouse yields (production cost). Greenhouse energy demand and yield production models are coupled with a cost model to investigate the interaction between energy consumption costs and yield production benefits. The coupled model is defined as an optimisation problem to determine the optimal values of decision variables (e.g. cover material, heating and cooling technology, inside temperature and relative humidity set points, plant density, etc.), which result in minimum production cost as the objective function. The results show that the integrated energy demand-crop yield production...