Normal Operation Phase Research Articles

An Improved Stacking Model for Equipment Spare Parts Demand Forecasting Based on Scenario Analysis

The purpose of spare parts management is to maximize the system’s availability and minimize the economic costs. The problem of cost availability trade-off leads to the problem of spare parts demand prediction. Accurate and reasonable spare parts demand forecasting can realize the balance between cost and availability. So, this paper focuses on spare parts management during the equipment normal operation phase and tries to forecast the demand of spare parts in a specific inspection and replacement cycle. Firstly, the equipment operation and support scenarios are analyzed to obtain the supportability data related to spare parts requirements. Then, drawing on the idea of ensemble learning, a new feature selection method has been designed, which can overcome the limitations of a single feature selection method. In addition, an improved stacking model is proposed to predict the demand for spare parts. In the traditional stacking model, there are two levels of learning, base-learning, and meta-learning, in which the outputs of base learners are taken as the input of the meta learner. However, the proposed model brings the initial feature together with the output of the base learner layer as the input of the meta learner layer. And experiments have shown that the performance of the improved stacking model is better than the base learners and the traditional stacking model on the same data set.

A method of reducing the radial load of the shaft of a vertical axis wind turbine based on movable mass blocks

Fatigue failure caused by unsteady loads on the shaft is an important limiting factor in the development of large VAWT. This study proposes an active control method that relies on movable mass blocks to reduce the unsteady loads. Then on the basis of the aerodynamic load of the VAWT simulated by computational fluid dynamics, the motion laws of the mass blocks with different masses are investigated. When the mass of mass block is 0.075 kg, the radial load of the shaft can be reduced by 97.1% and the shaft deformation can be eliminated by 99% without affecting the power output of wind turbine. However, further research on the start-up performance of the VAWT indicates that the active control method also prolongs the start-up time. Thus a method of adjusting the moment of inertia of wind turbine with a rotation speed of 15.6 m/s is proposed to save 40.6% of the start-up time with respect to the method used for direct start-up with large moment of inertia of 0.036 kg m2. After the start-up, a transition displacement curve is plotted to aid in the switching design of the operation mode of mass blocks between the start-up phase and the normal operation phase.

A trust model for popular smart home devices

Nowadays, smart home devices like Amazon Echo and Google Home have reached mainstream popularity. Being in the homes of users, these devices are intrinsically intrusive, being able to access details such as users’ name, gender, home address, calendar appointments and others. There are growing concerns about indiscriminate data collection and invasion of user privacy in smart home devices, but studies show that perceived benefits are exceeding perceived risks when it comes to consumers. As a result, consumers are placing a lot of trust in these devices, sometimes without realizing it. Improper trust assumptions and security controls can lead to unauthorized access and control of the devices, which can result in serious consequences. In this paper, we explore the behaviour of devices such as Amazon Echo and Google Home in a smart home setting with respect to trust relationships and propose a trust model to improve these relationships among all the involved actors. We have evaluated how trust was built and managed from the initial set-up phase to the normal operation phase, during which we performed a number of interaction tests with different types of users (i.e. owner, guests). As a result, we were able to assess the effectiveness of the provided security controls and identify potential relevant security issues. In order to address the identified issues, we defined a trust model and propose a solution based on it for further securing smart home systems.

Characteristics of KOMPSAT-3A Key Image Quality Parameters During Normal Operation Phase

Characteristics of KOMPSAT-3A Key Image Quality Parameters During Normal Operation Phase

Mechanical properties of ultra-low temperature mortar stone

In order to study the mechanical properties of concrete materials in the normal operation phase of LNG tanks, the longitudinal strain of the loading direction and the transverse strain of the vertical loading at the corresponding temperature were measured by using the resistance strain gauge test technique. The elasticity of the mortar block and stone in the ultra-low temperature environment was studied. Modulus, Poisson’s ratio and shear modulus are respectively related to temperature. The results show that the Poisson’s ratio of stone and mortar is not obvious with temperature, which can be considered as a fixed value; the elastic modulus and shear modulus of mortar block increase linearly with the decrease of temperature, and the elastic modulus and shear modulus of stone The temperature decrease is a quadratic function relationship of decreasing first and then increasing. The elastic modulus and shear modulus of the stone are all the smallest at around -60 °C. It is concluded that the concrete material has better mechanical properties than the normal temperature environment in the ultra-low temperature environment, and can be used to further improve the design and construction of the LNG tank.

Assessment of amount and concentration of tritium in HTTR-IS system based on tritium behavior during high-temperature continuous operation of HTTR

The tritium concentration in the high temperature engineering test reactor (HTTR) was measured during high-temperature (950°C) continuous operation for 50days, which is the first measurement of tritium concentration in the secondary helium circuit during operation using the intermediate heat exchanger, to develop an assessment base for evaluating tritium behavior in the high temperature gas-cooled reactor hydrogen production system. The tritium concentration in the primary helium gas increased after startup and peaked at 1.6×10−1Bq/cm3 (STP) at 60% reactor power. Then, it decreased slightly over the course of the normal operation phase. This decrease could be attributed to the effect of tritium chemisorption on graphite. The tritium concentration in the secondary helium gas was slightly lower than that in the primary helium gas. The tritium concentration in the secondary helium gas peaked at 4.7×10−2Bq/cm3 (STP) during the power enhancement phase. Thereafter, it decreased gradually to 2.2×10−2Bq/cm3 (STP) at the end of the normal power operation phase. As assessed herein, the concentration and total quantity of tritium in the secondary helium cooling system of the HTTR-iodine sulfur (IS) system can be maintained below the regulatory limits, which implies that the hydrogen production plant can be exempt from the safety function of the nuclear facility.

Study on IC Reactor Treating Straw-Washing Wastewater and Changes of Sludge Bed

In this paper, we utilized IC reactor to treat straw-washing wastewater of straw pulping and papermaking. The removal rate of COD in normal operation is 28.14%, which is much lower than the value of wake-up stage and acclimation stage; gas production rate in the whole normal operation phase kept a lower level, and the average is 12.36L/h; so straw-washing water is not suitable for advanced anaerobic treatment. While COD removal rate is 28.14%, SCOD removal rate is only 6.96%; added the effluent VFA concentration which is 692~1211mg/L is greatly exceed normal control level, we can know that when treating straw-washing water the biological system was under acidification phase of the anaerobic process. Thus the straw-washing water is suitable for hydrolysis-acidification Process. Granular size of seed sludge was 3~5mm, 100 days later it became 1.5~3mm, and 120 days later it was 1~2.5mm mainly, With the acidification occurring, the mass proportion of the granular sludge to total sludge was reduced, the proportions of 2# and 3# sampling ports are decreasing from 70~85% to 30~50%. Because of lack of adequate nutrition and appropriate loading conditions, straw-washing water can’t support the cultivation and maintenance of granular sludge.

Anaerobic treatment of Tequila vinasses in a CSTR-type digester

Tequila industries in general produce great volumes of effluents with high pollutant loads, which are discharged (untreated or partially treated) into natural receivers, thus causing severe environmental problems. In this contribution, we propose an integrated system as a first step to comply with the Mexican ecological norms and stabilize the anaerobic treatment of Tequila vinasses with main design criteria: simple and easy operation, reduce operating time and associated costs (maintenance), integrated and compact design, minimal cost of set-up, start-up, monitoring and control. This system is composed of a fully instrumented and automated lab-scale CSTR-type digester, on-line measuring devices of key variables (pH, temperature, flow rates, etc.), which are used along with off-line readings of chemical oxygen demand (COD), biogas composition, alkalinity and volatile fatty acids to guarantee the operational stability of the anaerobic digestion process. The system performance was evaluated for 200 days and the experimental results show that even under the influence of load disturbances, it is possible to reduce the COD concentration to 85% in the start-up phase and up to 95% during the normal operation phase while producing a biogas with a methane composition greater than 65%. It is also shown that in order to maintain an efficient treatment, the buffering capacity (given by the alkalinity ratio, alpha = intermediate alkalinity/total alkalinity) must be closely monitored.

Software dependability models under memory faults with application to a digital system in nuclear power plants

In this work, software dependability under memory faults in the operational phase is predicted by two models: an analytic model and the stochastic activity network (SAN) model. The analytic model is based on the simple reliability theory and the graph theory, which represents the software as a graph composed of nodes and arcs. Through proper transformation, the graph can be reduced to a simple two-node graph from which software reliability can be derived. The SAN model permits the representation of concurrency, timeliness, fault tolerance, and degradable performance of the system and provides a means for determining the stochastic behavior of a software. Using these models, we predict the reliability of an application software in a digital system, Interposing Logic System (ILS), in a nuclear power plant and show the sensitivity of software reliability to major physical parameters which affect software failure in the normal operation phase. It is found that the effects of hardware faults on software failure should be considered for the accurate prediction of software dependability in the operation phase.