A new tool for the simulation of different nuclear fleets at equilibrium

Scenario simulations are the main tool for studying the impact of a nuclear reactor fleet on the related fuel cycle facilities. This equilibrium preliminary study aims to present the functionalities of a new tool and to show the wide variety of reactors/cycles/strategies that can be studied in steady state conditions and validated with more details thanks to dynamic code. Different types of scenario simulation tools have been developed at CEA over the years, this study focuses on dynamic and equilibrium codes. Dynamic fuel cycle simulation code models the ingoing and outgoing material flow in all the facilities of a nuclear reactor fleet and their evolutions through the different nuclear processes over a given period of time. Equilibrium fuel cycle simulation code models advanced nuclear fuel cycles in equilibrium conditions, i.e. in conditions which stabilize selected nuclear inventories such as spent nuclear fuel constituents, plutonium or some minor actinides. The principle of this work is to analyze different nuclear reactors (PWR, AMR) and several fuel types (UOX, MOX, ERU, MIX) to simulate advanced nuclear fleet with partial and fully plutonium and uranium multi-recycling strategies at equilibrium. At this first stage, selected results are compared with COSI6 simulations in order to evaluate the precision of this new tool, showing a significant general agreement.

Design and simulation analysis of high-temperature heat-storage combined-circulation system

In view of the continuous increase in the proportion of renewable energy connected to the grid in China and the increasing peak-to-valley difference in electricity demand on the power grid, this paper proposes a high-temperature thermal-storage combined-cycle power-generation system. Using Thermoflex thermal simulation analysis software, a high-temperature thermal-storage combined-cycle simulation analysis system model was established, and the influence of different initial temperatures and pressure ratios on the combined-cycle system was analysed. Sensitivity analysis of factors such as electricity cost, annual operating hours, initial equipment investment, unit efficiency and other factors that affect the net income of the system was carried out. According to the current power-peak-shaving auxiliary service market in China, it is pointed out that high-temperature thermal-storage combined-cycle projects must be profitable and obtain good economic benefits. The results obtained, on the one hand, provide suggestions for the flexibility and transformation of current gas-fired steam generators for peak shaving and, on the other hand, provide references for the subsequent development of high-temperature thermal-storage combined-cycle demonstration projects.

Research on Intelligent Metrological Verification Technology Based on Internet of Things

Intelligent metrological verification is of great significance to improve the accuracy of equipment. Especially in the current situation of rapid increase in residential electricity consumption, electric energy meters have received widespread attention from the society as an important device that affects electricity trade settlement. In this research, this article will be based on the technological environment of the Internet of Things. After the analysis of the intelligent metrological verification system, the key technical means will be highlighted, including automatic sealing technology, automatic connection and disconnection technology, and cycle simulation system design. This article provides support for the verification system construction of the metrological center.

Tracking ankle joint movements during gait cycle via control of functional electrical stimulation

Functional electrical stimulation (FES) is an effective method to induce muscle contraction and to improve movements in individuals with injured central nervous system. In order to develop the FES systems for an individual with gait impairment, an appropriate control strategy must be designed to accurate tracking performance. The goal of this study is to present a method for designing proportional-derivative (PD) and sliding mode controllers (SMC) for the FES applied to the musculoskeletal model of an ankle joint to track the desired movements obtained by experiments on two healthy individuals during the gait cycle. Simulation results of the developed controller on musculoskeletal model of the ankle joint illustrated that the SMC is able to track the desired movements more accurately than the PD controller and prevents oscillating patterns around the experimentally measured data. Therefore, the sliding mode as the nonlinear method is more robust in face to unmodeled dynamics and model errors and track the desired path smoothly. Also, the required control effort is smoother in SMC with respect to the PD controller because of the nonlinearity.

Analysis of Supercritical CO2 Cycle Using Zigzag Channel Pre-Cooler: A Design Optimization Study Based on Deep Neural Network

The role of a pre-cooler is critical to the sCO2-BC as it not only acts as a sink but also controls the conditions at the main compressor’s inlet that are vital to the cycle’s overall performance. Despite their prime importance, studies on the pre-cooler’s design are hard to find in the literature. This is partly due to the unavailability of data around the complex thermohydraulic characteristics linked with their operation close to the critical point. Henceforth, the current work deals with designing and optimizing pre-cooler by utilizing machine learning (ML), an in-house recuperator and pre-cooler design, an analysis code (RPDAC), and a cycle design point code (CDPC). Initially, data computed using 3D Reynolds averaged Navier-Stokes (RANS) equation is used to train the machine learning (ML) model based on the deep neural network (DNN) to predict Nusselt number (Nu) and friction factor (f). The trained ML model is then used in the pre-cooler design and optimization code (RPDAC) to generate various designs of the pre-cooler. Later, RPDAC was linked with the cycle design point code (CDPC) to understand the impact of various designs of the pre-cooler on the cycle’s performance. Finally, a multi-objective genetic algorithm was used to optimize the pre-cooler geometry in the environment of the power cycle. Results suggest that the trained ML model can approximate 99% of the data with 90% certainty in the pre-cooler’s operating regime. Cycle simulation results suggest that the cycle’s performance calculation can be misleading without considering the pre-cooler’s pumping power. Moreover, the optimization study indicates that the compressor’s inlet temperature ranging from 307.5 to 308.5 and pre-cooler channel’s Reynolds number ranging from 28,000 to 30,000 would be a good compromise between the cycle’s efficiency and the pre-cooler’s size.

Disaster management and emerging technologies: a performance-based perspective

Purpose This paper aims to analyse how emerging technologies (ETs) impact on improving performance in disaster management (DM) processes and, concretely, their impact on the performance according to the different phases of the DM cycle (preparedness, response, recovery and mitigation). Design/methodology/approach The methodology is based on a systematic review of the literature. Scopus, ProQuest, EBSCO and Web of Science were used as data sources, and an initial sample of 373 scientific articles was collected. After abstracts and full texts were read and refinements to the search were made, a final corpus of 69 publications was analysed using VOSviewer software for text mining and cluster visualisation. Findings The results highlight how ETs foster the preparedness and resilience of specific systems when dealing with different phases of the DM cycle. Simulation and disaster risk reduction are the fields of major relevance in the application of ETs to DM. Originality/value This paper contributes to the literature by adding the lenses of performance measurement, management and accountability in analysing the impact of ETs on DM. It thus represents a starting point for scholars to develop future research on a rapidly and continuously developing topic.

Real-time engine model development based on time complexity analysis

Real-time simulation models play an important role in the development of engine control systems. The mean value model (MVM) meets real-time requirements but has limited accuracy. By contrast, a crank-angle resolved model, such as the filling -and-empty model, can be used to simulate engine performance with high accuracy but cannot meet real-time requirements. Time complexity analysis is used to develop a real-time crank-angle resolved model with high accuracy in this study. A method used in computer science, program static analysis, is used to theoretically determine the computational time for a multicylinder engine filling-and-empty (crank-angle resolved) model. Then, a prediction formula for the engine cycle simulation time is obtained and verified by a program run test. The influence of the time step, program structure, algorithm and hardware on the cycle simulation time are analyzed systematically. The multicylinder phase shift method and a fast calculation method for the turbocharger characteristics are used to improve the crank-angle resolved filling-and-empty model to meet real-time requirements. The improved model meets the real-time requirement, and the real-time factor is improved by 3.04 times. A performance simulation for a high-power medium-speed diesel engine shows that the improved model has a max error of 5.76% and a real-time factor of 3.93, which meets the requirement for a hardware-in-the-loop (HIL) simulation during control system development.

Determination of temperature thresholds for the parasitoid Diachasmimorpha longicaudata (Hymenoptera: Braconidae), using life cycle simulation modeling: Implications for effective field releases in classical biological control of fruit flies

The braconid parasitoid Diachasmimorpha longicaudata (Ashmead) (Hymenoptera: Braconidae) is one of the most important natural enemies in classical biological control programs against tephritid fruit flies worldwide. In light of the spread of the invasive fruit fly species, Bactrocera dorsalis in Africa and beyond, there is a need to implement classical biological control. The current study aimed to determine temperature thresholds for D. longicaudata reared on B. dorsalis, using life cycle simulation modeling to guide informed parasitoid releases in Africa. Simulated parameters included thermal requirements, population growth parameters at different temperature requirements, suitable areas for the establishment, and the number of generations per year under projected climatic conditions. The lower thermal threshold for the development was estimated at 10.0°C, with a thermal constant (k) of 333.3-degree days, while the maximum temperature threshold was estimated at 33.69°C. Fecundity was highest at 25°C, with 177.3 eggs per female. Temperature significantly affected the population growth parameters of D. longicaudata, and the maximum value of the intrinsic rate of increase (rm) was 0.145 at 27°C. Results indicate that D. longicaudata could successfully establish in tropical and sub-tropical regions under current and future climatic conditions. However, a slight change in the suitable areas is expected by the year 2050 due to a slight and gradual rise in temperature. Our findings provide important information for further release of this parasitoid in Africa as well as designing pest management strategies to limit the spread and reduce the impact of fruit flies sustainably.

CENTRIFUGAL COMPRESSOR PERFORMANCE MAPS TREATMENT FOR INTERNAL COMBUSTION ENGINES OPERATING CYCLE SIMULATION

Simulation of the supercharged internal combustion engines operation cycle is impossible without correct estimation of the supercharger operating parameters. Standard approach is to use specially prepared performance maps of compressor and turbine of the turbocharger, which are based on the experimental (or manufacturer’s) raw data. Centrifugal compressor performance maps interpolation, extrapolation and treatment provides challenging requirements as it is important to get correct simulation under such special conditions as compressor choke, rotating stall and pumping surge. At the same time it’s important to obtain the fast and stable calculations of the engine’s operating cycle. Blitz-PRO – online internal combustion engines operating cycle simulation service – offers supercharger performance maps preprocessing and implementation. It provides three different modes of compressor surge consideration during calculations: 1) full-scale surge mode using Moore-Greitzer approach; 2) mild surge mode with flexible adjustment; 3) “stable” mode, when the surge is neglected and the compressor constant-speed lines are extended from the rotating stall point to the lower mass flow region with the hyperbolic equation. Using the MAN 8G70ME-E engine 12140 kW, 82 rpm operating point as an example, the calculation results are compared for three modes of compressor surge consideration. The “stable” mode provides the fastest and the most stable calculations, while the calculations under the full-scale surge mode could generate the numerical (nonphysical) instability of calculations, which are caused by the high sensitivity of the two-stroke engines to the gas exchange processes as it is shown. The mild surge mode provides fast and stable enough calculation with the surge consideration ability, which could be assumed as the best solution for the given example. The researcher should choose between provided three modes of the centrifugal compressor surge consideration according to the calculations tasks, preferring “stable” mode for initial model setup and mild surge mode for the surge probability check, while the accurate compressor surge simulation needs further development.