Flexible operation of large-scale coal-fired power plant integrated with solvent-based post-combustion CO2 capture based on neural network inverse control

Post-combustion carbon capture (PCC) with chemical absorption has strong interactions with coal-fired power plant (CFPP). It is necessary to investigate dynamic characteristics of the integrated CFPP-PCC system to gain knowledge for flexible operation. It has been demonstrated that the integrated system exhibits large time inertial and this will incur additional challenge for controller design. Conventional PID controller cannot effectively control CFPP-PCC process. To overcome these barriers, this paper presents an improved neural network inverse control (NNIC) which can quickly operate the integrated system and handle with large time constant. Neural network (NN) is used to approximate inverse dynamic relationships of integrated CFPP-PCC system. The NN inverse model uses setpoints as model inputs and gets predictions of manipulated variables. The predicted manipulated variables are then introduced as feed-forward signals. In order to eliminate steady-state bias and to operate the integrated CFPP-PCC under different working conditions, improvements have been achieved with the addition of PID compensator. The improved NNIC is evaluated in a large-scale supercritical CFPP-PCC plant which is implemented in gCCS toolkit. Case studies are carried out considering variations in power setpoint and capture level setpoint. Simulation results reveal that proposed NNIC can track setpoints quickly and exhibit satisfactory control performances

Review of dynamic modelling, system identification and control scheme in solvent-based post-combustion carbon capture process

Solvent-based post-combustion carbon capture (PCC) process is widely viewed as the most viable option for reducing CO 2 emission. This technology has been deployed globally and many researches have been conducted in this area. In this paper, current status of dynamic modelling, system identification and control scheme of solvent-based PCC process is reviewed. Different research directions of these areas are discussed to conclude the existing challenges. Based on this, this paper is also trying to provide potential solutions as possible pathways for flexible and economical operation

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Dynamic Characteristics of the Steam Accumulator Charging and Discharging

The method of numerical simulation is used to study the charging and discharging process of steam accumulator. By analyzing the charging and discharging thermal process of steam accumulator, establishing the mathematical model and using MATLAB software to simulate the solution, the dynamic characteristic curves of charging and discharging are obtained, and the charging and discharging conditions of the steam accumulator are defined. This research has an important significance in the design and application of the steam accumulator

Dynamic Characteristics of the Steam Accumulator Charging and Discharging

The method of numerical simulation is used to study the charging and discharging process of steam accumulator. By analyzing the charging and discharging thermal process of steam accumulator, establishing the mathematical model and using MATLAB software to simulate the solution, the dynamic characteristic curves of charging and discharging are obtained, and the charging and discharging conditions of the steam accumulator are defined. This research has an important significance in the design and application of the steam accumulator

Electronic Asymmetry Engineering of Fe–N–C Electrocatalyst via Adjacent Carbon Vacancy for Boosting Oxygen Reduction Reaction

Single-atomic transition metal–nitrogen–carbon (M–N–C) structures are promising alternatives toward noble-metal-based catalysts for oxygen reduction reaction (ORR) catalysis involved in sustainable energy devices. The symmetrical electronic density distribution of the M─N4 moieties, however, leads to unfavorable intermediate adsorption and sluggish kinetics. Herein, a Fe–N–C catalyst with electronic asymmetry induced by one nearest carbon vacancy adjacent to Fe─N4 is conceptually produced, which induces an optimized d-band center, lowered free energy barrier, and thus superior ORR activity with a half-wave potential (E1/2) of 0.934 V in a challenging acidic solution and 0.901 V in an alkaline solution. When assembled as the cathode of a Zinc–air battery (ZAB), a peak power density of 218 mW cm−2 and long-term durability up to 200 h are recorded, 1.5 times higher than the noble metal-based Pt/C+RuO2 catalyst. This work provides a new strategy on developing efficient M–N–C catalysts and offers an opportunity for the real-world application of fuel cells and metal–air batteries.</p

Heterostructure Engineering of 2D Superlattice Materials for Electrocatalysis

Exploring low-cost and high-efficient electrocatalyst is an exigent task in developing novel sustainable energy conversion systems, such as fuel cells and electrocatalytic fuel generations. 2D materials, specifically 2D superlattice materials focused here, featured highly accessible active areas, high density of active sites, and high compatibility with property-complementary materials to form heterostructures with desired synergetic effects, have demonstrated to be promising electrocatalysts for boosting the performance of sustainable energy conversion and storage devices. Nevertheless, the reaction kinetics, and in particular, the functional mechanisms of the 2D superlattice-based catalysts yet remain ambiguous. In this review, based on the recent progress of 2D superlattice materials in electrocatalysis applications, the rational design and fabrication of 2D superlattices are first summarized and the application of 2D superlattices in electrocatalysis is then specifically discussed. Finally, perspectives on the current challenges and the strategies for the future design of 2D superlattice materials are outlined. This review attempts to establish an intrinsic correlation between the 2D superlattice heterostructures and the catalytic properties, so as to provide some insights into developing high-performance electrocatalysts for next-generation sustainable energy conversion and storage.</p

Germline mutation landscape of Chinese patients with familial breast/ovarian cancer in a panel of 22 susceptibility genes

 Abstract Genetic testing for germline mutations in BRCA1/2 of patients with breast cancer (BC) is part of routine patient care. However, BRCA1/2 mutations account only for a fraction of familial BC. A custom panel of 22 gene sequencing was performed on each patient. Among the 481 female patients, 135 patients were detected to carry pathogenic (P)/likely pathogenic (LP) mutations (28.1%), which corresponded to 12 different cancer predisposition genes [14.6% (70/481) on BRCA1 gene, 5.0% (24/481) on BRCA2 gene, 8.5% (41/481) on non‐BRCA1/2 genes]. Moreover, 24.7% (119/481) of patients had mutation of unknown significance (VUS) in these genes. The most common (8/481) pathogenic mutation is BRCA1 c.5470_5477del, while BRIP1 2392 C > T of patients was detected. All the mutations detected were mainly seen in the homologous recombinant repair pathway. Compared to BRCA2 mutation, BRCA1 mutation is higher in younger female patients (P < 0.01). Some pathogenic mutations were detected in the patients’ familiy members without the past history of tumor and 92 novel mutations were detected (31 on BRCA including 2 P, 16 LP, 13 VUS; 61 on non‐BRCA1/2 including 9 LP, 52 VUS). The detection rate of BRCA1/2 mutations was higher in patients with three or more cancer family members than those with one or two. However, the difference was not statistically different. The results suggest that multigene panel testing can increase mutation detection rate for high‐risk BC patients. Detailed family history can help to categorize new mutations