ORC units driven by engine waste heat – a simulation study

ORC (organic Rankine cycle) technology is promising in industry for utilizing low-grade heat to generate electricity. It is acknowledged that in an internal combustion engine, only a small amount of primary fuel energy can be effectively used for the power generation, and the other part of the energy lost through exhaust gas, cooling of elements and overcoming friction. The heat in exhaust gas and cooling system (jacket water) can be used as a heat source to drive ORC units for power generation. In this way, the energy lost can be recovered to generate extra power. In this study, Ricardo Wave software was used to investigate the amount of waste heat available from a 1-cylinder diesel engine and THERMOLIB toolbox in SIMULINK was used to simulate and evaluate the performance of a small ORC unit designed for the application. The simulation results from the engine and ORC models were validated against experimental data from other researchers. Two different heating methods to the ORC were used: a) directly driven by the exhaust gas and jacket water (EG-JW); b) thermal oil (TO) was used to collect the waste heat from the engine exhaust gas; the heated thermal oil together with jacket water were then used to drive the ORC. It was found that the performance of the ORC was improved and it was more stable when using TO under different engine running conditions than that directly driven by EG-JW

Daily natural gas load prediction method based on APSO optimization and Attention-BiLSTM

As the economy continues to develop and technology advances, there is an increasing societal need for an environmentally friendly ecosystem. Consequently, natural gas, known for its minimal greenhouse gas emissions, has been widely adopted as a clean energy alternative. The accurate prediction of short-term natural gas demand poses a significant challenge within this context, as precise forecasts have important implications for gas dispatch and pipeline safety. The incorporation of intelligent algorithms into prediction methodologies has resulted in notable progress in recent times. Nevertheless, certain limitations persist. However, there exist certain limitations, including the tendency to easily fall into local optimization and inadequate search capability. To address the challenge of accurately predicting daily natural gas loads, we propose a novel methodology that integrates the adaptive particle swarm optimization algorithm, attention mechanism, and bidirectional long short-term memory (BiLSTM) neural networks. The initial step involves utilizing the BiLSTM network to conduct bidirectional data learning. Following this, the attention mechanism is employed to calculate the weights of the hidden layer in the BiLSTM, with a specific focus on weight distribution. Lastly, the adaptive particle swarm optimization algorithm is utilized to comprehensively optimize and design the network structure, initial learning rate, and learning rounds of the BiLSTM network model, thereby enhancing the accuracy of the model. The findings revealed that the combined model achieved a mean absolute percentage error (MAPE) of 0.90% and a coefficient of determination (R2) of 0.99. These results surpassed those of the other comparative models, demonstrating superior prediction accuracy, as well as exhibiting favorable generalization and prediction stability

Krüppel-Like Factor 4 Is a Regulator of Proinflammatory Signaling in Fibroblast-Like Synoviocytes through Increased IL-6 Expression

Human fibroblast-like synoviocytes play a vital role in joint synovial inflammation in rheumatoid arthritis (RA). Proinflammatory cytokines induce fibroblast-like synoviocyte activation and dysfunction. The inflammatory mediator Krüppel-like factor 4 is upregulated during inflammation and plays an important role in endothelial and macrophage activation during inflammation. However, the role of Krüppel-like factor 4 in fibroblast-like synoviocyte activation and RA inflammation remains to be defined. In this study, we identify the notion that Krüppel-like factor 4 is higher expressed in synovial tissues and fibroblast-like synoviocytes from RA patients than those from osteoarthritis patients. In vitro, the expression of Krüppel-like factor 4 in RA fibroblast-like synoviocytes is induced by proinflammatory cytokine tumor necrosis factor-α. Overexpression of Krüppel-like factor 4 in RA fibroblast-like synoviocytes robustly induced interleukin-6 production in the presence or absence of tumor necrosis factor-α. Conversely, knockdown of Krüppel-like factor 4 markedly attenuated interleukin-6 production in the presence or absence of tumor necrosis factor-α. Krüppel-like factor 4 not only can bind to and activate the interleukin-6 promoter, but also may interact directly with nuclear factor-kappa B. These results suggest that Krüppel-like factor 4 may act as a transcription factor mediating the activation of fibroblast-like synoviocytes in RA by inducing interleukin-6 expression in response to tumor necrosis factor-α

Reversible On-Off Photoswitching of DNA Replication Using a Dumbbell Oligodeoxynucleotide

In most organisms, DNA extension is highly regulated; however, most studies have focused on controlling the initiation of replication, and few have been done to control the regulation of DNA extension. In this study, we adopted a new strategy for azODNs to regulate DNA extension, which is based on azobenzene oligonucleotide chimeras regulated by substrate binding affinity, and the conformation of the chimera can be regulated by a light source with a light wavelength of 365 nm. The results showed that the primer was extended with Taq DNA polymerase after visible light treatment, and DNA extension could be effectively hindered with UV light treatment. We also verify the reversibility of the photoregulation of primer extension through photoswitching of dumbbell asODNs by alternate irradiation with UV and visible light. Our method has the advantages of fast and simple, green response and reversible operations, providing a new strategy for regulating gene replication

Histone H3 Exerts a Key Function in Mitotic Checkpoint Control ▿

It has been firmly established that many interphase nuclear functions, including transcriptional regulation, are regulated by chromatin and histones. How mitotic progression and quality control might be influenced by histones is less well characterized. We show that histone H3 plays a crucial role in activating the spindle assembly checkpoint in response to a defect in mitosis. Prior to anaphase, all chromosomes must attach to spindles emanating from the opposite spindle pole bodies. The tension between sister chromatids generated by the poleward pulling force is an integral part of chromosome biorientation. Lack of tension due to erroneous attachment activates the spindle assembly checkpoint, which corrects the mistakes and ensures segregation fidelity. A histone H3 mutation impairs the ability of yeast cells to activate the checkpoint in a tensionless crisis, leading to missegregation and aneuploidy. The defects in tension sensing result directly from an attenuated H3-Sgo1p interaction essential for pericentric recruitment of Sgo1p. Reinstating the pericentric enrichment of Sgo1p alleviates the mitotic defects. Histone H3, and hence the chromatin, is thus a key factor transmitting the tension status to the spindle assembly checkpoint

Simulation Study of an ORC System Driven by the Waste Heat Recovered from a Trigeneration System

Trigeneration produces power, heat and cooling simultaneously. It utilises the waste heat from generator for heating and generating cooling. From previous studies, it is found that some part of the waste heat recovered by the trigeneration is not being used when it is in operation. It is therefore necessary to find a way to utilise the heat. Integrating an ORC (organic Rankine cycle) system into a micro trigeneration system is studied. The waste heat recovered by the trigeneration system is utilised by the ORC system to generate electrical power. An ORC model is set up in Matlab and a micro trigeneration system based a diesel engine generator in the laboratory at Newcastle University is used as the case study. R245fa is used as the working fluid. The result showed that the ORC system may generate 0.737 kW electrical power with 9.25% efficiency at the generator full-load operation point