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Sequence Impedance Prediction for Grid-Connected Converters Based on Bi-LSTM
Get PDFThe large-scale application of voltage-source converters (VSCs) to power grids may negatively impact their stability. Stability analysis methods based on impedance modeling offer a theoretical framework to analyze and address this issue. However, under conditions of uncertainty regarding the internal structure and parameters of VSCs, existing impedance measurement techniques using frequency scanning are limited in terms of data acquisition and accuracy. In practice, the power output demand for VSCs in grid-connected operation tends to vary, making it challenging for frequency scanning schemes to account for changes in operating conditions. To address this challenge, this article proposes a sequence impedance prediction solution based on a bidirectional long short-term memory method, which requires only limited data to accomplish high-precision prediction of the overall impedance of VSCs under multiple operating points. Unlike the existing dq-based impedance prediction schemes, the sequence impedance method will greatly simplify the prediction process, and the physical meaning is clear. In addition, this article applies trained model to a small-scale VSC model through transfer learning for experimental validation. The process saves computational resources while maintaining prediction accuracy and demonstrates the adaptability of the proposed model.</p
Occupants’ willingness to share information for improved comfort and energy efficiency in offices
No full textBackground: Human environmental perception and occupant behaviour are influenced by a multitude of factors, including demographic variables and individual preferences. Advancements in data collection allow the acquisition of extensive personal information, such as heart rate, skin temperature, and emotional responses to environmental conditions. These data can enhance research on multi-domain influences and on optimizing building operations but raise questions regarding individuals’ willingness to share personal information.Methodology:This study investigates how factors like data type, data collector, and anonymity level are associated with occupants’ willingness to share information for improved indoor environmental conditions or energy efficiency. A stated preference discrete choice experiment was developed and applied, with responses collected from participants in 29 countries, resulting in a dataset with 791 samples. The discrete choice analysis was conducted using mixed logit models and based on Random Utility Theory.Results:The outcomes indicate that respondents exhibit relative indifference toward sharing demographic and physical environmental data, while having heightened concerns about sharing psychological and activity-related information. Anonymity and control over the data appear to be of crucial importance. Additionally, data collection by academic institutions is preferred to that by for-profit entities. Variability in willingness to share data across and within samples of countries suggests a necessity for tailored strategies.Impact:This research underscores the necessity of balancing advancements in energy efficiency and thermal comfort with societal needs that respect individual rights. Practical recommendations for effective personal data collection are provided and methodological limitations due to scenario complexity and participant engagement are highlighted
Coalition Formation and Firm Representatives’ Answers to Complainers on Social Media: Their Interplay and the Coalition Ripple Effect
Get PDFWe ask whether complaint answers by firm representatives depend on coalition formation—others taking sides with complainers or firm representatives—and whether coalition formation by third actors depends on complaint answers. An online field study revealed that, from the firm representative perspective, the 73.2% probability of a complaint answer in the absence of any coalition decreases to 10.9%–12.8% in the presence of a prior coalition with a firm representative or complainer. From the third actor perspective, the probability of the formation of a coalition with a firm representative decreases by one-third in the presence versus absence of a prior complaint answer; coalitions with complainers are not curtailed. Furthermore, a coalition with a firm representative shifts the average complaint answer from somewhat favorable to unfavorable, which facilitates coalitions with complainers, creating a coalition ripple effect. The results offer managerial guidance, as dissatisfying online complaint handling remains problematic
Parameter sensitivity study of a morphology-adaptive CFD model for flat plate air lubrication
No full textIn this study, the effect of air lubrication on drag reduction on a downward-facing flat plate is investigated using a morphology-adaptive multiphase CFD model (MultiMorph). The model is applied to simultaneously simulate bubble drag reduction (BDR) and air layer drag reduction (ALDR) regimes. A sensitivity study of the MultiMorph submodels is performed to quantify the important parameters in air lubrication modelling using this simulation method. A comparison with experimental data using the baseline submodels showed 20-30 % deviations in drag reduction as a function of air flow rate with improved prediction of drag reduction in the transitional regime compared to a two-dimensional study. The submodel sensitivity study revealed that closure models accounting for lift and turbulent dispersion are found to affect drag reduction by up to ± 44.2 %. The value of the disperse bubble diameter is found to cause changes up to ± 28.1 %, assuming monodisperse bubbles. In contrast, drag reduction results are largely insensitive to the specific drag and wall lubrication closure model, and small changes in the turbulence damping strength and virtual mass coefficient cause differences below ± 10 %. These findings highlight some of the important modelling considerations and parameters for simulating air lubrication using the MultiMorph model.</p
The effect of implementing colon capsule endoscopy in colorectal cancer screening on participation and sociodemographic inequalities:A parallel group randomised controlled trial
Get PDFOBJECTIVES: Significant sociodemographic inequalities in participation in colorectal cancer (CRC) screening programmes across the globe are evident. We aimed to investigate the effect of introducing colon capsule endoscopy (CCE) as a filter test in faecal immunochemical test (FIT)-based CRC screening on overall FIT participation and social inequalities in FIT participation.STUDY DESIGN: We conducted a randomised controlled trial, randomising 368,452 individuals.METHODS: Both groups received an invitation to submit a FIT sample, which elicited a follow-up investigation if ≥ 20 μg haemoglobin/g faeces was detected. The control group followed the standard screening pathway and was referred for follow-up colonoscopy. The intervention group were free to choose between colonoscopy and colon capsule endoscopy.RESULTS: The overall FIT participation proportion was significantly lower in the intervention group (63.4 %), compared to the control group (64.9 %). All sociodemographic subgroups in the intervention group had lower participation proportions than their control group counterpart, with an average of 1.4 (range 0.3-2.7) percentage points lower participation. The odds of non-participation, divided by sociodemographic characteristics, were not significantly different between interventions and controls for any subgroup, except for those aged 55-59 in which the odds ratios for non-participation was 1.59 (1.54-1.65) in the control group and 1.48 (1.43-1.53) in the intervention group, comparing them to those aged above 70.CONCLUSIONS: Introducing a free choice between colon capsule endoscopy and colonoscopy if FIT positive did not increase FIT participation in CRC screening. Further, it did not affect the pattern of social inequalities in FIT uptake.</p
Corneal Immune Cells and Their Relation to Diabetic Peripheral Neuropathy and Neuropathic Pain
No full textABSTRACT Introduction/Aims As corneal dendritic cells (DCs) are immune cells that can reflect systemic inflammatory activity, this study aimed to investigate whether the density and maturity of corneal DCs are associated with diabetes, diabetic peripheral neuropathy (DPN), and neuropathic pain. Methods Participants included individuals with type 1 diabetes mellitus (T1DM) and painful DPN (n?=?19), T1DM and painless DPN (n?=?15), T1DM without DPN (n?=?19), and healthy controls (n?=?20). Corneal confocal microscopy was used to quantify and categorize DCs as either mature or immature and based on their proximity to corneal nerves. Results No significant differences between groups were observed in total DC density (p?=?0.34). Subgroup analysis revealed distinct patterns in which participants with DPN (regardless of pain status) exhibited a higher density of immature DCs distant from corneal nerves compared to those without DPN (14.4 [6.64?37.5] vs. 3.75 [0?17.7]?no./mm2, p?Introduction/Aims: As corneal dendritic cells (DCs) are immune cells that can reflect systemic inflammatory activity, this study aimed to investigate whether the density and maturity of corneal DCs are associated with diabetes, diabetic peripheral neuropathy (DPN), and neuropathic pain. Methods: Participants included individuals with type 1 diabetes mellitus (T1DM) and painful DPN (n = 19), T1DM and painless DPN (n = 15), T1DM without DPN (n = 19), and healthy controls (n = 20). Corneal confocal microscopy was used to quantify and categorize DCs as either mature or immature and based on their proximity to corneal nerves. Results: No significant differences between groups were observed in total DC density (p = 0.34). Subgroup analysis revealed distinct patterns in which participants with DPN (regardless of pain status) exhibited a higher density of immature DCs distant from corneal nerves compared to those without DPN (14.4 [6.64–37.5] vs. 3.75 [0–17.7] no./mm 2, p < 0.05). Healthy controls had a greater density of immature DCs near the nerves compared to the T1DM + DPN group (2.8 [0–8.44] vs. 8.3 [3.12–15.1] no./mm 2), while the T1DM + DPN group had a higher density than the painful DPN (3.1 [1.25–5.62] no./mm 2). For mature DCs near the nerves, individuals with painful DPN (2.5 [1.4–3.12] no./mm 2) had a lower density compared to all other groups. Discussion: This study demonstrates distinct patterns of corneal DC distribution in relation to painful and painless DPN. The findings suggest that immune-mediated mechanisms may play a role in the development of neuropathy and neuropathic pain in diabetes. The pathophysiological significance remains to be clarified. Trial Registration: ClinicalTrials.gov: NCT04078516.</p
Phraseologismen als Mittel zur Didaktisierung von Grammatik in „Deutsch als Zusatzkompetenz“-Kursen
No full text3D CFD modelling of self-heating and self-ignition with parametric investigations in solid fuel stockpiles
No full textOpen-air stockpiles of solid fuels, such as coal and biomass, are susceptible to self-heating and spontaneous combustion due to low-temperature oxidation, moisture migration, and, in the case of biomass, biological processes. Computational fluid dynamics (CFD) combined with experimental data plays a crucial role in predicting and preventing such hazardous occurrences. Compared to conventional 1D and 2D models, 3D modelling provides distinct advantages by faithfully replicating the intricate geometry of the stockpile and accurately accounting for realistic ambient flow conditions, resulting in more reliable simulation results. In this study, a 3D CFD model is developed to numerically replicate the self-heating and self-ignition process within a coal pile as previously reported in the literature. The CFD model, developed using Ansys Fluent, incorporates essential considerations such as low-temperature coal oxidation and water evaporation, and implements various source terms reflective of the chemical and physical processes within the coal pile through User Defined Functions (UDFs). Since the thermal conductivity and mass diffusivity in a coal pile may be in the same order as the local turbulent conductivity and diffusivity, it is crucial to assess whether the flow within the pile is turbulent or laminar and accommodate the correct flow regime within the pile. Our simulation results reveal three distinct stages of self-heating within the coal pile, which are consistent with the observations reported in the literature. Notably, the upper-middle zone inside the coal pile exhibits high temperatures and relatively low oxygen content, primarily limited by the internal air velocity. Key parameters, such as coal pile height, moisture content, wind speed, and heat loss at the pile bottom, are found to significantly impact the self-heating process. The developed CFD model lays the groundwork for a comprehensive and systematic parametric study, from which applicable guidelines for preventing and mitigating fire accidents in coal piles are suggested. This model will be extended to biomass stockpiles by incorporating biological reactions as well as addressing the differences between low-temperature biomass and coal oxidation.</p
Assessing the CFD applicability of chemical kinetic mechanisms for pure ammonia combustion
Get PDFAmmonia is a promising carbon-free fuel, but realising its potential for green energy requires combustion models that are both accurate and computationally efficient. While many reaction mechanisms have been proposed, few are designed with computational fluid dynamics (CFD) applications in mind. This study evaluates 11 mechanisms based on their predictions of laminar flame speed, peak flame temperature, NO emissions, computational cost, and minimum species timescales. One-dimensional flame simulations across equivalence ratios from 0.5 to 1.5 identified three different mechanisms as the most promising, though each showed trade-offs in computational cost, NO prediction, or laminar flame speed accuracy. Random forest regression showed that the minimum species time scale is a key factor for solution time, on par with the number of reactions. Mechanisms with OH* sub-mechanisms produced very short time scales, potentially limiting their CFD applicability. Overall, the results highlight the need to balance computational cost and accuracy in mechanism selection, and call for further development of reduced mechanisms that address CFD-relevant metrics, such as the minimum species time scale
