Article
Neurosciences
Amirhossein Jafarian, Peter Zeidman, Rob C. Wykes, Matthew Walker, Karl J. Friston
Summary: Adiabatic dynamic causal modelling is a method for inferring slow changes in biophysical parameters controlling fast neuronal fluctuations. It relies on established neural mass models and an adiabatic approximation to summarize fast neuronal states using second order statistics. The method introduces a circular causality involving synaptic parameters and neuronal activity, and is validated through simulations and an illustrative application to seizure activity in an animal model.
Article
Economics
Mingming Zhang, Simei Zhou, Qunwei Wang, Liyun Liu, Dequn Zhou
Summary: This paper predicts the future state of energy security in China on the path to achieving carbon neutrality. The results show that energy security is expected to improve from Poor to Poor+ state in 2040, 2050, and 2060 under the carbon neutrality scenario. However, under the existing policy scenario, energy security is expected to remain in a Poor state. Carbon neutrality has a small negative impact on energy security in the short term, but a positive impact in the long term. The dimensions of energy security, including availability, applicability, acceptability, and affordability, may not achieve balanced development under the carbon neutrality scenario.
Article
Engineering, Industrial
Yushan Liu, Luyi Li, Zeming Chang
Summary: This paper proposes a novel Bayesian updating framework based on principal component analysis (PCA) to solve the challenging problem of updating dynamic systems with high-dimensional output. The framework constructs a new likelihood function based on low-dimensional output principal components (PCs), which has been analytically proven to provide equivalent likelihood measures to the original one. An efficient Bayesian updating algorithm is also proposed in the PCA-based framework, which incorporates adaptive Bayesian updating with structural reliability methods (aBUS) and the Kriging model. Four examples are conducted to validate the proposed method.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Engineering, Civil
Jia-Hua Yang, Heung-Fai Lam, Yong-Hui An
Summary: The paper proposes a new two-phase adaptive MCMC method to address the problem of determining the posterior probability density function (PDF) in Bayesian model updating. By using a parameter-space search algorithm and a weighted MCMC algorithm, samples in the regions of high probability can be generated adaptively without going through computationally demanding multiple levels.
ENGINEERING STRUCTURES
(2022)
Article
Green & Sustainable Science & Technology
Javanshir Fouladvand, Amineh Ghorbani, Yasin Sari, Thomas Hoppe, Rolf Kunneke, Paulien Herder
Summary: This paper takes a comprehensive view of the energy security of community energy systems, considering dimensions such as energy price, environment, and availability. The study finds that energy communities can improve the energy security of individual households, reduce CO2 emissions, and be cost-effective in the long run. Project leadership and available subsidy amount are important factors in ensuring energy security.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Acoustics
Philippe Bisaillon, Rimple Sandhu, Chris Pettit, Mohammad Khalil, Dominique Poirel, C. S. Manohar, Abhijit Sarkar
Summary: We propose a Bayesian framework for selecting physics-based models and error models simultaneously. By using colored noise to capture the mismatch between calibrated models and observational data, the predictive capabilities of the models are improved.
JOURNAL OF SOUND AND VIBRATION
(2022)
Article
Engineering, Environmental
Jingyu Zhu, Guoming Chen, Faisal Khan, Ming Yang, Xinhong Li, Xiangkun Meng, Rui He
Summary: The study introduces a sequence-based dynamic reliability assessment method for the MPD system, which focuses on dynamic modeling of sequential operations by integrating GO-FLOW and dynamic Bayesian Network (DBN).
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
(2021)
Article
Green & Sustainable Science & Technology
Mohamd Laimon, Thanh Mai, Steven Goh, Talal Yusaf
Summary: In this study, the impact of renewable energy systems and energy efficiency on the performance of the energy sector is examined using a system dynamics approach. The results show that improvements in energy efficiency and the adoption of renewable energy sources can lead to significant reductions in energy consumption and domestic CO2 emissions.
Article
Biochemical Research Methods
Tong Shao, Wenfang Wang, Meiyu Duan, Jiahui Pan, Zhuoyuan Xin, Baoyue Liu, Fengfeng Zhou, Guoqing Wang
Summary: The study found that the mutation rate of the new coronavirus is not high, similar to that of the SARS virus. There are similarities and differences in potential modification sites between the 2019-nCoV and SARS virus. Based on skyline results, it is speculated that the gene population activity of 2019-nCoV may have occurred before the end of 2019.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Energy & Fuels
Yuxiang Xia, Qi Wang, Cairan Miao, Yi Tang
Summary: The low inertia caused by the integration of renewable energy and the increasing use of power electronic equipment poses challenges to frequency security. This article proposes a fast frequency security assessment method based on the extended SFR model, which considers multiple frequency response sources. The effectiveness of the proposed model is verified and it shows characteristics of both rapidity and accuracy in judging the security of power systems.
Article
Mathematics
Jiaowei Shi, Shiyan Sun, Jun Xie, Chaobing Zheng
Summary: The paper proposes a method to analyze the dynamic damage probability of laser systems and calculates the damage probability by constructing energy density distribution models and probability distributions. The simulation validates the effectiveness of the method, which provides important guidance for the shooting timing of high-energy laser systems.
Article
Engineering, Environmental
Abbas Mamudu, Faisal Khan, Sohrab Zendehboudi, Sunday Adedigba
Summary: This study proposes a dynamic risk modeling strategy for a hydrocarbon sub-surface production system under a gas lift mechanism using a data-driven probabilistic methodology. The integrated approach of MLP-ANN model and BN technique offers an effective strategy to avoid production failure, monitor dynamic risks, and assist in production decision-making, especially in complex production systems.
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
(2021)
Article
Economics
Katherine Emma Lonergan, Nicolas Suter, Giovanni Sansavini
Summary: Policymaking is increasingly focused on achieving an energy transition that is not only cost-effective and low carbon, but also fair and just. While energy system models have been valuable tools in achieving the first two objectives, their ability to support a just transition is still uncertain. A review of recent energy systems modelling studies suggests that there is potential for models to support a just transition, especially in terms of assessing distributional outcomes. However, many of the existing approaches in the literature are not well aligned with current energy justice goals and discourses, resulting in decreased policy relevance and suboptimal planning support. The authors propose eight actions for modellers to increase the policy relevance of their studies, including greater engagement with policy and research discourses, conducting location-specific case studies, involving public participation in the modelling process, and considering asset decommissioning.
Article
Energy & Fuels
Tingting Li, Yangze Zhou, Yang Zhao, Chaobo Zhang, Xuejun Zhang
Summary: Bayesian network is a powerful algorithm for diagnosing faults in building energy systems. This study proposes a hierarchical object oriented Bayesian network-based method, which reuses predefined standard network fragments to generate system-level fault diagnosis models, avoiding repetitive modeling work.
Article
Engineering, Industrial
Abhinav Subramanian, Sankaran Mahadevan
Summary: This paper proposes a physics-informed machine learning approach for response prediction in dynamic systems. The approach combines a physics-based model and a probabilistic machine learning model to account for model error. The model error is quantified using Bayesian state estimation, and the machine learning model is trained to predict the output discrepancy. Different computational options are developed for different types of inputs and computational requirements. The proposed approach is demonstrated with numerical examples of a deep beam and hypersonic flow over an aircraft panel.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Energy & Fuels
Ricardas Krikstolaitis, Vincenzo Bianco, Linas Martisauskas, Sigita Urboniene
Summary: This study analyzes the electricity and natural gas supply security in Germany, France, Italy, and Spain, and finds that Germany and France have higher energy security due to their rich energy resources and nuclear power.
Article
Green & Sustainable Science & Technology
Alvyra Galkiene, Ona Monkeviciene, Lina Kaminskiene, Ricardas Krikstolaitis, Maile Kaesper, Ilze Ivanova
Summary: The critical situation in education caused by COVID-19 has reduced the involvement of pupils from vulnerable groups, particularly those with low learning achievements. This study reveals that self-regulatory collaborative learning has a strong and sustainable impact on the achievements of pupils with emotional and learning difficulties in various educational environments.
Article
Energy & Fuels
Linas Martisauskas, Juozas Augutis, Ricardas Krikstolaitis, Rolandas Urbonas, Inga Saruniene, Vytis Kopustinskas
Summary: This paper presents a framework for assessing the resilience of energy systems using quantitative indicators and demonstrates the future foresight capabilities and potential of selected resilience indicators through calculations for the Lithuanian energy system. The results reveal that a diverse electricity production mix and supply and production diversification in the prospective energy system are the most important factors impacting energy system resilience.
Article
Thermodynamics
Migle Jakucionyte-Skodiene, Ricardas Krikstolaitis, Genovaite Liobikiene
Summary: In the European Union, the household sector accounts for a quarter of greenhouse gas emissions and this share is increasing. Research indicates that changes in concern, personal responsibility, and climate-friendly behavior can have a significant impact on household emissions. However, there is a lack of studies on how these factors contribute to household greenhouse gas emissions. This study aims to analyze the effects of changes in concern, personal responsibility, and climate-friendly behavior on household emissions in the EU. The results show that changes in the choice of green energy supplier and home insulation significantly affect greenhouse gas emissions in the household sector.
Article
Green & Sustainable Science & Technology
Genovaite Liobikiene, Ricardas Krikstolaitis, Astrida Miceikiene
Summary: This study analyzed the changes in biomass extraction in EU countries and found that during the period of economic growth and transition, biomass extraction decreased in most EU countries, while during the bioeconomy strategy period, only a few countries had a reduction in biomass extraction. The study suggests that achieving sustainable bioeconomy principles in most EU countries remains a significant challenge, and efforts should be made to improve the productivity level of biomass.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2023)
Article
Thermodynamics
F. Gardumi, I Keppo, M. Howells, S. Pye, G. Avgerinopoulos, V Lekavicius, A. Galinis, L. Martisauskas, U. Fahl, P. Korkmaz, D. Schmid, R. Cunha Montenegro, S. Syri, A. Hast, U. Mortberg, O. Balyk, K. Karlsson, X. Pang, G. Mozgeris, R. Trubins, D. Jaksic, I. M. Turalija, M. Mikulic
Summary: With the publication of the European Green Deal, the European Union aims to achieve carbon neutrality by 2050. While the reduction of direct greenhouse gas emissions is technically feasible, pursuing the wrong path may have significant unintended impacts. An integrated assessment framework is discussed to inform the European Commission on decarbonization strategies. The framework goes beyond existing ones in scope, depth, and cross-scale coverage, utilizing specialized models and case studies. Challenges of consistency are identified and can be addressed through iterative linking, harmonizing assumptions, and comparing model outputs. The framework's highest added value lies in providing insights on the technical feasibility of decarbonization pathways, vulnerability aspects, and unintended environmental and health impacts at different scales.
Article
Energy & Fuels
Vytautas Bocullo, Linas Martisauskas, Darius Pupeikis, Ramunas Gatautis, Rytis Vencaitis, Rimantas Bakas
Summary: The field of solar photovoltaic (PV) plants has experienced significant growth, but the impact of shading on PV plant performance remains a concern. This study proposes a methodology using UAV photogrammetry to evaluate shading effects on PV systems and determine optimal configuration. A high-detail 3D model allows for obstacle evaluation and accurate recreation of shading proximities. The methodology was applied to PV systems in Kaunas, Lithuania, resulting in a 11% difference in PV yield and highlighting the need for financing support and optimal design.
Article
Chemistry, Multidisciplinary
Otilija Vonzudaite, Linas Martisauskas, Rimantas Bakas, Sigita Urboniene, Rolandas Urbonas
Summary: This study focuses on selecting the optimal heat pump systems for different types of buildings, considering technical, economic, environmental, and social factors. The results show that air-to-water heat pumps and electric heaters are the most efficient heating systems, which can be combined with hybrid heat pumps for schools and a supermarket. The goal of achieving carbon neutrality was accomplished for 8 out of 11 buildings analyzed. The most profitable investments were in the heating systems of renovated five-story and unrenovated nine-story apartment buildings.
APPLIED SCIENCES-BASEL
(2023)
Article
Mathematics, Applied
Ricardas Krikstolaitis, Gintautas Mozgeris, Edmundas Petrauskas, Petras Rupsys
Summary: This study applied stochastic differential equations and Copula theories to estimate the dependencies among five dimensions, and introduced a normalized multi-dimensional interaction information index based on differential entropy to capture the dependencies between state variables.
Article
Forestry
Petras Rupsys, Gintautas Mozgeris, Edmundas Petrauskas, Ricardas Krikstolaitis
Summary: In this study, a normal copula approach was used to estimate the dependencies between tree size variables, and a normalized multivariate interaction information measure was introduced to assess their causality. The validity of the method was demonstrated through the analysis of an empirical dataset.
Article
Health Care Sciences & Services
Gabriele Jenciute, Gabriele Kasputyte, Inesa Buneviciene, Erika Korobeinikova, Domas Vaitiekus, Arturas Inciura, Laimonas Jarusevicius, Romas Bunevicius, Ricardas Krikstolaitis, Tomas Krilavicius, Elona Juozaityte, Adomas Bunevicius
Summary: This study aims to evaluate the feasibility of using passively generated data from smartphone sensors for remote monitoring of cancer patients to predict their disease trajectories and patient-centered health outcomes. The study will collect mobility data and sociability indices from patients and evaluate their associations with clinical data and patient-reported health outcomes.
JMIR RESEARCH PROTOCOLS
(2023)
Article
Horticulture
Laima Cesoniene, Ricardas Krikstolaitis, Remigijus Daubaras, Romas Mazeika
Summary: Investigating suitable substrates for plant saplings is crucial for finding new components. Currently, a large number of saplings are cultivated for blueberry plantations. Research on the use of various organic and inorganic components in substrates is important to reduce the reliance on excavated peat. This study aimed to analyze the impact of different mixes of peat, spruce, pine fibers, and perlite on the growth of blueberry saplings.
Article
Thermodynamics
Yong Cheng, Fukai Song, Lei Fu, Saishuai Dai, Zhiming Yuan, Atilla Incecik
Summary: This paper investigates the accessibility of wave energy absorption by a dual-pontoon floating breakwater integrated with hybrid-type wave energy converters (WECs) and proposes a hydraulic-pneumatic complementary energy extraction method. The performance of the system is validated through experiments and comparative analysis.
Article
Thermodynamics
Jing Gao, Chao Wang, Zhanwu Wang, Jin Lin, Runkai Zhang, Xin Wu, Guangyin Xu, Zhenfeng Wang
Summary: This study aims to establish a new integrated method for biomass cogeneration project site selection, with a focus on the application of the model in Henan Province. By integrating Geographic Information System and Multiple Criterion Decision Making methods, the study conducts site selection in two stages, providing a theoretical reference for the construction of biomass cogeneration projects.
Article
Thermodynamics
Mert Temiz, Ibrahim Dincer
Summary: The current study presents a hybrid small modular nuclear reactor and solar-based system for sustainable communities, integrating floating and bifacial photovoltaic arrays with a small modular reactor. The system efficiently generates power, hydrogen, ammonia, freshwater, and heat for residential, agricultural, and aquaculture facilities. Thermodynamic analysis shows high energy and exergy efficiencies, as well as large-scale ammonia production meeting the needs of metropolitan areas. The hybridization of nuclear and solar technologies offers advantages of reliability, environmental friendliness, and cost efficiency compared to renewable-alone and fossil-based systems.
Editorial Material
Thermodynamics
Wojciech Stanek, Wojciech Adamczyk
Article
Thermodynamics
Desheng Xu, Yanfeng Li, Tianmei Du, Hua Zhong, Youbo Huang, Lei Li, Xiangling Duanmu
Summary: This study investigates the optimization of hybrid mechanical-natural ventilation for smoke control in complex metro stations. The results show that atrium fires are more significantly impacted by outdoor temperature variations compared to concourse/platform fires. The gathered high-temperature smoke inside the atrium can reach up to 900 K under a 5 MW train fire energy release. The findings provide crucial engineering insights into integrating weather data and adaptable ventilation protocols for smoke prevention/mitigation.
Article
Thermodynamics
Da Guo, Heping Xie, Mingzhong Gao, Jianan Li, Zhiqiang He, Ling Chen, Cong Li, Le Zhao, Dingming Wang, Yiwei Zhang, Xin Fang, Guikang Liu, Zhongya Zhou, Lin Dai
Summary: This study proposes a new in-situ pressure-preserved coring tool and elaborates its pressure-preserving mechanism. The experimental and field test results demonstrate that this tool has a high pressure-preservation capability and can maintain a stable pressure in deep wells. This study provides a theoretical framework and design standards for the development of similar technologies.
Article
Thermodynamics
Aolin Lai, Qunwei Wang
Summary: This study assesses the impact of China's de-capacity policy on renewable energy development efficiency (REDE) using the Global-MSBM model and the difference-in-differences method. The findings indicate that the policy significantly enhances REDE, promoting technological advancements and marketization. Moreover, regions with stricter environmental regulations experience a higher impact.
Article
Thermodynamics
Mostafa Ghasemi, Hegazy Rezk
Summary: This study utilizes fuzzy modeling and optimization to enhance the performance of microbial fuel cells (MFCs). By simulating and analyzing experimental data sets, the ideal parameter values for increasing power density, COD elimination, and coulombic efficiency were determined. The results demonstrate that the fuzzy model and optimization methods can significantly improve the performance of MFCs.
Article
Thermodynamics
Zhang Ruan, Lianzhong Huang, Kai Wang, Ranqi Ma, Zhongyi Wang, Rui Zhang, Haoyang Zhao, Cong Wang
Summary: This paper proposes a grey box model for fuel consumption prediction of wing-diesel hybrid vessels based on feature construction. By using both parallel and series grey box modeling methods and six machine learning algorithms, twelve combinations of prediction models are established. A feature construction method based on the aerodynamic performance of the wing and the energy relationship of the hybrid system is introduced. The best combination is obtained by considering the root mean square error, and it shows improved accuracy compared to the white box model. The proposed grey box model can accurately predict the daily fuel consumption of wing-diesel hybrid vessels, contributing to operational optimization and the greenization and decarbonization of the shipping industry.
Article
Thermodynamics
Huayi Chang, Nico Heerink, Junbiao Zhang, Ke He
Summary: This study examines the interaction between off-farm employment decisions between couples and household clean energy consumption in rural China, and finds that two-paycheck households are more likely to consume clean energy. The off-farm employment of women is a key factor driving household clean energy consumption to a higher level, with wage-employed wives having a stronger influence on these decisions than self-employed ones.
Article
Thermodynamics
Hanguan Wen, Xiufeng Liu, Ming Yang, Bo Lei, Xu Cheng, Zhe Chen
Summary: Demand-side management is crucial to smart energy systems. This paper proposes a data-driven approach to understand the relationship between energy consumption patterns and household characteristics for better DSM services. The proposed method uses a clustering algorithm to generate optimal customer groups for DSM and a deep learning model for training. The model can predict the possibility of DSM membership for a given household. The results demonstrate the usefulness of weekly energy consumption data and household socio-demographic information for distinguishing consumer groups and the potential for targeted DSM strategies.
Article
Thermodynamics
Xinglan Hou, Xiuping Zhong, Shuaishuai Nie, Yafei Wang, Guigang Tu, Yingrui Ma, Kunyan Liu, Chen Chen
Summary: This study explores the feasibility of utilizing a multi-level horizontal branch well heat recovery system in the Qiabuqia geothermal field. The research systematically investigates the effects of various engineering parameters on production temperature, establishes mathematical models to describe their relationships, and evaluates the economic viability of the system. The findings demonstrate the significant economic feasibility of the multi-level branch well system.
Article
Thermodynamics
Longxin Zhang, Songtao Wang, Site Hu
Summary: This investigation reveals the influence of tip leakage flow on the modern transonic rotor and finds that the increase of tip clearance size leads to a decline in rotor performance. However, an optimal tip clearance size can extend the rotor's stall margin.
Article
Thermodynamics
Kristian Gjoka, Behzad Rismanchi, Robert H. Crawford
Summary: This paper proposes a framework for assessing the performance of 5GDHC systems and demonstrates it through a case study in a university campus in Melbourne, Australia. The results show that 5GDHC systems are a cost-effective and environmentally viable solution in mild climates, and their successful implementation in Australia can create new market opportunities and potential adoption in other countries with similar climatic conditions.
Article
Thermodynamics
Jianwei Li, Guotai Wang, Panpan Yang, Yongshuang Wen, Leian Zhang, Rujun Song, Chengwei Hou
Summary: This study proposes an orientation-adaptive electromagnetic energy harvester by introducing a rotatable bluff body, which allows for self-regulation to cater for changing wind flow direction. Experimental results show that the output power of the energy harvester can be greatly enhanced with increased rotatory inertia of the rotating bluff body, providing a promising solution for harnessing wind-induced vibration energy.
