bluuebunny/crossref_metadata_2025 huggingface dataset:
Feasibility of a Remotely Delivered Strength and Balance Training Program for Older Adults with Cancer
Authors: Sattar Schroder , Haase Kristen , Penz Kelly , Effa Corrie , Nedeljak Joni , Chalchal Haji , Souied Osama , Amir Eitan , Pitters Eric , Campbell Diane , Alibhai Shabbir , McNeely Margaret L.
Published: November 2021

Falls are a major issue among older adults with cancer and lead to interruptions in cancer treatment. Resistance and balance training can prevent falls in older adults, but minimal evidence is available regarding the older cancer population, who often have unique risk factors. We used a pre–post design to assess the feasibility of a remotely delivered exercise program that progressed in difficulty and its efficacy on lower body strength, balance, and falls in older adults with cancer who had prior in-person exercise experience. Twenty-six older adults with cancer completed the intervention. Attendance rate for the virtual component was 97.6% and for the independent component was 84.7%. Participants perceived the program as rewarding and enjoyable (100%), felt this program prepared them to exercise on their own (92%), were confident to continue exercising on their own (81%), and would recommend the program to other patients (100%). The median balance score at baseline and end-of-study was 4 (IQR = 0). The median chair-stand time decreased from 9.2 s (IQR = 3.13) to 7.7 s (IQR = 4.6). A statistically significant difference in lower body strength (r = 0.68, p = 0.001) was detected post-intervention. The findings from this study can inform the design of a larger randomized trial.
Trophic Ecology of Juvenile Southern King Crab Associated with Kelp Forest: Evidence of Cannibalism
Authors: Pardo Luis Miguel , Andrade Claudia , Zenteno-Devaud Lisette , Garrido Bastián , Rivera Cristóbal
Published: November 2021

The southern king crab, Lithodes santolla, is a well-known predator/scavenger species during its adult phase but its feeding strategy in early stages is less studied. This information is important to understand their role in ecosystems and to improve fishery management (i.e., stock enhancement). Based on stomach contents and stable isotope analysis, we determined variation in the composition of diet and niche overlap in vagile and cryptic phase collected within and outside a kelp forest, Macrocystis pyrifera, of Aguila Bay at the Magellan Strait in Patagonia, Chile. Results of juvenile stomach content analysis showed 60% dissimilarity between cryptic and vagile juvenile phases. Algae dominated the volumetric contribution in cryptic juveniles while crustacean dominated the diet in vagile phase. Exoskeleton of other king crabs occurred in 43% of juveniles with crustaceans in their stomach. This fact confirms cannibalistic behavior in the wild in this species, which is consistent with findings in massive laboratory cultures. There was no evidence of isotopic niche shift between cryptic and vagile juvenile phases. Overlapping isotopic niches of different-sized juveniles suggest that they exploit similar food resources. However, vagile individuals occupy a higher trophic position than cryptic individuals, which could suggest a switch in dietary preference, from detritivorous/herbivory within kelp forests to omnivory outside of kelp forests, and an increase in the level of cannibalism in vagile juveniles.
State of Crop Landraces in Arcadia (Greece) and In-Situ Conservation Potential
Authors: Thanopoulos Ricos , Chatzigeorgiou Tilemachos , Argyropoulou Konstantina , Kostouros Nikolaos-Marios , Bebeli Penelope J.
Published: November 2021

Genetic erosion of landraces is increasing worldwide, however there are still regions rich in landrace biodiversity, such as islands and mountainous isolated areas. Defining the reasons of landrace abandonment in these areas, as well as collecting and preserving landraces, is of outmost importance. In this context, the Agricultural University of Athens organized missions in 53 villages of Arcadia, a prefecture rich in floral biodiversity and variable climatic conditions and topography. The aim was to collect samples of the on-farm (in-situ) conserved annual crop landraces and record the location of perennial crop local varieties. Since traditional knowledge and practices have been playing a vital role in the survival of landraces and local varieties, information was obtained through personal interviews with locals using semi-structured questionnaires. Even though the number of accessions collected from Arcadia has been reduced (141 samples) compared to previous collections and genetic erosion is advancing dramatically for cereals and pulses, a significant number of landraces is still cultivated by the locals. The reasons of landrace abandonment were other sources of occupation than agriculture, such as public service jobs, mechanization, and commercialization of agriculture. Gastronomic and agro-tourism along with European Union trademarks and policies can support locals in landrace/local varieties in-situ conservation.
Thermal–Statistical Odd–Even Fermions’ Staggering Effect and the Order–Disorder Disjunction
Authors: Pennini Flavia , Plastino Angelo , Plastino Angel Ricardo
Published: November 2021

We review thermal–statistical considerations on the odd–even staggering effect (OES) in fermions. There is a well known OES in nuclear binding energies at zero temperature. We discuss here a thermal OES (finite temperatures) that establishes links with the order–disorder disjunction. The present thermal considerations cannot be found in the nuclear literature.
An Improved Approach towards Multi-Agent Pursuit–Evasion Game Decision-Making Using Deep Reinforcement Learning
Authors: Wan Kaifang , Wu Dingwei , Zhai Yiwei , Li Bo , Gao Xiaoguang , Hu Zijian
Published: November 2021

A pursuit–evasion game is a classical maneuver confrontation problem in the multi-agent systems (MASs) domain. An online decision technique based on deep reinforcement learning (DRL) was developed in this paper to address the problem of environment sensing and decision-making in pursuit–evasion games. A control-oriented framework developed from the DRL-based multi-agent deep deterministic policy gradient (MADDPG) algorithm was built to implement multi-agent cooperative decision-making to overcome the limitation of the tedious state variables required for the traditionally complicated modeling process. To address the effects of errors between a model and a real scenario, this paper introduces adversarial disturbances. It also proposes a novel adversarial attack trick and adversarial learning MADDPG (A2-MADDPG) algorithm. By introducing an adversarial attack trick for the agents themselves, uncertainties of the real world are modeled, thereby optimizing robust training. During the training process, adversarial learning was incorporated into our algorithm to preprocess the actions of multiple agents, which enabled them to properly respond to uncertain dynamic changes in MASs. Experimental results verified that the proposed approach provides superior performance and effectiveness for pursuers and evaders, and both can learn the corresponding confrontational strategy during training.
Einstein-Podolsky-Rosen Steering for Mixed Entangled Coherent States
Authors: Abdel-Khalek Sayed , Berrada Kamal , Algarni Mariam , Eleuch Hichem
Published: November 2021

By using the Born Markovian master equation, we study the relationship among the Einstein–Podolsky–Rosen (EPR) steering, Bell nonlocality, and quantum entanglement of entangled coherent states (ECSs) under decoherence. We illustrate the dynamical behavior of the three types of correlations for various optical field strength regimes. In general, we find that correlation measurements begin at their maximum and decline over time. We find that quantum steering and nonlocality behave similarly in terms of photon number during dynamics. Furthermore, we discover that ECSs with steerability can violate the Bell inequality, and that not every ECS with Bell nonlocality is steerable. In the current work, without the memory stored in the environment, some of the initial states with maximal values of quantum steering, Bell nonlocality, and entanglement can provide a delayed loss of that value during temporal evolution, which is of interest to the current study.
Falkner–Skan Flow with Stream-Wise Pressure Gradient and Transfer of Mass over a Dynamic Wall
Authors: Khan Muhammad Fawad , Sulaiman Muhammad , Tavera Romero Carlos Andrés , Alkhathlan Ali
Published: November 2021

In this work, an important model in fluid dynamics is analyzed by a new hybrid neurocomputing algorithm. We have considered the Falkner–Skan (FS) with the stream-wise pressure gradient transfer of mass over a dynamic wall. To analyze the boundary flow of the FS model, we have utilized the global search characteristic of a recently developed heuristic, the Sine Cosine Algorithm (SCA), and the local search characteristic of Sequential Quadratic Programming (SQP). Artificial neural network (ANN) architecture is utilized to construct a series solution of the mathematical model. We have called our technique the ANN-SCA-SQP algorithm. The dynamic of the FS system is observed by varying stream-wise pressure gradient mass transfer and dynamic wall. To validate the effectiveness of ANN-SCA-SQP algorithm, our solutions are compared with state-of-the-art reference solutions. We have repeated a hundred experiments to establish the robustness of our approach. Our experimental outcome validates the superiority of the ANN-SCA-SQP algorithm.
Multi-Hop Question Generation Using Hierarchical Encoding-Decoding and Context Switch Mechanism
Authors: Ji Tianbo , Lyu Chenyang , Cao Zhichao , Cheng Peng
Published: November 2021

Neural auto-regressive sequence-to-sequence models have been dominant in text generation tasks, especially the question generation task. However, neural generation models suffer from the global and local semantic semantic drift problems. Hence, we propose the hierarchical encoding–decoding mechanism that aims at encoding rich structure information of the input passages and reducing the variance in the decoding phase. In the encoder, we hierarchically encode the input passages according to its structure at four granularity-levels: [word, chunk, sentence, document]-level. Second, we progressively select the context vector from the document-level representations to the word-level representations at each decoding time step. At each time-step in the decoding phase, we progressively select the context vector from the document-level representations to word-level. We also propose the context switch mechanism that enables the decoder to use the context vector from the last step when generating the current word at each time-step.It provides a means of improving the stability of the text generation process during the decoding phase when generating a set of consecutive words. Additionally, we inject syntactic parsing knowledge to enrich the word representations. Experimental results show that our proposed model substantially improves the performance and outperforms previous baselines according to both automatic and human evaluation. Besides, we implement a deep and comprehensive analysis of generated questions based on their types.
Stories and Theatre for Teaching Physics at Primary School
Authors: Giliberti Marco
Published: November 2021

The paper contains progress reports supported by data about two short activities aimed at introducing physics themes in primary school. The first is a formal storytelling intervention named “Mommy Comet” carried out in first- and fifth-grade classes and concerning motion in the absence of forces in the Solar System broad context. The second is an informal work with third-, fourth- and fifth-degree students to investigate what physics is about. The results obtained by analyzing questionnaires and conducting interviews show how these narrative tools can offer wide potentialities and prove great effectiveness in introducing young students to physics.
Quantum Physics Education Research over the Last Two Decades: A Bibliometric Analysis
Authors: Bitzenbauer Philipp
Published: November 2021

Quantum physics is an essential field of science education research, which reflects the high relevance of research on quantum physics and its technologies all around the globe. In this paper, we report on a bibliometric analysis of the science education research community’s scientific output in the area of quantum physics in the period from 2000 to 2021. A total of 1520 articles published in peer-reviewed physics and science education journals were retrieved from Web of Science and Scopus databases to conduct bibliometric analysis. This study aims to provide an overview of quantum physics education research in terms of scientific production, preferred publication venues, most involved researchers and countries (including collaborations), and research topics. The main findings point to a continuous increase in research output in the field of quantum physics education over the last two decades. Furthermore, they indicate a shift regarding the research foci. While formerly mainly papers on the teaching of quantum physics content were published, recently, an increase in the relevancy of empirical studies on the teaching and learning of quantum physics can be observed.
IoT Security Challenges: Cloud and Blockchain, Postquantum Cryptography, and Evolutionary Techniques
Authors: Balogh Stefan , Gallo Ondrej , Ploszek Roderik , Špaček Peter , Zajac Pavol
Published: November 2021

Internet of Things connects the physical and cybernetic world. As such, security issues of IoT devices are especially damaging and need to be addressed. In this treatise, we overview current security issues of IoT with the perspective of future threats. We identify three main trends that need to be specifically addressed: security issues of the integration of IoT with cloud and blockchains, the rapid changes in cryptography due to quantum computing, and finally the rise of artificial intelligence and evolution methods in the scope of security of IoT. We give an overview of the identified threats and propose solutions for securing the IoT in the future.
Hyperspectral Remote Sensing Image Feature Representation Method Based on CAE-H with Nuclear Norm Constraint
Authors: Yu Xiaodong , Ding Rui , Shao Jingbo , Li Xiaohui
Published: November 2021

Due to the high dimensionality and high data redundancy of hyperspectral remote sensing images, it is difficult to maintain the nonlinear structural relationship in the dimensionality reduction representation of hyperspectral data. In this paper, a feature representation method based on high order contractive auto-encoder with nuclear norm constraint (CAE-HNC) is proposed. By introducing Jacobian matrix in the CAE of the nuclear norm constraint, the nuclear norm has better sparsity than the Frobenius norm and can better describe the local low dimension of the data manifold. At the same time, a second-order penalty term is added, which is the Frobenius norm of the Hessian matrix expressed in the hidden layer of the input, encouraging a smoother low-dimensional manifold geometry of the data. The experiment of hyperspectral remote sensing image shows that CAE-HNC proposed in this paper is a compact and robust feature representation method, which provides effective help for the ground object classification and target recognition of hyperspectral remote sensing image.
Predicting Regional Outbreaks of Hepatitis A Using 3D LSTM and Open Data in Korea
Authors: Lee Kwangok , Lee Munkyu , Na Inseop
Published: November 2021

In 2020 and 2021, humanity lived in fear due to the COVID-19 pandemic. However, with the development of artificial intelligence technology, mankind is attempting to tackle many challenges from currently unpredictable epidemics. Korean society has been exposed to various infectious diseases since the Korean War in 1950, and to overcome them, the six most serious cases in National Notifiable Infectious Diseases (NNIDs) category I were defined. Although most infectious diseases have been overcome, viral hepatitis A has been on the rise in Korean society since 2010. Therefore, in this paper, the prediction of viral hepatitis A, which is rapidly spreading in Korean society, was predicted by region using the deep learning technique and a publicly available dataset. For this study, we gathered information from five organizations based on the open data policy: Korea Centers for Disease Control and Prevention (KCDC), National Institute of Environmental Research (NIER), Korea Meteorological Agency (KMA), Public Open Data Portal, and Korea Environment Corporation (KECO). Patient information, water environment information, weather information, population information, and air pollution information were acquired and correlations were identified. Next, an epidemic outbreak prediction was performed using data preprocessing and 3D LSTM. The experimental results were compared with various machine learning methods through RMSE. In this paper, we attempted to predict regional epidemic outbreaks of hepatitis A by linking the open data environment with deep learning. It is expected that the experimental process and results will be used to present the importance and usefulness of establishing an open data environment.
Design and Fabrication of a Printed Tri-Band Antenna for 5G Applications Operating across Ka-, and V-Band Spectrums
Authors: Hussain Musa , Jarchavi Syed Muhammad Rizvi , Naqvi Syeda Iffat , Gulzar Usama , Khan Salahuddin , Alibakhshikenari Mohammad , Huynen Isabelle
Published: November 2021

In this paper, an umbrella-shaped patch antenna for future millimeter-wave applications for the 5G frequency band is presented. The proposed antenna resonates at multiple frequency bands, i.e., 28 GHz, 38 GHz, and 55 GHz (V-band) that have been globally allocated for 5G communications systems. The proposed antenna is designed using Rogers RT/duroid 5870, with a relative permittivity, loss tangent and thickness of 2.33 mm, 0.0012 mm and 0.79 mm, respectively. The antenna has an overall size of 8 mm × 8 mm which correspond to 0.7 λ × 0.7 λ, where λ is free space wavelength at the lowest resonance. Moreover, the wide bandwidth, high gain and tri band operational mode is achieved by introducing two stubs to the initial design. The antenna prototype was fabricated and validated experimentally. The comparison of the simulated and measured results demonstrates a good correlation. Additionally, the comparative analysis with state of the art work demonstrates that the proposed antenna offers compact size, simple geometrical configuration, wide bandwidth, high gain, and radiation efficiency which makes the proposed antenna a potential candidate for compact smart 5G devices.
Method for Determining the Optimal Capacity of Energy Storage Systems with a Long-Term Forecast of Power Consumption
Authors: Senchilo Nikita Dmitrievich , Ustinov Denis Anatolievich
Published: November 2021

The unevenness of the electricity consumption schedule at enterprises leads to a peak power increase, which leads to an increase in the cost of electricity supply. Energy storage devices can optimize the energy schedule by compensating the planned schedule deviations, as well as reducing consumption from the external network when participating in a demand response. However, during the day, there may be several peaks in consumption, which lead to a complete discharge of the battery to one of the peaks; as a result, total peak power consumption does not decrease. To optimize the operation of storage devices, a day-ahead forecast is often used, which allows to determine the total number of peaks. However, the power of the storage system may not be sufficient for optimal peak compensation. In this study, a long-term forecast of power consumption based on the use of exogenous parameters in the decision tree model is used. Based on the forecast, a novel algorithm for determining the optimal storage capacity for a specific consumer is developed, which optimizes the costs of leveling the load schedule.
Building Sustainable Pavements: Investigating the Effectiveness of Recycled Tire Rubber as a Modifier in Asphalt Mixtures
Authors: Plati Christina , Cliatt Brad
Published: November 2021

Building more sustainable pavements for the future requires knowledge of alternative and innovative materials for utilization in future road construction and maintenance activities. Being mindful of this need, the present study investigates a Reacted and Activated Rubber (RAR) compound modifier with the aim of defining an optimal RAR percentage in Asphalt Concrete (AC) mixes. It is acknowledged that when this type of modifier is incorporated within an AC mix as an alternative for the bituminous binder material, the associated economic, environmental and social benefits are significant. Simply put, the use of RAR modifiers provides the potential to utilize a waste product (rubber tires) as a more sustainable alternative to bitumen within AC mixtures. However, it seems that the information about the overall performance of AC mixes modified with RAR is currently limited. On these grounds, the present study focuses on the surface course layer and evaluates (a) achieved physical characteristics (compaction degree/voids), (b) mechanical characterization results (stiffness moduli) and (c) friction-based properties of tested mixtures incorporating varying RAR levels and different test temperatures. From the evaluation, it is concluded that for the case of the surface course mixture under investigation, the optimal percentage by weight of bitumen for inclusion of the RAR modifier is 10%.
Coopetitive Platform: Common Benefits in Electricity and Gas Distribution
Authors: Czakon Wojciech , Mucha-Kuś Karolina , Sołtysik Maciej
Published: November 2021

Simultaneous collaboration and competition, or coopetition, has so far been studied among firms or non-profit organizations, leaving the public arena largely unexplored. This study focuses on identifying and measuring common benefit generation by local government actors in coopetition. We purposefully choose a metropolis composed of 41 municipalities setting to identify and measure those effects of coopetition that cannot be achieved by individual actors alone. We use real data and tariffs to run simulations that identify common and individual benefits generated in gas and electricity distribution. We find that savings can be achieved by mutualizing energy procurement, even though the distribution of savings is not equal among municipalities. We substantiate that energy communities can act as coopetitive platforms to optimize energy costs of municipalities.
Modeling, Controller Design and Simulation Groundwork on Multirotor Unmanned Aerial Vehicle Hybrid Power Unit
Authors: Krznar Matija , Pavković Danijel , Cipek Mihael , Benić Juraj
Published: November 2021

This paper presents the results of modeling, control system design and simulation verification of a hybrid-electric drive topology suitable for power flow control within unmanned aerial vehicles (UAVs). The hybrid power system is based on the internal combustion engine (ICE) driving a brushless DC (BLDC) generator supplying the common DC bus used for power distribution within the aircraft. The overall control system features proportional-integral-derivative (PID) feedback control of the ICE rotational speed using a Luenberger estimator for engine-generator set rotational speed estimation. The BLDC generator active rectifier voltage and current are controlled by proportional-integral (PI) feedback controllers, augmented by estimator-based feed-forward load compensators. The overall control system design has been based on damping optimum criterion, which yields straightforward analytical expressions for controller and estimator parameters. The robustness to key process parameters variations is investigated by means of root-locus methodology, and the effectiveness of the proposed hybrid power unit control system is verified by means of comprehensive computer simulations.
Use of Learning Mechanisms to Improve the Condition Monitoring of Wind Turbine Generators: A Review
Authors: Nunes Ana Rita , Morais Hugo , Sardinha Alberto
Published: November 2021

The main goal of this paper is to review and evaluate how we can take advantage of state-of-the-art machine learning techniques and apply them in wind energy operation conditions monitoring and fault diagnosis, boosting wind turbines’ availability. To accomplish this, we focus our work on analysing the current techniques in predictive maintenance, which are aimed at acting before a major failure occurs using condition monitoring. In particular, we start framing the predictive maintenance problem as an ML problem to detect patterns that indicate a fault on turbine generators. Then, we extend the problem to detect future faults. Therefore, this review will consist of analysing techniques to tackle the challenges of each machine learning stage, such as data pre-processing, feature engineering, and the selection of the best-suited model. By using specific evaluation metrics, the expected final result of using these techniques will be an improvement in the early prediction of a future fault. This improvement will have an increase in the availability of the turbine, and therefore in energy production.
Carbon Footprint-Energy Detection for Desalination Small Plant Adaptation Response
Authors: Ghani Latifah Abdul , Ali Nora’aini , Nazaran Ilyanni Syazira , Hanafiah Marlia M. , Yatim Norhafiza Ilyana
Published: November 2021

The Life Cycle Assessment (LCA) system, which can be used as a decision support tool for managing environmental sustainability, includes carbon footprint assessment as one of the available methodologies. In this study, a carbon footprint assessment was used to investigate seawater production systems of a desalination plant in Senok, Kelantan, Malaysia. Three stages of the desalination plant processing system were investigated and the inventory database was developed using the relevant model framework. Subsequently, measurements and interpretations were performed on several key indicators such as greenhouse gases, energy efficiency, acidic gases, smog, and toxic gases. Overall, the results of the study indicate that the Reverse Osmosis (RO) technology that is used in the desalination plant in the study area is one of the best options to meet the demands of the environmental sustainability agenda (SDGs). This is due to the lower carbon dioxide (CO2) emission, of about 3.5 × 10−2 kg of CO2 eq per m3/year, that was recorded for the entire operation of the system. However, several factors that influence important errors in carbon footprint decisions, such as the lack of EIA reporting data and the literature on carbon footprint in the Malaysian scenario, in addition to direct and indirect carbon input calculations, need to be identified in more detail in future research.
Scalable Microgrid Process Model: The Results of an Off-Grid Household Experiment
Authors: Sysko-Romańczuk Sylwia , Kluj Grzegorz , Hawrysz Liliana , Rokicki Łukasz , Robak Sylwester
Published: November 2021

The security of national energy systems as well as the transition to a low-carbon future are two hot topics of discussion in the international political arena. Research on the stability of centralized energy systems is currently focused on distributed generation. Developing a scalable microgrid model enabling its massive adoption is one of the safest and feasible ways to solve such problem. The paper aims to fill an existing gap regarding the operation model of microgrids that is a barrier for the large-scale integration of those in the conventional grid network. In the proposed approach the authors identified key processes to be considered when operating microgrids, in the conditions shown through an experimental (simulation) campaign. A three-phase research was performed: (1) systematic literature review to explore the management models of a stand-alone microgrid design and management; (2) a household experiment; and (3) a computer simulation of energy balance for a selected household. We identified eight key processes constituting a scalable microgrid: five core processes, two supporting processes, and one management process. Subsequently, we developed a map of these processes obtaining a microgrid process model for massive adoption. The model of processes can be considered as a repeatable pattern of conduct in the creation and maintenance of microgrids, which their future owners can follow. To support our literature findings, we performed an experiment and a computer simulation of three sub-processes of the (re)design of the infrastructure process: (1) wind turbine selection, (2) photovoltaic power plant selection, and (3) energy-storage selection. Results confirm conditional stability of the analyzed microgrid and the need for cyclical simulation exercises until unconditional stability is achieved. In terms of sustainability, to keep the microgrid permanently in a positive energy balance will require the implementation of all key processes.
Performance of Common Rail Direct Injection (CRDi) Engine Using Ceiba Pentandra Biodiesel and Hydrogen Fuel Combination
Authors: Khan T. M. Yunus , Soudagar Manzoore Elahi M. , Khandal S. V. , Javed Syed , Mokashi Imran , Baig Maughal Ahmed Ali , Ismail Khadiga Ahmed , Elfasakhany Ashraf
Published: November 2021

An existing diesel engine was fitted with a common rail direct injection (CRDi) facility to inject fuel at higher pressure in CRDi mode. In the current work, rotating blades were incorporated in the piston cavity to enhance turbulence. Pilot fuels used are diesel and biodiesel of Ceiba pentandra oil (BCPO) with hydrogen supply during the suction stroke. Performance evaluation and emission tests for CRDi mode were carried out under different loading conditions. In the first part of the work, maximum possible hydrogen substitution without knocking was reported at an injection timing of 15° before top dead center (bTDC). In the second part of the work, fuel injection pressure (IP) was varied with maximum hydrogen fuel substitution. Then, in the third part of the work, exhaust gas recirculation (EGR), was varied to study the nitrogen oxides (NOx) generated. At 900 bar, HC emissions in the CRDi engine were reduced by 18.5% and CO emissions were reduced by 17% relative to the CI mode. NOx emissions from the CRDi engine were decreased by 28% relative to the CI engine mode. At 20%, EGR lowered the BTE by 14.2% and reduced hydrocarbons, nitrogen oxide and carbon monoxide by 6.3%, 30.5% and 9%, respectively, compared to the CI mode of operation.
Reconfiguration Strategy for DC Distribution Network Fault Recovery Based on Hybrid Particle Swarm Optimization
Authors: Yang Minsheng , Li Jianqi , Li Jianying , Yuan Xiaofang , Xu Jiazhu
Published: November 2021

DC distribution network faults seriously affect the reliability of system power supply. Therefore, this paper proposes a fault recovery reconfiguration strategy for DC distribution networks, based on hybrid particle swarm optimization. The original particle swarm algorithm is improved by simplifying the distribution network structure, introducing Lévy Flight, and designing an adaptive coding strategy. First, the distribution network structure is equivalently simplified to reduce the problem dimensionality. Further, the generated branch groups are ensured to satisfy the radial constraints based on the adaptive solution strategy. Subsequently, Lévy flight is introduced to achieve intra-group optimality search for each branch group. The method is simulated in several distribution systems and analyzed in comparison with the particle swarm algorithm, genetic algorithm, and cuckoo algorithm. Finally, the results validate the accuracy and efficiency of the proposed method.
Identifying Key Factors in Determining Disparities in Energy Consumption in China: A Household Level Analysis
Authors: Yang Ling , Zhao Kai , Zhao Yankai , Zhong Mengyuan
Published: November 2021

With the rapid progress of socio-economic development and urbanization in China, a wide variety of literature has focused on the phenomenon of energy-consumption disparity, which in turn could be related to numerous fundamental energy dilemmas that China must deal with now or soon, including energy use inefficiency, regional energy shortage, insufficient use of green energy, etc. However, in most cases, only a tendency scenario is discussed, while identifying which factors are more likely to affect the improvement of energy supply/use has not yet been fully explored. Therefore, this paper attempts to explore differences in energy consumption in specific, household-level aspects. Based on the information provided by Chinese General Social Survey (CGSS2015), the Gini coefficient and the Lorentz asymmetry coefficient are used to measure the difference among various categories of energy type and end use within and between different geographical sub-groups. The findings show that: (1) household energy-consumption behaviors exhibit a complicated effect on the overall level of energy-consumption difference; (2) from the supply side, energy users show the most significant difference in biomass energy consumption, while from the demand side, the contribution of space heating to the difference in total energy consumption is the highest; (3) a great urban–rural difference in energy consumption is generally observed with its difference within rural areas being much greater than in urban areas; (4) the eastern, middle and western regions weight differently in explaining the overall difference of energy consumption. These findings provide meaningful materials and references for policymakers in China to understand the overall situation of individual energy consumption to a great extent, and to locate key points to reform the current energy policy framework.
Thermal Properties of Shape-Stabilized Phase Change Materials Based on Porous Supports for Thermal Energy Storage
Authors: Dominici Franco , Miliozzi Adio , Torre Luigi
Published: November 2021

The use of phase change materials (PCM) for thermal energy storage (TES) is of great relevance, especially for the exploitation, in various ways, of the major ecological resource offered by solar energy. Unfortunately, the transition to the liquid state of PCM requires complex systems and limits their application. The goal of producing shape-stabilized phase change materials (SSPCM) is mainly pursued with the use of media capable of containing PCM during solid/liquid cycles. In this work, four cheap shape stabilizers were considered: sepiolite, diatomite, palygorskite and zeolite and two molten salts as PCM, for medium (MT) and high temperature (HT). The SSPCM, produced with an energy saving method, showed good stability and thermal storage performances. Diatomite reaches up to 400% wt. of encapsulated PCM, with a shape stabilization coefficient (SSc) of 97.7%. Zeolite exhibits a SSc of 87.3% with 348% wt. of HT-PCM. Sepiolite contains 330% wt. of MT-PCM with an SSc of 82.7. Therefore, these materials show characteristics such that they can be efficiently used in thermal energy storage systems, both individually and inserted in a suitable matrix (for example a cementitious matrix).
Biomass Potential of the Marginal Land of the Polish Sudetes Mountain Range
Authors: Helis Marek , Strzelczyk Maria , Golimowski Wojciech , Steinhoff-Wrześniewska Aleksandra , Paszkiewicz-Jasińska Anna , Hawrot-Paw Małgorzata , Koniuszy Adam , Hryniewicz Marek
Published: November 2021

Marginal land is the area remaining in agricultural use, which is not suitable for food production because of its unfavorable ecological, anthropological, and economic conditions. A certain amount of such land exists in mountainous areas. An analysis was undertaken on the example of the Polish Sudeten mountain range of energy use. The study aimed to estimate the biomass potential for the efficient use of agricultural land in mountain areas. The characteristics of the Polish Sudeten Mountains mountain range were characterized using Geographic Information System (GIS) methods. The Polish Sudeten Mountains covers an area of 370,392 ha, 95,341 ha of which is arable land, 35,726 ha of which is class 5 bonitation land with a northern exposure of 19,030 ha and southern exposure of 16,696 ha. Depending on the sowing structure, we can obtain 331,639 tons/year of dry biomass (Miscanthus sacchariflorus on the southern and Helianthus tuberoses on northern exposure). Fertilization levels will significantly affect low yielding plants, and water stress significantly reduced yields in all cases. Due to the steep slope of the 5th-grade halves and intensive rainfall in the mountain region, the establishment of perennial plantations is recommended. The research shows that after the first year of cultivation, yields of 9.27 tons/ha of dry matter can be obtained with a low yield of trees, shrubs and perennials.
Evaluation of Multiyear Weather Data Effects on Hygrothermal Building Energy Simulations Using WUFI Plus
Authors: Libralato Michele , De Angelis Alessandra , Tornello Giulia , Saro Onorio , D’Agaro Paola , Cortella Giovanni
Published: November 2021

Transient building energy simulations are powerful design tools that are used for the estimation of HVAC demands and internal hygrothermal conditions of buildings. These calculations are commonly performed using a (often dated) typical meteorological year, generated from past weather measurements excluding extreme weather conditions. In this paper the results of multiyear building simulations performed considering coupled Heat and Moisture Transfer (HMT) in building materials are presented. A simple building is simulated in the city of Udine (Italy) using a weather record of 25 years. Performing a multiyear simulation allows to obtain a distribution of results instead of a single number for each variable. The small therm climate change is shown to influence thermal demands and internal conditions with multiyear effects. From this results it is possible to conclude that weather records used as weather files have to be periodically updated and that moisture transfer is relevant in energy and comfort calculations. Moreover, the simulations are performed using the software WUFI Plus and it is shown that using a thermal model for the building envelope could be a non negligible simplification for the comfort related calculations.
Time-Lapse CSEM Monitoring: Correlating the Anomalous Transverse Resistance with SoPhiH Maps
Authors: Menezes Paulo T. L. , Correa Jorlivan L. , Alvim Leonardo M. , Viana Adriano R. , Sansonowski Rui C.
Published: November 2021

The CSEM method, which is frequently used as a risk-reduction tool in hydrocarbon exploration, is finally moving to a new frontier: reservoir monitoring and surveillance. In the present work, we present a CSEM time-lapse interpretation workflow. One essential aspect of our workflow is the demonstration of the linear relationship between the anomalous transverse resistance, an attribute extracted from CSEM data inversion, and the SoPhiH attribute, which is estimated from fluid-flow simulators. Consequently, it is possible to reliably estimate SoPhiH maps from CSEM time-lapse surveys using such a relationship. We demonstrate our workflow’s effectiveness in the mature Marlim oilfield by simulating the CSEM time-lapse response after 30 and 40 years of seawater injection and detecting the remaining sweet spots in the reservoir. The Marlim reservoirs are analogous to several turbidite reservoirs worldwide, which can also be appraised with the proposed workflow. The prediction of SoPhiH maps by using CSEM data inversion can significantly improve reservoir time-lapse characterization.
Validation of Voltage Instability Detection and Control Using a Real Power System Incident
Authors: Lambrou Charalambos , Mandoulidis Panagiotis , Vournas Costas
Published: November 2021

This paper applies a voltage instability monitoring method based on voltage and current measurements from a transmission bus PMU on the Hellenic Interconnected System using both unstable and marginally stable scenarios, derived from the historical 12 July 2004 blackout of the Athens area. The effectiveness, selectivity and reliability of the proposed monitoring method is clearly demonstrated, allowing its integration into a System Protection Scheme with direct load shedding. It is shown that the proposed instability detection and control scheme could have prevented the voltage collapse if applied at the time of the event.
Exergetic and Economic Evaluation of CO2 Liquefaction Processes
Authors: Chen Feng , Morosuk Tatiana
Published: November 2021

The transport of CO2, as a part of the carbon capture and storage chain, has received increased attention in the last decade. This paper aims to evaluate the most promising CO2 liquefaction processes that can be used for port-to-port and port–offshore CO2 ship transportation. The energetic, exergetic, and economic analyses are applied. The liquefaction pressure has been set to 15 bar (liquefaction temperature −30 °C), which corresponds to the design of the existing CO2 carriers. The three-stage vapor-compression process has been selected among closed systems (with propane-R290, ammonia-R717, and R134a as the working fluid) and the precooled Linde–Hampson process—as the open system (with R717). The three-stage vapor-compression process R290 shows the lowest energy consumption, and the CO2 liquefaction cost 21.3 USD/tCO2. Although the power consumption of precooled Linde–Hampson process is 3.1% higher than the vapor-compression process with R209, the lowest total capital expenditures are notable. The CO2 liquefaction cost of precooled Linde–Hampson process is 21.13 USD/tCO2. The exergetic efficiency of the three-stage vapor-compression process with R290 is 66.6%, while the precooled Linde–Hampson process is 64.8%.
Online Machine Learning of Available Capacity for Vehicle-to-Grid Services during the Coronavirus Pandemic
Authors: Shipman Rob , Roberts Rebecca , Waldron Julie , Rimmer Chris , Rodrigues Lucelia , Gillott Mark
Published: November 2021

Vehicle-to-grid services make use of the aggregated capacity available from a fleet of vehicles to participate in energy markets, help integrate renewable energy in the grid and balance energy use. In this paper, the critical components of such a service are described in the context of a commercial service that is currently under development. Key among these components is the prediction of available capacity at a future time. In this paper, we extend a previous work that used a deep learning recurrent neural network for this task to include online machine learning, which enables the network to continually refine its predictions based on observed behaviour. The coronavirus pandemic that was declared in 2020 resulted in closures of the university and substantial changes to the behaviour of the university fleet. In this work, the impact of this change in vehicles usage was used to test the predictions of a network initially trained using vehicle trip data from 2019 with and without online machine learning. It is shown that prediction error is significantly reduced using online machine learning, and it is concluded that a similar capability will be of critical importance for a commercial service such as the one described in this paper.
Solidification Enhancement in a Triple-Tube Latent Heat Energy Storage System Using Twisted Fins
Authors: Sun Xinguo , Mahdi Jasim M. , Mohammed Hayder I. , Majdi Hasan Sh. , Zixiong Wang , Talebizadehsardari Pouyan
Published: November 2021

This work evaluates the influence of combining twisted fins in a triple-tube heat exchanger utilised for latent heat thermal energy storage (LHTES) in three-dimensional numerical simulation and comparing the outcome with the cases of the straight fins and no fins. The phase change material (PCM) is in the annulus between the inner and the outer tube, these tubes include a cold fluid that flows in the counter current path, to solidify the PCM and release the heat storage energy. The performance of the unit was assessed based on the liquid fraction and temperature profiles as well as solidification and the energy storage rate. This study aims to find suitable and efficient fins number and the optimum values of the Re and the inlet temperature of the heat transfer fluid. The outcomes stated the benefits of using twisted fins related to those cases of straight fins and the no-fins. The impact of multi-twisted fins was also considered to detect their influences on the solidification process. The outcomes reveal that the operation of four twisted fins decreased the solidification time by 12.7% and 22.9% compared with four straight fins and the no-fins cases, respectively. Four twisted fins improved the discharging rate by 12.4% and 22.8% compared with the cases of four straight fins and no-fins, respectively. Besides, by reducing the fins’ number from six to four and two, the solidification time reduces by 11.9% and 25.6%, respectively. The current work shows the impacts of innovative designs of fins in the LHTES to produce novel inventions for commercialisation, besides saving the power grid.
Particle-Size Fractionation and Thermal Variation of Oil Shales in the Songliao Basin, NE China: Implication for Hydrocarbon-Generated Process
Authors: Jia Jianliang , Liu Zhaojun
Published: November 2021

The synchronous variation and association of organic matter (OM) and minerals in the hydrocarbon-generated process of oil shales are poorly understood. The goal of the paper is to investigate OM occurrence and thermal variation so as to reveal the hydrocarbon generation potential of oil shales. Based on detailed analyses of particle, organic, mineral, and thermal data from lacustrine oil shales in the Songliao Basin, we observed three layers of shale particles after settling in the water column characterized by a distinct color, degree of consolidation, and particle size. The particle sizes are divided into three ranges of fine grain (<1 μm), medium grain (1–20 μm), and coarse grain (>20 μm) via laser particle analysis. The particle-size distribution indicates the presence of OM polymerization and dominant contribution of the associated mineral surface and bioclastic OMs to the OM abundance of oil shale. Various OM occurrences are influenced by OM sources and redox conditions, whereas the degree of biodecomposition and particle sizes affect the placement of OM occurrences. Based on multiple thermal analyses, a synchronous response of OM and minerals to thermal variation dominates at 300–550 °C. The I/S and chlorite minerals are characterized by an entire illitization, while solid/absorbed OMs and hydrocarbon-generated water were expelled in large quantities. This contributes to major loss weights of oil shales during heating. The peak hydrocarbon-generated rate occurred at 457 °C for oil shales, corresponding to around 1.3% vitrinite reflectance value. These results are suggested to improve the understanding of OM occurrences and the thermal degradation constraint on the hydrocarbon-generated process, and contribute to the interpretation of the hydrocarbon generation potential and in-situ exploitation of oil shales.