Search results for: energy performance assessment

Authors: Lee Myung-Won, Kwak Keun-Chang

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This paper is concerned with knowledge representation and extraction of fuzzy if-then rules using Interval Type-2 Context-based Fuzzy C-Means clustering (IT2-CFCM) with the aid of fuzzy granulation. This proposed clustering algorithm is based on information granulation in the form of IT2 based Fuzzy C-Means (IT2-FCM) clustering and estimates the cluster centers by preserving the homogeneity between the clustered patterns from the IT2 contexts produced in the output space. Furthermore, we can obtain the automatic knowledge representation in the design of Radial Basis Function Networks (RBFN), Linguistic Model (LM), and Adaptive Neuro-Fuzzy Networks (ANFN) from the numerical input-output data pairs. We shall focus on a design of ANFN in this paper. The experimental results on an estimation problem of energy performance reveal that the proposed method showed a good knowledge representation and performance in comparison with the previous works.

Keywords: IT2-FCM, IT2-CFCM, context-based fuzzy clustering, adaptive neuro-fuzzy network, knowledge representation

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Authors: Suvimon Wajeetongratana, Sittichai Thammasane

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This research objective was to study the development training that affecting the work performance of Suan Sunandha Rajabhat University manpower. The sample of 200 manpower was used to collect data for the survey. The statistics for data analysis were frequency percentage, mean value, standard deviation and hypothesis testing using independent samples (t-test). The study indicated that the development training has the most affect to employees in the high level and the second was coaching by the senior follow by the orientation in case of changing jobs task or changing positions. Interms of manpower work performance have three performance areas are quality of the job is better than the original. Moreover the results of hypothesis testing found that the difference personal information including gender, age, education, income per month have difference effectiveness of attitudes and also found the develop training is correlated with the performance of employees in the same direction.

Keywords: development training, employees job satisfaction, work performance, Sunandha Rajabhat University

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Authors: Rihab Hentati, Younes Boujelbene

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Nowadays we realize more and more than the value of a company is not only a function of its means of production but depends essentially on the managerial aptitude and orientation to implement the material and human means for generating profitability. Indeed, a productive R&D activity, a good strategy, and innovation are originally supplementary benefits that increase the value of the business. Is this ‘value-added’ closely linked to innovation? The purpose of our research is to Meta-analyze the results of 56 empirical studies in order to explain the overall effect of innovation on performance of small and medium-sized enterprises. In order to justify the differences in the results, we look for the moderating factors that may affect the innovation-performance relationship. We find a positive and significant relationship between innovation and performance in small and medium-sized enterprises. The results also note a positive relationship between entrepreneurial orientation, research and development (R&D), and performance in SMEs. In addition, innovation has a strong impact on performance measured both with accounting and market index. The originality of the article is based on a rigorous synthesis, based on several statistical tools, of an important subject of research in finance.

Keywords: innovation, performance, entrepreneurial orientation, meta-analysis, moderator variables

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Authors: Yongjian Gu

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Ocean thermal energy is one of the ocean energy sources. It is a renewable, sustainable, and green energy source. Ocean thermal energy conversion (OTEC) applies the ocean temperature gradient between the warmer surface seawater and the cooler deep seawater to run a heat engine and produce a useful power output. Unfortunately, the ocean temperature gradient is not big. Even in the tropical and equatorial regions, the surface water temperature can only reach up to 28oC and the deep water temperature can be as low as 4oC. The thermal efficiency of the OTEC plants, therefore, is low. In order to improve the plant thermal efficiency by using the limited ocean temperature gradient, some OTEC plants use the method of adding more equipment for better heat recovery, such as heat exchangers, pumps, etc. Obviously, the method will increase the plant's complexity and cost. The more important impact of the method is the additional equipment needs to consume power too, which may have an adverse effect on the plant net power output, in turn, the plant thermal efficiency. In the paper, the author first describes varied OTEC plants and the practice of using the method of adding more equipment for improving the plant's thermal efficiency. Then the author proposes a parameter, plant back works ratio ϕ, for measuring if the added equipment is appropriate for the plant thermal efficiency improvement. Finally, in the paper, the author presents examples to illustrate the application of the back work ratio ϕ as a key parameter in the OTEC plant design and operation.

Keywords: ocean thermal energy, ocean thermal energy conversion (OTEC), OTEC plant, plant back work ratio ϕ

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Authors: S. Kumchoo

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The result of suggestion for low energy diet (1,000-1,200 kcal) in obese women to the effect on body weight, waist circumference and body mass index (BMI) in this experiment. Quisi experimental research was used for this study and it is a One-group pretest-posttest designs measurement method. The aim of this study was body weight, waist circumference and body mass index (BMI) reduction by using low energy diet (1,000-1,200 kcal) in obese women, the result found that in 15 of obese women that contained their body mass index (BMI) ≥ 30, after they obtained low energy diet (1,000-1,200 kcal) within 2 weeks. The data were collected before and after of testing the results showed that the average of body weight decrease 3.4 kilogram, waist circumference value decrease 6.1 centimeter and the body mass index (BMI) decrease 1.3 kg.m² from their previous body weight, waist circumference and body mass index (BMI) before experiment started. After this study, the volunteers got healthy and they can choose or select some food for themselves. For this study, the research can be improved for data development for forward study in the future.

Keywords: body weight, waist circumference, low energy diet, BMI

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Authors: Rizwan Ullah, Abdar Ali, Zahid Ullah

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This paper illustrates the study of three isolated zero voltage switched (ZVS) PWM full bridge (FB) converters to charge the high voltage battery in the charger of electric vehicle (EV). EV battery chargers have several challenges such as high efficiency, high reliability, low cost, isolation, and high power density. The cost of magnetic and filter components in the battery charger is reduced when switching frequency is increased. The increase in the switching frequency increases switching losses. ZVS is used to reduce switching losses and to operate the converter in the battery charger at high frequency. The performance of each of the three converters is evaluated on the basis of ZVS range, dead times of the switches, conduction losses of switches, circulating current stress, circulating energy, duty cycle loss, and efficiency. The limitations and merits of each PWM FB converter are reviewed. The converter with broader ZVS range, high efficiency and low switch stresses is selected for battery charger applications in EV.

Keywords: electric vehicle, PWM FB converter, zero voltage switching, circulating energy

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Authors: Oktay Nusratov, Ramin Rzaev, Aydin Goyushov

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Fuzzy inference method based approach to the forming of modular intellectual system of assessment the quality of communication services is proposed. Developed under this approach the basic fuzzy estimation model takes into account the recommendations of the International Telecommunication Union in respect of the operation of packet switching networks based on IP-protocol. To implement the main features and functions of the fuzzy control system of quality telecommunication services it is used multilayer feedforward neural network.

Keywords: quality of communication, IP-telephony, fuzzy set, fuzzy implication, neural network

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Authors: Inayat Ur Rehman, Georgia Sakellari

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Cloud computing has evolved into a vital technology for businesses, offering scalability, flexibility, and cost-effectiveness. However, maintaining high availability and optimal performance in the cloud is crucial for reliable services. This paper explores the significance of cloud monitoring and performance optimization in sustaining the high availability of cloud-based systems. It discusses diverse monitoring tools, techniques, and best practices for continually assessing the health and performance of cloud resources. The paper also delves into performance optimization strategies, including resource allocation, load balancing, and auto-scaling, to ensure efficient resource utilization and responsiveness. Addressing potential challenges in cloud monitoring and optimization, the paper offers insights into data security and privacy considerations. Through this thorough analysis, the paper aims to underscore the importance of cloud monitoring and performance optimization for ensuring a seamless and highly available cloud computing environment.

Keywords: cloud computing, cloud monitoring, performance optimization, high availability, scalability, resource allocation, load balancing, auto-scaling, data security, data privacy

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Authors: Austin Ikechukwu Gbasouzor, Sam Nna Omenyi, Sabuj Malli

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This study is an extension of the previous work done with ARS-680 Environmental Chamber. Drying is a complex operation that demands much energy and time. Drying is essentially important for preservation of ginger rhizome. Drying of ginger was modeled, and then the effective diffusion coefficient and activation energy where determined. For this purpose, the experiments were done at six levels of varied temperature ranging from (10, 20, 30, 40, 50, 60°C). The average effective diffusion coefficient for their studies samples for temperature range of 40°C to 70°C was 4.48 x10-10m²/s, 4.96 x10-10m²/s, and 5.31 x10-10m²/s for 0.8, 1.5 and 3m/s drying air velocity respectively. These values closely agreed with the values of effective diffusion coefficients obtained in these studies for the variously treated ginger rhizomes and test conducted.

Keywords: activation energy, diffusion coefficients, drying model, drying time, ginger rhizomes, moisture ratio, thin layer

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Authors: Lia Marchi, Ernesto Antonini

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The impact of industrial sites on people’s living environment both involves detrimental effects on the ecosystem and perceptual-aesthetic interferences with the scenery. These, in turn, affect the economic and social value of the landscape, as well as the wellbeing of workers and local communities. Given the diffusion of the phenomenon and the relevance of its effects, it emerges the need for a joint approach to assess and thus mitigate the impact of factories on the landscape –being this latest assumed as the result of the action and interaction of natural and human factors. However, the impact assessment tools suitable for the purpose are quite heterogeneous and mostly monodisciplinary. On the one hand, green building rating systems (GBRSs) are increasingly used to evaluate the performance of manufacturing sites, mainly by quantitative indicators focused on environmental issues. On the other hand, methods to detect the visual and social impact of factories on the landscape are gradually emerging in the literature, but they generally adopt only qualitative gauges. The research addresses the integration of the environmental impact assessment and the perceptual-aesthetic interferences of factories on the landscape. The GBRSs model is assumed as a reference since it is adequate to simultaneously investigate different topics which affect sustainability, returning a global score. A critical analysis of GBRSs relevant to industrial facilities has led to select the U.S. GBC LEED protocol as the most suitable to the scope. A revision of LEED v4 Building Design+Construction has then been provided by including specific indicators to measure the interferences of manufacturing sites with the perceptual-aesthetic and social aspects of the territory. To this end, a new impact category was defined, namely ‘PA - Perceptual-aesthetic aspects’, comprising eight new credits which are specifically designed to assess how much the buildings are in harmony with their surroundings: these investigate, for example the morphological and chromatic harmonization of the facility with the scenery or the site receptiveness and attractiveness. The credits weighting table was consequently revised, according to the LEED points allocation system. As all LEED credits, each new PA credit is thoroughly described in a sheet setting its aim, requirements, and the available options to gauge the interference and get a score. Lastly, each credit is related to mitigation tactics, which are drawn from a catalogue of exemplary case studies, it also developed by the research. The result is a modified LEED scheme which includes compatibility with the landscape within the sustainability assessment of the industrial sites. The whole system consists of 10 evaluation categories, which contain in total 62 credits. Lastly, a test of the tool on an Italian factory was performed, allowing the comparison of three mitigation scenarios with increasing compatibility level. The study proposes a holistic and viable approach to the environmental impact assessment of factories by a tool which integrates the multiple involved aspects within a worldwide recognized rating protocol.

Keywords: environmental impact, GBRS, landscape, LEED, sustainable factory

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Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

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Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: electrical disaggregation, DTW, general appliance modeling, event detection

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Authors: Chi Zhang, Hua-Peng Chen

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With the increasingly demanding resources in the word, renewable and clean energy has been considered as an alternative way to replace traditional ones. Thus, one of practical examples for using wind energy is wind turbine, which has gained more attentions in recent research. Like most offshore structures, the blades, which is the most critical components of the wind turbine, will be subjected to millions of loading cycles during service life. To operate safely in marine environments, the blades are typically made from fibre reinforced composite materials to resist fatigue delamination and harsh environment. The fatigue crack development of blades is uncertain because of indeterminate mechanical properties for composite and uncertainties under offshore environment like wave loads, wind loads, and humid environments. There are three main delamination failure modes for composite blades, and the most common failure type in practices is subjected to mixed mode loading, typically a range of opening (mode 1) and shear (mode 2). However, the fatigue crack development for mixed mode cannot be predicted as deterministic values because of various uncertainties in realistic practical situation. Therefore, selecting an effective stochastic model to evaluate the mixed mode behaviour of wind turbine blades is a critical issue. In previous studies, gamma process has been considered as an appropriate stochastic approach, which simulates the stochastic deterioration process to proceed in one direction such as realistic situation for fatigue damage failure of wind turbine blades. On the basis of existing studies, various Paris Law equations are discussed to simulate the propagation of the fatigue crack growth. This paper develops a Paris model with the stochastic deterioration modelling according to gamma process for predicting fatigue crack performance in design service life. A numerical example of wind turbine composite materials is investigated to predict the mixed mode crack depth by Paris law and the probability of fatigue failure by gamma process. The probability of failure curves under different situations are obtained from the stochastic deterioration model for comparisons. Compared with the results from experiments, the gamma process can take the uncertain values into consideration for crack propagation of mixed mode, and the stochastic deterioration process shows a better agree well with realistic crack process for composite blades. Finally, according to the predicted results from gamma stochastic model, assessment strategies for composite blades are developed to reduce total lifecycle costs and increase resistance for fatigue crack growth.

Keywords: Reinforced fibre composite, Wind turbine blades, Fatigue delamination, Mixed failure mode, Stochastic process.

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Authors: Nadia Allouache, Mohamed Belmedani

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—It is imperative today to further explore alternatives to fossil fuels by promoting in particular renewable sources such as solar energy to produce cold. It is also important to carefully examine its current state as well as its future prospects in order to identify the best conditions to support its optimal development. Technologies linked to this alternative source fascinate their users because they seem magical in their ability to directly transform solar energy into cooling without resorting to polluting fuels such as those derived from hydrocarbons or other toxic substances. In addition, these not only allow significant savings in electricity, but can also help reduce the costs of electrical energy production when applied on a large scale. In this context, our study aims to analyze the performance of solar adsorption cooling systems by selecting the appropriate pair Adsorbent/Adsorbat. This paper presents a model describing the heat and mass transfer in tubular finned adsorber of solar adsorption refrigerating machine. The modelisation of the solar reactor take into account the heat and mass transfers phenomena. The reactor pressure is assumed to be uniform, the reactive reactor is characterized by an equivalent thermal conductivity and assumed to be at chemical and thermodynamic equilibrium. The numerical model is controlled by heat, mass and sorption equilibrium equations. Under the action of solar radiation, the mixture of adsorbent–adsorbate has a transitory behavior. Effect of key parameters on the adsorbed quantity and on the thermal and solar performances are analyzed and discussed. The results show that, The performances of the system that depends on the incident global irradiance during a whole day depends on the weather conditions. For the used working pairs, the increase of the fins number corresponds to the decreasing of the heat losses towards environmental and the increasing of heat transfer inside the adsorber. The system performances are sensitive to the evaporator and condenser temperatures. For the considered data measured for clear type days of may and july 2023 in Algeria and Tunisia, the performances of the cooling system are very significant in Algeria compared to Tunisia.

Keywords: adsorption, adsorbent-adsorbate pair, finned reactor, numerical modeling, solar energy

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Authors: Khalid Abdullah Alshuhail, Syrif Junidi, Ideisan Abu-Abdoum, Abdulsalam Aldawoud

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For the intention of reducing energy consumption, a proposed construction brick was made of imitation termite mound soil referred here as termite brick (TB). To calculate the thermal performance, a real case model was constructed by using this biomimetic brick for testing purposes. This paper aims at investigating the thermal performance of this brick during different climatic months. Its thermal behaviour was thoroughly studied over the course of four months by using continuous method (CMm). The main parameters were focused on temperature and relative humidity. It was found that the TB does not perform similarly in all four months and/or in all orientations. Each four-month model study was deeply analyzed. By using the CMm method, the model was also examined. The measuring period shows generally that internal temperature and internal humidity are higher in the roof within 2 degrees and lowest at north wall orientation. The relative humidity was also investigated systematically. The paper reveals more interesting findings.

Keywords: building material, continious monitoring, orientation, wall, temprature

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Authors: Musatafa Abbas Abbood Albadr, Masri Ayob, Sabrina Tiun, Fahad Taha Al-Dhief, Mohammad Kamrul Hasan

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Breast Cancer (BC) is considered one of the most frequent reasons of cancer death in women between 40 to 55 ages. The BC is diagnosed by using digital images of the FNA (Fine Needle Aspirate) for both benign and malignant tumors of the breast mass. Therefore, this work proposes the Online Sequential Extreme Learning Machine (OSELM) algorithm for diagnosing BC by using the tumor features of the breast mass. The current work has used the Wisconsin Diagnosis Breast Cancer (WDBC) dataset, which contains 569 samples (i.e., 357 samples for benign class and 212 samples for malignant class). Further, numerous measurements of assessment were used in order to evaluate the proposed OSELM algorithm, such as specificity, precision, F-measure, accuracy, G-mean, MCC, and recall. According to the outcomes of the experiment, the highest performance of the proposed OSELM was accomplished with 97.66% accuracy, 98.39% recall, 95.31% precision, 97.25% specificity, 96.83% F-measure, 95.00% MCC, and 96.84% G-Mean. The proposed OSELM algorithm demonstrates promising results in diagnosing BC. Besides, the performance of the proposed OSELM algorithm was superior to all its comparatives with respect to the rate of classification.

Keywords: breast cancer, machine learning, online sequential extreme learning machine, artificial intelligence

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Authors: Shahram Jamali, Samira Hamed

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One of the open issues in Random Early Detection (RED) algorithm is how to set its parameters to reach high performance for the dynamic conditions of the network. Although original RED uses fixed values for its parameters, this paper follows a model-based approach to upgrade performance of the RED algorithm. It models the routers queue behavior by using the Markov model and uses this model to predict future conditions of the queue. This prediction helps the proposed algorithm to make some tunings over RED's parameters and provide efficiency and better performance. Widespread packet level simulations confirm that the proposed algorithm, called Markov-RED, outperforms RED and FARED in terms of queue stability, bottleneck utilization and dropped packets count.

Keywords: active queue management, RED, Markov model, random early detection algorithm

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Authors: Habtamu Anagaw Muluneh, Gebregziabher Kahsay, Tamiru Negussie

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Theoretical study of the density of state, condensation energy, specific heat, and magnetization in a spin-triplet superconductor are the main goals of this work. Utilizing the retarded double-time temperature-dependent Green's function formalism and building a model Hamiltonian for the system at hand, we were able to derive the expressions for the parameters mentioned above. The phase diagrams are plotted using MATLAB scripts. From the phase diagrams, the density of electrons increases as the excitation energy increases, and the maximum excitation energy is equal to the superconducting gap, but it decreases when the value exceeds the gap and finally becomes the same as the density of the normal state. On the other hand, the condensation energy decreases with the increase in temperature and attains its minimum value at the superconducting transition temperature but increases with the increase in superconducting transition temperature (TC) and finally becomes zero, implying the superconducting energy is equal to the normal state energy. The specific heat increases with the increase in temperature, attaining its maximum value at the TC and then undergoing a jump, showing the presence of a second-order phase transition from the superconducting state to the normal state. Finally, the magnetization of both the itinerant and localized electrons decreases with the increase in temperature and finally becomes zero at TC = 1.6 K and magnetic phase transition temperature T = 2 K, respectively, which results in a magnetic phase transition from a ferromagnetic to a paramagnetic state. Our finding is in good agreement with the previous findings.

Keywords: spin triplet superconductivity, Green’s function, condensation energy, density of state, specific heat, magnetization

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Authors: Mohammadreza Kashizadeh, Mohammadamin Hashemi

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This paper explores a kinetic building facade designed for optimal energy capture and architectural expression. The system integrates photovoltaic panels with soft robotic actuators for precise solar tracking, resulting in enhanced electricity generation compared to static facades. Driven by the growing interest in dynamic building envelopes, the exploration of facade systems are necessitated. Increased energy generation and regulation of energy flow within buildings are potential benefits offered by integrating photovoltaic (PV) panels as kinetic elements. However, incorporating these technologies into mainstream architecture presents challenges due to the complexity of coordinating multiple systems. To address this, the design leverages soft robotic actuators, known for their compliance, resilience, and ease of integration. Additionally, the project investigates the potential for employing Large Language Models (LLMs) to streamline the design process. The research methodology involved design development, material selection, component fabrication, and system assembly. Grasshopper (GH) was employed within the digital design environment for parametric modeling and scripting logic, and an LLM was experimented with to generate Python code for the creation of a random surface with user-defined parameters. Various techniques, including casting, Three-dimensional 3D printing, and laser cutting, were utilized to fabricate physical components. A modular assembly approach was adopted to facilitate installation and maintenance. A case study focusing on the application of this facade system to an existing library building at Polytechnic University of Milan is presented. The system is divided into sub-frames to optimize solar exposure while maintaining a visually appealing aesthetic. Preliminary structural analyses were conducted using Karamba3D to assess deflection behavior and axial loads within the cable net structure. Additionally, Finite Element (FE) simulations were performed in Abaqus to evaluate the mechanical response of the soft robotic actuators under pneumatic pressure. To validate the design, a physical prototype was created using a mold adapted for a 3D printer's limitations. Casting Silicone Rubber Sil 15 was used for its flexibility and durability. The 3D-printed mold components were assembled, filled with the silicone mixture, and cured. After demolding, nodes and cables were 3D-printed and connected to form the structure, demonstrating the feasibility of the design. This work demonstrates the potential of soft robotics and Artificial Intelligence (AI) for advancements in sustainable building design and construction. The project successfully integrates these technologies to create a dynamic facade system that optimizes energy generation and architectural expression. While limitations exist, this approach paves the way for future advancements in energy-efficient facade design. Continued research efforts will focus on cost reduction, improved system performance, and broader applicability.

Keywords: artificial intelligence, energy efficiency, kinetic photovoltaics, pneumatic control, soft robotics, sustainable building

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Authors: Hsin-Chih Lai, Yung-Lung Lee, Yun-Yao Chi, Ching-Yi Horng, Pei-Chih Wu, Hsien-Chang Wang

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Taiwan, a climatically challenged island, has always been keen on the issue of water resource management due to its limitations in water storage. Since water resource management has been the focal point of many adaptations to climate change, there has been a lack of attention on another issue, water quality. This study chooses the Errer River Basin as the experimental focus for water quality in Taiwan. With the Errer River Basin being one of the most polluted rivers in Taiwan, this study observes the effects of climate change on this river over a period of time. Taiwan is also targeted by multiple typhoons every year, the heavy rainfall and strong winds create problems of pollution being carried to different river segments, including into the ocean. This study aims to create an impact and risk assessment on Errer River Basin, to show the connection from climate change to potential extreme events, which in turn could influence water quality and ultimately human health. Using dynamic downscaling, this study narrows the information from a global scale to a resolution of 1 km x 1 km. Then, through interpolation, the resolution is further narrowed into a resolution of 200m x 200m, to analyze the past, present, and future of extreme events. According to different climate change scenarios, this study designs an assessment index on the vulnerability of the Errer River Basin. Through this index, Errer River inhabitants can access advice on adaptations to climate change and act accordingly.

Keywords: climate change, adaptation, water quality, risk assessment

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Authors: Majid Saaly, Shahriar Tavousi Tafreshi, Mehdi Nazari Afshar

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The structural systems with the sandwich composite wall (SCSSC) are of very popular due to their ductileness and competency to swallow more energy and power than standard reinforced concrete shear walls. The purpose of this enhanced system is in high-rise building, Nuclear power plant facilities, and bridge slabs are much more. SCSSCs showed acceptable seismic performance under experimental tests and cyclic loading from the points of view of in-plane and out-of-plane shear and flexural interaction, in-plane punching shear, and compressive behavior. The use of sandwich composite walls with J-hook connectors has a significant effect on energy dissipation and reduction of dynamic responses of mid-rise and high-rise structural models. By changing the systems of the building from SW to SCWJ, the maximum inter-story drift values of ten- and fifteen-story models are reduced by up to 25% and 35%, respectively.

Keywords: J-Hook sandwich composite walls, fling step, directivity, IDA analyses, fractile curves

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Authors: Babatunde J. Falaye

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In this study, we obtain the approximate analytical solutions of the radial Schrödinger equation for the Deng-Fan diatomic molecular potential by using exact quantization rule approach. The wave functions have been expressed by hypergeometric functions via the functional analysis approach. An extension to rotational-vibrational energy eigenvalues of some diatomic molecules are also presented. It is shown that the calculated energy levels are in good agreement with the ones obtained previously E_nl-D (shifted Deng-Fan).

Keywords: Schrödinger equation, exact quantization rule, functional analysis, Deng-Fan potential

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Authors: Sabina Ampon-Wireko

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Purpose: The study explores the influence of the organizational climate of silence on job performance through the mediating effects of work engagement (WE). Further, the degree to which supervisor support (SS) and work engagement moderate job performance are examined. Method: Using a questionnaire, the study collected 565 valid responses from frontline nurses in Ghana. The hierarchical regression technique was employed in estimating the relationship between the variables. Findings: The results showed a significant negative influence of top managers' and supervisors' attitudes to silence on both contextual and task performance. Communication opportunities, however, revealed positive and significant effects on contextual and task performance. Work engagement had no role in mediating top managers' and supervisors’ attitudes toward silence, communication opportunities, and task performance. Supervisor support acted as a moderating factor in the relationship between job engagement and task performance. In contrast, despite the direct positive relationship between supervisor support and contextual performance, it failed to moderate the relationship between work engagement and contextual performance. Practical implications: The study's findings demonstrate the need for health managers and supervisors to become more conscious of silence. The findings offer diverse recommendations for encouraging the sharing of relevant ideas, facts, and opinions within the health sector.

Keywords: organizational climate of silence, job performance, work engagement, supervisor support, frontline nurses

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Authors: Edgard Gnansounoua, Pavel Vaskan, Elia Ruiz Pachón

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This work addresses the economic and environmental performance of integrated biorefineries based on sugarcane juice and residues in the context of Brazil. We have considered four multiproduct scenarios; two from existing Brazilian sugar mills and the others from ethanol autonomous distilleries. They are integrated biorefineries producing first (1G) and second (2G) generation ethanol, sugar, molasses (for animal feed) and electricity. We show the results for the analysis and comparison of the different scenarios using a techno-economic value-based approach and LCA methodology. We have found that all the analysed scenarios show positive values of Climate change and Fossil depletion reduction as compared to the reference systems. However the scenario producing only ethanol shows less efficiency in Human toxicity, Freshwater ecotoxicity and Freshwater eutrophication impacts. The best economic configuration is provided by the scenario with the largest ethanol production. On the other hand, the best environmental performance is presented by the scenario with full integration sugar – 1G2G ethanol production. The integration of 2G based residues in a 1G ethanol production plant leads to positive environmental impacts compared to the conventional 1G industrial plant but proves to be more expensive.

Keywords: sugarcane, biorefinery, 1G/2G bioethanol integration, LCA, Brazil

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Authors: Shahrokh Barati, Reza Ramezani

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Due to the countries growing attention to the renewable energy producing, the demand for energy from renewable energy has gone up among the renewable energy sources; wind energy is the fastest growth in recent years. In this regard, in order to increase the availability of wind turbines, using of Fault Detection and Isolation (FDI) system is necessary. Wind turbines include of various faults such as sensors fault, actuator faults, network connection fault, mechanical faults and faults in the generator subsystem. Although, sensors and actuators have a large number of faults in wind turbine but have discussed fewer in the literature. Therefore, in this work, we focus our attention to design a sensor and actuator fault detection and isolation algorithm and Fault-tolerant control systems (FTCS) for Wind Turbine. The aim of this research is to propose a comprehensive fault detection and isolation system for sensors and actuators of wind turbine based on data-driven approaches. To achieve this goal, the features of measurable signals in real wind turbine extract in any condition. The next step is the feature selection among the extract in any condition. The next step is the feature selection among the extracted features. Features are selected that led to maximum separation networks that implemented in parallel and results of classifiers fused together. In order to maximize the reliability of decision on fault, the property of fault repeatability is used.

Keywords: FDI, wind turbines, sensors and actuators faults, renewable energy

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Authors: F. Infante, W. Kaal, S. Perfetto, S. Herold

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In the last decade the demand of wireless sensors and low-power electric devices for condition monitoring in mechanical structures has been strongly increased. Networks of wireless sensors can potentially be applied in a huge variety of applications. Due to the reduction of both size and power consumption of the electric components and the increasing complexity of mechanical systems, the interest of creating dense nodes sensor networks has become very salient. Nevertheless, with the development of large sensor networks with numerous nodes, the critical problem of powering them is drawing more and more attention. Batteries are not a valid alternative for consideration regarding lifetime, size and effort in replacing them. Between possible alternative solutions for durable power sources useable in mechanical components, vibrations represent a suitable source for the amount of power required to feed a wireless sensor network. For this purpose, energy harvesting from structural vibrations has received much attention in the past few years. Suitable vibrations can be found in numerous mechanical environments including automotive moving structures, household applications, but also civil engineering structures like buildings and bridges. Similarly, a dynamic vibration absorber (DVA) is one of the most used devices to mitigate unwanted vibration of structures. This device is used to transfer the primary structural vibration to the auxiliary system. Thus, the related energy is effectively localized in the secondary less sensitive structure. Then, the additional benefit of harvesting part of the energy can be obtained by implementing dedicated components. This paper describes the design process of an energy harvesting tuned vibration absorber (EHTVA) for rotating systems using piezoelectric elements. The energy of the vibration is converted into electricity rather than dissipated. The device proposed is indeed designed to mitigate torsional vibrations as with a conventional rotational TVA, while harvesting energy as a power source for immediate use or storage. The resultant rotational multi degree of freedom (MDOF) system is initially reduced in an equivalent single degree of freedom (SDOF) system. The Den Hartog’s theory is used for evaluating the optimal mechanical parameters of the initial DVA for the SDOF systems defined. The performance of the TVA is operationally assessed and the vibration reduction at the original resonance frequency is measured. Then, the design is modified for the integration of active piezoelectric patches without detuning the TVA. In order to estimate the real power generated, a complex storage circuit is implemented. A DC-DC step-down converter is connected to the device through a rectifier to return a fixed output voltage. Introducing a big capacitor, the energy stored is measured at different frequencies. Finally, the electromechanical prototype is tested and validated achieving simultaneously reduction and harvesting functions.

Keywords: energy harvesting, piezoelectricity, torsional vibration, vibration absorber

Procedia PDF Downloads 147

Authors: Khaled Own Mohaisen, Md. Hasan Zahir, Salah U. Al-Dulaijan, Shamsad Ahmad, Mohammed Maslehuddin

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Shape-stabilized phase change materials (ss-PCMs) for energy storage systems were developed using perlite, scoria, and oil ash as a carrier, with polyethylene glycol (PEG) with a molecular weight of 6000 as phase change material (PCM). Physical mixing using simple impregnation of ethanol evaporation technique method was carried out to fabricate the form stabilized PCM. The fabricated PCMs prevent leakage, reduce the supercooling effect and minimize recalescence problems of the PCM. The differential scanning calorimetry (DSC) results show that perlite composite (ExPP) has the highest latent heat of melting and freezing values of (141.6 J/g and 143.7 J/g) respectively, compared with oil ash (OAP) and scoria (SCP) composites. Moreover, ExPP has the highest impregnation ratio, energy storage efficiency, and energy storage capacity compared with OAP and SCP. However, OAP and SCP have higher thermal conductivity values compared to ExPP composites which accelerate the thermal storage response in the composite. These results were confirmed with DSC, and the characteristic of the PCMs was investigated by using XRD and FE-SEM techniques.

Keywords: expanded perlite, oil ash, scoria, energy storage material

Procedia PDF Downloads 90

Authors: Wala Abou Saoud, Aymen Amine Assadi, Monia Guiza, Abdelkrim Bouzaza, Wael Aboussaoud, Abdelmottaleb Ouederni, Dominique Wolbert

Abstract:

Volatile organic compounds (VOCs) constitute one of the most important families of chemicals involved in atmospheric pollution, causing damage to the environment and human health, and need, consequently, to be eliminated. Among the promising technologies, dielectric barrier discharge (DBD) plasma - photocatalysis coupling reveals very interesting prospects in terms of process synergy of compounds mineralization’s, with low energy consumption. In this study, the removal of organic compounds such butyraldehyde (BUTY) and dimethyl disulfide (DMDS) (exhaust gasses from animal quartering centers.) in air mixture using DBD plasma coupled with photocatalysis was tested, in order to determine whether or not synergy effect was present. The removal efficiency of these pollutants, a selectivity of CO₂ and CO, and byproducts formation such as ozone formation were investigated in order to evaluate the performance of the combined process. For this purpose, a series of experiments were carried out in a continuous reactor. Many operating parameters were also investigated such as the specific energy of discharge, the inlet concentration of pollutant and the flowrate. It appears from this study that, the performance of the process has enhanced and a synergetic effect is observed. In fact, we note an enhancement of 10 % on removal efficiency. It is interesting to note that the combined system leads to better CO₂ selectivity than for plasma. Consequently, intermediates by-products have been reduced due to various other species (O•, N, OH•, O₂•-, O₃, NO₂, NOx, etc.). Additionally, the behavior of combining DBD plasma and photocatalysis has shown that the ozone can be easily also decomposed in presence of photocatalyst.

Keywords: combined process, DBD plasma, photocatalysis, pilot scale, synergetic effect, VOCs

Procedia PDF Downloads 330

Authors: Chalermporn Jindapeng

Abstract:

The main objective of the study of the suitable operating conditions of hot water generators combined with central air package units: a case study of Tipco Building Group was to analyze the suitable operating conditions and energy-related costs in each operating condition of hot water generators combined with central air package units which resulted in water-cooled packages. Thermal energy from vapor form refrigerants at high pressures and temperatures was exchanged with thermal energy of the water in the swimming pool that required suitable temperature control for users with the use of plate heat exchangers before refrigerants could enter the condenser in its function to change the status of vapor form refrigerants at high pressures and temperatures to liquid form at high pressures and temperatures. Thus, if this was used to replace heat pumps it could reduce the electrical energy that was used to make hot water and reduce the cost of the electrical energy of air package units including the increased efficacy of air package units. Of the analyses of the suitable operating conditions by means of the study of the elements involved with actual measurements from the system that had been installed at the Tipco Building Group hot water generators were combined with air package units which resulted in water-cooled packages with a cooling capacity of 75 tonnes. Plate heat exchangers were used in the transfer of thermal energy from refrigerants to one set of water with a heat exchanger area of 1.5 m² which was used to increase the temperature of swimming pool water that has a capacity of 240 m³. From experimental results, it was discovered after continuous temperature measurements in the swimming pool every 15 minutes that swimming pool water temperature increased by 0.78 ⁰C 0.75 ⁰C 0.74 ⁰C and 0.71 ⁰C. The rates of flow of hot water through the heat exchangers were equal to 14, 16, 18 and 20 litres per minute respectively where the swimming pool water temperature was at a constant value and when the rate of flow of hot water increased this caused hot water temperatures to decrease and the coefficient of performance of the air package units to increase from 5.9 to 6.3, 6.7, 6.9 and 7.6 while the rates of flow of hot water were equal to 14, 16, 18 and 20 litres per minute, respectively. As for the cooling systems, there were no changes and the system cooling functions were normal as the cooling systems were able to continuously transfer incoming heat for the swimming pool water which resulted in a constant pressure in the cooling system that allowed its cooling functions to work normally.

Keywords: central air package units, heat exchange, hot water generators, swimming pool

Procedia PDF Downloads 258

Authors: Mingbao Chen

Abstract:

After Rio+20, the blue economy rises all over the world, and it has become the focus field of national development. At present, the blue economy has become a new growth point in the field of global economy and the direction of the development of ‘green’ in the ocean. However, in fact, the key factors affecting the development of the blue economy have not been explored in depth, and the development policies and performance of the blue economy have not been scientifically evaluated. This cannot provide useful guidance for the development of the blue economy. Therefore, it is urgent to establish a quantitative evaluation framework to measure the performance of the blue economic development. Based on the full understanding of the connotation and elements of the blue economy, and studying the literature, this article has built an universality and operability evaluation index system, including ecological environment, social justice, sustainable growth, policy measures, and so on. And this article also established a sound evaluation framework of blue economic development performance. At the same time, this article takes China as a sample to test the framework of the adaptability, and to assess the performance of China's blue economic.

Keywords: Blue economy, development performance, evaluation framework, assess method

Procedia PDF Downloads 247

Authors: S. Kumchoo

Abstract:

The result of suggestion for low energy diet (1,000-1,200 kcal) in obese women to the effect on body weight, waist circumference and body mass index (BMI) in this experiment. Quisi experimental research was used for this study and it is a One-group pretest-posttest designs measurement method. The aim of this study was body weight, waist circumference and body mass index (BMI) reduction by using low energy diet (1,000-1,200 kcal) in obese women, the result found that in 15 of obese women that contained their body mass index (BMI) ≥ 30, after they obtained low energy diet (1,000-1,200 kcal) within 2 weeks. The data were collected before and after of testing the results showed that the average of body weight decrease 3.4 kilogram, waist circumference value decrease 6.1 centimeter and the body mass index (BMI) decrease 1.3 kg.m2 from their previous body weight, waist circumference and body mass index (BMI) before experiment started. After this study, the volunteers got healthy and they can choose or select some food for themselves. For this study, the research can be improved for data development for forward study in the future.

Keywords: body weight, waist circumference, BMI, low energy diet

Procedia PDF Downloads 456