Search results for: input output linearization

Authors: Cem Çindaş, Serkan Şimşek

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In this paper, the study and design of a 3-dB 90° directional coupler operating in the S-band is proposed. The coupler employs symmetrical multi-section coupled lines designed in a stripline technique. Design is realized in AWR Design Environment and CST Microwave Studio. Using these two programs played a key role in attaining outcomes swiftly and precisely. The simulation results show that the coupler maintains amplitude consistency within ± 0.3 dB, isolation and reflection losses better than 16 dB, and phase difference between two output ports of 88º±0.6˚ in the 1.7 – 4.35 GHz range. This simulation results indicate an improvement is achieved in fractional bandwidth (FBW) performance around the center frequency of f0 = 3 GHz.

Keywords: coupled stripline, directional coupler, multi-section coupler, symmetrical coupler

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Authors: Bao Li, Aike Qiao, Gaoyang Li, Youjun Liu

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Background: Lumped parameter model (LPM) is a common numerical model for hemodynamic calculation. LPM uses circuit elements to simulate the human blood circulatory system. Physiological indicators and characteristics can be acquired through the model. However, due to the different physiological indicators of each individual, parameters in LPM should be personalized in order for convincing calculated results, which can reflect the individual physiological information. This study aimed to develop an automatic and effective optimization method to personalize the parameters in LPM of the blood circulatory system, which is of great significance to the numerical simulation of individual hemodynamics. Methods: A closed-loop LPM of the human blood circulatory system that is applicable for most persons were established based on the anatomical structures and physiological parameters. The patient-specific physiological data of 5 volunteers were non-invasively collected as personalized objectives of individual LPM. In this study, the blood pressure and flow rate of heart, brain, and limbs were the main concerns. The collected systolic blood pressure, diastolic blood pressure, cardiac output, and heart rate were set as objective data, and the waveforms of carotid artery flow and ankle pressure were set as objective waveforms. Aiming at the collected data and waveforms, sensitivity analysis of each parameter in LPM was conducted to determine the sensitive parameters that have an obvious influence on the objectives. Simulated annealing was adopted to iteratively optimize the sensitive parameters, and the objective function during optimization was the root mean square error between the collected waveforms and data and simulated waveforms and data. Each parameter in LPM was optimized 500 times. Results: In this study, the sensitive parameters in LPM were optimized according to the collected data of 5 individuals. Results show a slight error between collected and simulated data. The average relative root mean square error of all optimization objectives of 5 samples were 2.21%, 3.59%, 4.75%, 4.24%, and 3.56%, respectively. Conclusions: Slight error demonstrated good effects of optimization. The individual modeling algorithm developed in this study can effectively achieve the individualization of LPM for the blood circulatory system. LPM with individual parameters can output the individual physiological indicators after optimization, which are applicable for the numerical simulation of patient-specific hemodynamics.

Keywords: blood circulatory system, individual physiological indicators, lumped parameter model, optimization algorithm

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Authors: Adriana Haulica

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Powered by Machine Learning, Precise medicine is tailored by now to use genetic and molecular profiling, with the aim of optimizing the therapeutic benefits for cohorts of patients. As the majority of Machine Language algorithms come from heuristics, the outputs have contextual validity. This is not very restrictive in the sense that medicine itself is not an exact science. Meanwhile, the progress made in Molecular Biology, Bioinformatics, Computational Biology, and Precise Medicine, correlated with the huge amount of human biology data and the increase in computational power, opens new healthcare challenges. A more accurate diagnosis is needed along with real-time treatments by processing as much as possible from the available information. The purpose of this paper is to present a deeper vision for the future of Artificial Intelligence in Precise medicine. In fact, actual Machine Learning algorithms use standard mathematical knowledge, mostly Euclidian metrics and standard computation rules. The loss of information arising from the classical methods prevents obtaining 100% evidence on the diagnosis process. To overcome these problems, we introduce MEDICOMPILLS, a new architectural concept tool of information processing in Precise medicine that delivers diagnosis and therapy advice. This tool processes poly-field digital resources: global knowledge related to biomedicine in a direct or indirect manner but also technical databases, Natural Language Processing algorithms, and strong class optimization functions. As the name suggests, the heart of this tool is a compiler. The approach is completely new, tailored for omics and clinical data. Firstly, the intrinsic biological intuition is different from the well-known “a needle in a haystack” approach usually used when Machine Learning algorithms have to process differential genomic or molecular data to find biomarkers. Also, even if the input is seized from various types of data, the working engine inside the MEDICOMPILLS does not search for patterns as an integrative tool. This approach deciphers the biological meaning of input data up to the metabolic and physiologic mechanisms, based on a compiler with grammars issued from bio-algebra-inspired mathematics. It translates input data into bio-semantic units with the help of contextual information iteratively until Bio-Logical operations can be performed on the base of the “common denominator “rule. The rigorousness of MEDICOMPILLS comes from the structure of the contextual information on functions, built to be analogous to mathematical “proofs”. The major impact of this architecture is expressed by the high accuracy of the diagnosis. Detected as a multiple conditions diagnostic, constituted by some main diseases along with unhealthy biological states, this format is highly suitable for therapy proposal and disease prevention. The use of MEDICOMPILLS architecture is highly beneficial for the healthcare industry. The expectation is to generate a strategic trend in Precise medicine, making medicine more like an exact science and reducing the considerable risk of errors in diagnostics and therapies. The tool can be used by pharmaceutical laboratories for the discovery of new cures. It will also contribute to better design of clinical trials and speed them up.

Keywords: bio-semantic units, multiple conditions diagnosis, NLP, omics

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Authors: S. Zamir

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The modern era has brought with it significant organizational changes. These changes have not bypassed the academic world, and along with the old academic bonds that include a world of knowledge and ethics, academic faculty members are required more than ever not only to survive in the academic world, but also to thrive and flourish and position themselves as modern and opinionated academicians. Based upon the writings of organizational consultants, the article suggests a 10 X C model for cultivating an academic backbone, as well as emphasizing its input to the professional growth of university and college academics: Competence, Calculations of pain & gain, Character, Commitment, Communication, Curiosity, Coping, Courage, Collaboration and Celebration.

Keywords: academic career, academicians, higher education, the 10xC model

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Authors: Tesfaye Alamirew Dessie

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Our study focuses on developing a Model Predictive Controller (MPC) and evaluating it against a traditional PID for a pasteurization process. Utilizing system identification from the experimental data, the dynamics of the pasteurization process were calculated. Using best fit with data validation, residual, and stability analysis, the quality of several model architectures was evaluated. The validation data fit the auto-regressive with exogenous input (ARX322) model of the pasteurization process by roughly 80.37 percent. The ARX322 model structure was used to create MPC and PID control techniques. After comparing controller performance based on settling time, overshoot percentage, and stability analysis, it was found that MPC controllers outperform PID for those parameters.

Keywords: MPC, PID, ARX, pasteurization

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Authors: Yasaman Esfandiari

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Mechanical engineering has always dealt with amplification of the input power in power trains. One of the ways to achieve this goal is to use gears to change the amplitude and direction of the torque and the speed. However, the gears should be optimally designed to best achieve these objectives. In this study, helical gear systems are optimized to achieve maximum power. Material selection, space restriction, available facilities for manufacturing, the probability of tooth breakage, and tooth wear are taken into account and governing equations are derived. Finally, a Matlab code was generated to solve the optimization problem and the results are verified.

Keywords: design, gears, Matlab, optimization

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Authors: Omer Burak Iskender, Keck Voon Ling, Vincent Dubanchet, Luca Simonini

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This paper presents Guidance and Control (G&C) strategy to approach and synchronize with potentially rotating targets. The proposed strategy generates and tracks a safe trajectory for space servicing missions, including tasks like approaching, inspecting, and capturing. The main objective of this paper is to validate the G&C laws using a Hardware-In-the-Loop (HIL) setup with realistic rendezvous and docking equipment. Throughout this work, the assumption of full relative state feedback is relaxed by onboard sensors that bring realistic errors and delays and, while the proposed closed loop approach demonstrates the robustness to the above mentioned challenge. Moreover, G&C blocks are unified via the Model Predictive Control (MPC) paradigm, and the coupling between translational motion and rotational motion is addressed via dual quaternion based kinematic description. In this work, G&C is formulated as a convex optimization problem where constraints such as thruster limits and the output constraints are explicitly handled. Furthermore, the Monte-Carlo method is used to evaluate the robustness of the proposed method to the initial condition errors, the uncertainty of the target's motion and attitude, and actuator errors. A capture scenario is tested with the robotic test bench that has onboard sensors which estimate the position and orientation of a drifting satellite through camera imagery. Finally, the approach is compared with currently used robust H-infinity controllers and guidance profile provided by the industrial partner. The HIL experiments demonstrate that the proposed strategy is a potential candidate for future space servicing missions because 1) the algorithm is real-time implementable as convex programming offers deterministic convergence properties and guarantee finite time solution, 2) critical physical and output constraints are respected, 3) robustness to sensor errors and uncertainties in the system is proven, 4) couples translational motion with rotational motion.

Keywords: dual quaternion, model predictive control, real-time experimental test, rendezvous and docking, spacecraft autonomy, space servicing

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Authors: Milada Krejci, Martin Hill, Vaclav Hosek, Dobroslava Jandova, Jiri Kajzar, Pavel Blaha

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The paper declares effects of exercise intervention of the research project “Basic research of balance changes in seniors”, granted by the Czech Science Foundation. The objective of the presented study is to define predictors, which influence bio-psycho-social consequences and effects of balance ability in senior 65 years old and above. We focused on the Fall-Efficacy Scale changes evaluation in seniors. Comprehensive hypothesis of the project declares, that motion uncertainty (dyskinesia) can negatively affect the well-being of a senior in bio-psycho-social context. In total, random selection and testing of 100 seniors (30 males, 70 females) from Prague and Central Bohemian region was provided. The sample was divided by stratified random selection into experimental and control groups, who underwent input and output testing. For diagnostics the methods of Medical Anamnesis, Functional anthropological examinations, Tinetti Balance Assessment Tool, SF-36 Health Survey, Anamnestic comparative self-assessment scale were used. Intervention method called "Life in Balance" based on yoga techniques was applied in four-week cycle. Results of multivariate regression were verified by repeated measures ANOVA: subject factor, phase of intervention (between-subject factor), body fluid (within-subject factor) and phase of intervention × body fluid interaction). ANOVA was performed with a repetition involving the factors of subjects, experimental/control group, phase of intervention (independent variable), and x phase interaction followed by Bonferroni multiple comparison assays with a test strength of at least 0.8 on the probability level p < 0.05. In the paper results of the first-year investigation of the three years running project are analysed. Results of balance tests confirmed no significant difference between females and males in pre-test. Significant improvements in balance and walking ability were observed in experimental group in females comparing to males (F = 128.4, p < 0.001). In the females control group, there was no significant change in post- test, while in the female experimental group positive changes in posture and spine flexibility in post-tests were found. It seems that females even in senior age react better to incentives of intervention in balance and spine flexibility. On the base of results analyses, we can declare the significant improvement in social balance markers after intervention in the experimental group (F = 10.5, p < 0.001). In average, seniors are used to take four drugs daily. Number of drugs can contribute to allergy symptoms and balance problems. It can be concluded that static balance and walking ability of seniors according Tinetti Balance scale correlate significantly with psychic and social monitored markers.

Keywords: exercises, balance, seniors 65+, health, mental and social balance

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Authors: Boris Melnikov, Dmitrii Chaikovskii, Elena Melnikova

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The traveling salesman problem (TSP) is a well-known optimization problem that seeks to find the shortest possible route that visits a set of points and returns to the starting point. In this paper, we apply some heuristics of the TSP for the task of restoring the DNA matrix. This restoration problem is often considered in biocybernetics. For it, we must recover the matrix of distances between DNA sequences if not all the elements of the matrix under consideration are known at the input. We consider the possibility of using this method in the testing of distance calculation algorithms between a pair of DNAs to restore the partially filled matrix.

Keywords: optimization problems, DNA matrix, partially filled matrix, traveling salesman problem, heuristic algorithms

Procedia PDF Downloads 135

Authors: S. Mawlood, L. Denanny, N. Watson, B. Pickard

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DNA analysis has been widely accepted as providing valuable evidence concerning the identity of the source of biological traces. Our work has showed that DNA samples can survive on cartridges even after firing. The study also raised the possibility of determining other information such as the age of the donor. Such information may be invaluable in certain cases where spent cartridges from automatic weapons are left behind at the scene of a crime. In spite of the nature of touch evidence and exposure to high chamber temperatures during shooting, we were still capable to retrieve enough DNA for profile typing. In order to estimate age of contributor, DNA methylation levels were analyzed using EpiTect system for retrieved DNA. However, results were not conclusive, due to low amount of input DNA.

Keywords: DNA profile, DNA Methylation, fired cartridge, touch sample

Procedia PDF Downloads 438

Authors: Subramanyam Devarakonda Hanumantharao, Udayendu Prakash Sharma, Mahesh Garg

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Introduction: Gomabai Netralaya a reputed eye hospital is located in Neemuch a small city of Madhya Pradesh, India. The hospital is established in 1992 by Late. G.D Agrawal a renowned educationist, freedom fighter and philanthropist. The eye hospital was established to serve all sections of the society in affordable manner. To provide comprehensive eye care services to the rural poor the hospital started organizing outreach camps since 1994. Purpose: To study the cost effectiveness of outreach eye camps for addressing the sustainability issues of the outreach program. Methods: One year statistics of outreach eye camps were collected from Hospital Management Information System software to analyze the productivity of camps. Income and expenses report was collected from outreach department records to analyze per camp expenses and per patient expenses against the income generated. All current year records were analyzed to have accuracy of information and results. Information was collected in two ways: 1)Actual camp performance records and expenses from book of accounts. 2)Cross verification was done through one to one discussion with outreach staff. Results: Total 17534 outpatients were examined through 52 outreach eye camps. Total 6042 (34% of total outpatients) patients were advised with cataracts and 4651 (77% of advice) operations were performed. The average OPD per camp was 337 and per camp 116 patients was advised for cataract surgery and 89 surgeries were performed per camp. Total 18200 US$ incurred on organizing 52 outreach camps in the radius of 100 k.ms. Considering the total outpatients screened through camps the screening cost per patient was 1.00 US$ and considering the surgical output the per surgery expenses was 4.00 US$. The cost recovery of the total expenses was through Government grant of US$ 16.00 per surgery (that includes surgical grant). All logistics cost of camps and patients transportation cost was taken care by local donors. Conclusion: The present study demonstrates that with people’s participation, successful high volume outreach eye camps can be organized. The cost effectiveness of the outreach camps is totally depended on volume of outpatient’s turn-up at camp site and per camp surgical output. The only solution to sustainability of outreach eye camps is sharing of cost with local donors and increasing productivity.

Keywords: camps, outreach, productivity, sustainable

Procedia PDF Downloads 158

Authors: Jonathan Sohn

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Deep neural networks (DNNs) have shown state-of-the-art performance for many applications, including computer vision, natural language processing, and speech recognition. Recently, adversarial attacks have been studied in the context of deep neural networks, which aim to alter the results of deep neural networks by modifying the inputs slightly. For example, an adversarial attack on a DNN used for object detection can cause the DNN to miss certain objects. As a result, the reliability of DNNs is undermined by their lack of robustness against adversarial attacks, raising concerns about their use in safety-critical applications such as autonomous driving. In this paper, we focus on studying the adversarial attacks and defenses on DNNs for image classification. There are two types of adversarial attacks studied which are fast gradient sign method (FGSM) attack and projected gradient descent (PGD) attack. A DNN forms decision boundaries that separate the input images into different categories. The adversarial attack slightly alters the image to move over the decision boundary, causing the DNN to misclassify the image. FGSM attack obtains the gradient with respect to the image and updates the image once based on the gradients to cross the decision boundary. PGD attack, instead of taking one big step, repeatedly modifies the input image with multiple small steps. There is also another type of attack called the target attack. This adversarial attack is designed to make the machine classify an image to a class chosen by the attacker. We can defend against adversarial attacks by incorporating adversarial examples in training. Specifically, instead of training the neural network with clean examples, we can explicitly let the neural network learn from the adversarial examples. In our experiments, the digit recognition accuracy on the MNIST dataset drops from 97.81% to 39.50% and 34.01% when the DNN is attacked by FGSM and PGD attacks, respectively. If we utilize FGSM training as a defense method, the classification accuracy greatly improves from 39.50% to 92.31% for FGSM attacks and from 34.01% to 75.63% for PGD attacks. To further improve the classification accuracy under adversarial attacks, we can also use a stronger PGD training method. PGD training improves the accuracy by 2.7% under FGSM attacks and 18.4% under PGD attacks over FGSM training. It is worth mentioning that both FGSM and PGD training do not affect the accuracy of clean images. In summary, we find that PGD attacks can greatly degrade the performance of DNNs, and PGD training is a very effective way to defend against such attacks. PGD attacks and defence are overall significantly more effective than FGSM methods.

Keywords: deep neural network, adversarial attack, adversarial defense, adversarial machine learning

Procedia PDF Downloads 177

Authors: Salomão Manuel Francisco, Manuel António Salgueiro Da Silva, Bento Filipe Barreiras Pinto Cavadas, Teresa Monteiro Seixas

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In bachelor's degrees in Physics Education framework in Angola, and to a certain extent, within the community of Portuguese language countries (CPLP), teaching methodologies rely heavily on theoretical memorization and mathematical demonstrations. This approach often discourages students, particularly the female population, as the reliance on theoretical mathematical demonstrations generates the perception of Physics as an arduous, challenging discipline. To address this challenge and recognize the value of practical application as an evaluative criterion of material truth, we propose a practical activity in Environmental Physics that will be shared with Angolan higher education teachers, who will receive full scaffolding and support from the authors. These teachers, adopting and developing similar activities in a classroom setting, will contribute to the environmental education framework as well. Additionally, this work aligns with different goals of UNESCO's 2030 agenda, namely, specifically, goals 4, 5, 7, 11, 13, and 17. The experimental activity developed in this work is centered around the demonstration of the photovoltaic effect and its application for renewable energy production. The first objective of the activity is to study the variation of electrical power supplied by a photovoltaic system (PV) to an electrical circuit as the angle of light incidence changes. Students can observe that the power supplied to the circuit is greater when light rays fall perpendicularly on the PV. However, as the angle of incidence increases, resulting in a larger area covered by the light rays, the power supplied to the circuit decreases due to lower irradiance. The second objective is to demonstrate that the power output can be maximized by adjusting the circuit load resistance at each irradiance value. In these two parts of the activity, students can analyze experimental data taking into account the irradiance law and the equivalent circuit description of a PV cell. Through detailed data analysis, students are also expected to assess the effects of temperature on PV efficiency degradation and the efficiency enhancement provided by light concentration mechanisms. As a third objective, students can explore how the color of incident light affects the PV output power, considering the quantum nature of light and its interaction with the PV system.

Keywords: experiments, irradiation law, physic teaching, photovoltaic effect

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Authors: Iman Farasat, Howard M. Salis

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Engineered genetic circuits reprogram cellular behavior to act as living computers with applications in detecting cancer, creating self-controlling artificial tissues, and dynamically regulating metabolic pathways. Phenemenological models are often used to simulate and design genetic circuit behavior towards a desired behavior. While such models assume that each circuit component’s function is modular and independent, even small changes in a circuit (e.g. a new promoter, a change in transcription factor expression level, or even a new media) can have significant effects on the circuit’s function. Here, we use statistical thermodynamics to account for the several factors that control transcriptional regulation in bacteria, and experimentally demonstrate the model’s accuracy across 825 measurements in several genetic contexts and hosts. We then employ our first principles model to design, experimentally construct, and characterize a family of signal amplifying genetic circuits (genetic OpAmps) that expand the dynamic range of cell sensors. To develop these models, we needed a new approach to measuring the in vivo binding free energies of transcription factors (TFs), a key ingredient of statistical thermodynamic models of gene regulation. We developed a new high-throughput assay to measure RNA polymerase and TF binding free energies, requiring the construction and characterization of only a few constructs and data analysis (Figure 1A). We experimentally verified the assay on 6 TetR-homolog repressors and a CRISPR/dCas9 guide RNA. We found that our binding free energy measurements quantitatively explains why changing TF expression levels alters circuit function. Altogether, by combining these measurements with our biophysical model of translation (the RBS Calculator) as well as other measurements (Figure 1B), our model can account for changes in TF binding sites, TF expression levels, circuit copy number, host genome size, and host growth rate (Figure 1C). Model predictions correctly accounted for how these 8 factors control a promoter’s transcription rate (Figure 1D). Using the model, we developed a design framework for engineering multi-promoter genetic circuits that greatly reduces the number of degrees of freedom (8 factors per promoter) to a single dimensionless unit. We propose the Ptashne (Pt) number to encapsulate the 8 co-dependent factors that control transcriptional regulation into a single number. Therefore, a single number controls a promoter’s output rather than these 8 co-dependent factors, and designing a genetic circuit with N promoters requires specification of only N Pt numbers. We demonstrate how to design genetic circuits in Pt number space by constructing and characterizing 15 2-repressor OpAmp circuits that act as signal amplifiers when within an optimal Pt region. We experimentally show that OpAmp circuits using different TFs and TF expression levels will only amplify the dynamic range of input signals when their corresponding Pt numbers are within the optimal region. Thus, the use of the Pt number greatly simplifies the genetic circuit design, particularly important as circuits employ more TFs to perform increasingly complex functions.

Keywords: transcription factor, synthetic biology, genetic circuit, biophysical model, binding energy measurement

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Authors: Jožef Ritonja, Bojan Grčar, Boštjan Polajžer

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In recent years, electricity trade between neighboring countries has become increasingly intense. Increasing power transmission over long distances has resulted in an increase in the oscillations of the transmitted power. The damping of the oscillations can be carried out with the reconfiguration of the network or the replacement of generators, but such solution is not economically reasonable. The only cost-effective solution to improve the damping of power oscillations is to use power system stabilizers. Power system stabilizer represents a part of synchronous generator control system. It utilizes semiconductor’s excitation system connected to the rotor field excitation winding to increase the damping of the power system. The majority of the synchronous generators are equipped with the conventional power system stabilizers with fixed parameters. The control structure of the conventional power system stabilizers and the tuning procedure are based on the linear control theory. Conventional power system stabilizers are simple to realize, but they show non-sufficient damping improvement in the entire operating conditions. This is the reason that advanced control theories are used for development of better power system stabilizers. In this paper, the adaptive control theory for power system stabilizers design and synthesis is studied. The presented work is focused on the use of model reference adaptive control approach. Control signal, which assures that the controlled plant output will follow the reference model output, is generated by the adaptive algorithm. Adaptive gains are obtained as a combination of the "proportional" term and with the σ-term extended "integral" term. The σ-term is introduced to avoid divergence of the integral gains. The necessary condition for asymptotic tracking is derived by means of hyperstability theory. The benefits of the proposed model reference adaptive power system stabilizer were evaluated as objectively as possible by means of a theoretical analysis, numerical simulations and laboratory realizations. Damping of the synchronous generator oscillations in the entire operating range was investigated. Obtained results show the improved damping in the entire operating area and the increase of the power system stability. The results of the presented work will help by the development of the model reference power system stabilizer which should be able to replace the conventional stabilizers in power systems.

Keywords: power system, stability, oscillations, power system stabilizer, model reference adaptive control

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Authors: Marcin Zieliński, Marcin Dębowski, Mirosław Krzemieniewski

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The anaerobic degradation of substrates is limited especially by the rate and effectiveness of the first (hydrolytic) stage of fermentation. This stage may be intensified through pre-treatment of substrate aimed at disintegration of the solid phase and destruction of substrate tissues and cells. The most frequently applied criterion of disintegration outcomes evaluation is the increase in biogas recovery owing to the possibility of its use for energetic purposes and, simultaneously, recovery of input energy consumed for the pre-treatment of substrate before fermentation. Hydrodynamic cavitation is one of the methods for organic substrate disintegration that has a high implementation potential. Cavitation is explained as the phenomenon of the formation of discontinuity cavities filled with vapor or gas in a liquid induced by pressure drop to the critical value. It is induced by a varying field of pressures. A void needs to occur in the flow in which the pressure first drops to the value close to the pressure of saturated vapor and then increases. The process of cavitation conducted under controlled conditions was found to significantly improve the effectiveness of anaerobic conversion of organic substrates having various characteristics. This phenomenon allows effective damage and disintegration of cellular and tissue structures. Disintegration of structures and release of organic compounds to the dissolved phase has a direct effect on the intensification of biogas production in the process of anaerobic fermentation, on reduced dry matter content in the post-fermentation sludge as well as a high degree of its hygienization and its increased susceptibility to dehydration. A device the efficiency of which was confirmed both in laboratory conditions and in systems operating in the technical scale is a hydrodynamic generator of cavitation. Cavitators, agitators and emulsifiers constructed and tested worldwide so far have been characterized by low efficiency and high energy demand. Many of them proved effective under laboratory conditions but failed under industrial ones. The only task successfully realized by these appliances and utilized on a wider scale is the heating of liquids. For this reason, their usability was limited to the function of heating installations. Design of the presented cavitation generator allows achieving satisfactory energy efficiency and enables its use under industrial conditions in depolymerization processes of biomass with various characteristics. Investigations conducted on the laboratory and industrial scale confirmed the effectiveness of applying cavitation in the process of biomass destruction. The use of the cavitation generator in laboratory studies for disintegration of sewage sludge allowed increasing biogas production by ca. 30% and shortening the treatment process by ca. 20 - 25%. The shortening of the technological process and increase of wastewater treatment plant effectiveness may delay investments aimed at increasing system output. The use of a mechanical cavitator and application of repeated cavitation process (4-6 times) enables significant acceleration of the biogassing process. In addition, mechanical cavitation accelerates increases in COD and VFA levels.

Keywords: hydrodynamic cavitation, pretreatment, biomass, methane fermentation, Virginia fanpetals

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Authors: Beste Ozcan, Valerio Sperati, Laura Romano, Tania Moretta, Simone Scaffaro, Noemi Faedda, Federica Giovannone, Carla Sogos, Vincenzo Guidetti, Gianluca Baldassarre

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+me is an experimental interactive toy with the appearance of a soft, pillow-like, panda. Shape and consistency are designed to arise emotional attachment in young children: a child can wear it around his/her neck and treat it as a companion (i.e. a transitional object). When caressed on paws or head, the panda emits appealing, interesting outputs like colored lights or amusing sounds, thanks to embedded electronics. Such sensory patterns can be modified through a wirelessly connected tablet: by this, an adult caregiver can adapt +me responses to a child's reactions or requests, for example, changing the light hue or the type of sound. The toy control is therefore shared, as it depends on both the child (who handles the panda) and the adult (who manages the tablet and mediates the sensory input-output contingencies). These features make +me a potential tool for therapy with children with Neurodevelopmental Disorders (ND), characterized by impairments in the social area, like Autism Spectrum Disorders (ASD) and Language Disorders (LD): as a proposal, the toy could be used together with a therapist, in rehabilitative play activities aimed at encouraging simple social interactions and reinforcing basic relational and communication skills. +me was tested in two pilot experiments, the first one involving 15 Typically Developed (TD) children aged in 8-34 months, the second one involving 7 children with ASD, and 7 with LD, aged in 30-48 months. In both studies a researcher/caregiver, during a one-to-one, ten-minute activity plays with the panda and encourages the child to do the same. The purpose of both studies was to ascertain the general acceptability of the device as an interesting toy that is an object able to capture the child's attention and to maintain a high motivation to interact with it and with the adult. Behavioral indexes for estimating the interplay between the child, +me and caregiver were rated from the video recording of the experimental sessions. Preliminary results show how -on average- participants from 3 groups exhibit a good engagement: they touch, caress, explore the panda and show enjoyment when they manage to trigger luminous and sound responses. During the experiments, children tend to imitate the caregiver's actions on +me, often looking (and smiling) at him/her. Interesting behavioral differences between TD, ASD, and LD groups are scored: for example, ASD participants produce a fewer number of smiles both to panda and to a caregiver with respect to TD group, while LD scores stand between ASD and TD subjects. These preliminary observations suggest that the interactive toy +me is able to raise and maintain the interest of toddlers and therefore it can be reasonably used as a supporting tool during therapy, to stimulate pivotal social skills as imitation, turn-taking, eye contact, and social smiles. Interestingly, the young age of participants, along with the behavioral differences between groups, seem to suggest a further potential use of the device: a tool for early differential diagnosis (the average age of a child

Keywords: autism spectrum disorders, interactive toy, social interaction, therapy, transitional wearable companion

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Authors: Rahul Bishnoi

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Theatre, as Ann Ubersfld calls it, is a paradox. At once, it is both a literary work and a physical representation. Theatre as a text is eternal, reproducible, and identical while as a performance, theatre is momentary and never identical to the previous performances. In this dual existence of theatre, who is the author? Is the author the playwright who writes the dramatic text, or the director who orchestrates the performance, or the actor who embodies the text? From the poststructuralist lens of Barthes, the author is dead. Barthes’ argument of discrete temporality, i.e. the author is the before, and the text is the after, does not hold true for theatre. A published literary work is written, edited, printed, distributed and then gets consumed by the reader. On the other hand, theatrical production is immediate; an actor performs and the audience witnesses it instantaneously. Time, so to speak, does not separate the author, the text, and the reader anymore. The question of authorship gets further complicated in Augusto Boal’s “Theatre of the Oppressed” movement where the audience is a direct participant like the actors in the performance. In this research, through an experimental performance, the duality of theatre is explored with the authorship discourse. And the conventional definition of authorship is subjected to additional complexity by erasing the distinction between an actor and the audience. The design/methodology of the experimental performance is as follows: The audience will be asked to produce a text under an anonymous virtual alias. The text, as it is being produced, will be read and performed by the actor. The audience who are also collectively “authoring” the text, will watch this performance and write further until everyone has contributed with one input each. The cycle of writing, reading, performing, witnessing, and writing will continue until the end. The intention is to create a dynamic system of writing/reading with the embodiment of the text through the actor. The actor is giving up the power to the audience to write the spoken word, stage instruction and direction while still keeping the agency of interpreting that input and performing in the chosen manner. This rapid conversation between the actor and the audience also creates a conversion of authorship. The main conclusion of this study is a perspective on the nature of dynamic authorship of theatre containing a critical enquiry of the collaboratively produced text, an individually performed act, and a collectively witnessed event. Using practice as a methodology, this paper contests the poststructuralist notion of the author as merely a ‘scriptor’ and breaks it further by involving the audience in the authorship as well.

Keywords: practice based research, performance studies, post-humanism, Avant-garde art, theatre

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Authors: Kamyar Tolouei, Ehsan Moosavi

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In open-pit mines, the long-term production scheduling optimization problem (LTPSOP) is a complicated problem that contains constraints, large datasets, and uncertainties. Uncertainty in the output is caused by several geological, economic, or technical factors. Due to its dimensions and NP-hard nature, it is usually difficult to find an ideal solution to the LTPSOP. The optimal schedule generally restricts the ore, metal, and waste tonnages, average grades, and cash flows of each period. Past decades have witnessed important measurements of long-term production scheduling and optimal algorithms since researchers have become highly cognizant of the issue. In fact, it is not possible to consider LTPSOP as a well-solved problem. Traditional production scheduling methods in open-pit mines apply an estimated orebody model to produce optimal schedules. The smoothing result of some geostatistical estimation procedures causes most of the mine schedules and production predictions to be unrealistic and imperfect. With the expansion of simulation procedures, the risks from grade uncertainty in ore reserves can be evaluated and organized through a set of equally probable orebody realizations. In this paper, to synthesize grade uncertainty into the strategic mine schedule, a stochastic integer programming framework is presented to LTPSOP. The objective function of the model is to maximize the net present value and minimize the risk of deviation from the production targets considering grade uncertainty simultaneously while satisfying all technical constraints and operational requirements. Instead of applying one estimated orebody model as input to optimize the production schedule, a set of equally probable orebody realizations are applied to synthesize grade uncertainty in the strategic mine schedule and to produce a more profitable and risk-based production schedule. A mixture of metaheuristic procedures and mathematical methods paves the way to achieve an appropriate solution. This paper introduced a hybrid model between the augmented Lagrangian relaxation (ALR) method and the metaheuristic algorithm, the Harris Hawks optimization (HHO), to solve the LTPSOP under grade uncertainty conditions. In this study, the HHO is experienced to update Lagrange coefficients. Besides, a machine learning method called Random Forest is applied to estimate gold grade in a mineral deposit. The Monte Carlo method is used as the simulation method with 20 realizations. The results specify that the progressive versions have been considerably developed in comparison with the traditional methods. The outcomes were also compared with the ALR-genetic algorithm and ALR-sub-gradient. To indicate the applicability of the model, a case study on an open-pit gold mining operation is implemented. The framework displays the capability to minimize risk and improvement in the expected net present value and financial profitability for LTPSOP. The framework could control geological risk more effectively than the traditional procedure considering grade uncertainty in the hybrid model framework.

Keywords: grade uncertainty, metaheuristic algorithms, open-pit mine, production scheduling optimization

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Authors: Hsien-Te Lin

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The purpose of this paper is to introduce the BCFES (building carbon footprint evaluation system), which is a LCA (life cycle assessment) tool developed by the Low Carbon Building Alliance (LCBA) in Taiwan. A qualified BCFES for the building industry should fulfill the function of evaluating carbon footprint throughout all stages in the life cycle of building projects, including the production, transportation and manufacturing of materials, construction, daily energy usage, renovation and demolition. However, many existing BCFESs are too complicated and not very designer-friendly, creating obstacles in the implementation of carbon reduction policies. One of the greatest obstacle is the misapplication of the carbon footprint inventory standards of PAS2050 or ISO14067, which are designed for mass-produced goods rather than building projects. When these product-oriented rules are applied to building projects, one must compute a tremendous amount of data for raw materials and the transportation of construction equipment throughout the construction period based on purchasing lists and construction logs. This verification method is very cumbersome by nature and unhelpful to the promotion of low carbon design. With a view to provide an engineer-oriented BCFE with pre-diagnosis functions, a component input/output (I/O) database system and a scenario simulation method for building energy are proposed herein. Most existing BCFESs base their calculations on a product-oriented carbon database for raw materials like cement, steel, glass, and wood. However, data on raw materials is meaningless for the purpose of encouraging carbon reduction design without a feedback mechanism, because an engineering project is not designed based on raw materials but rather on building components, such as flooring, walls, roofs, ceilings, roads or cabinets. The LCBA Database has been composited from existing carbon footprint databases for raw materials and architectural graphic standards. Project designers can now use the LCBA Database to conduct low carbon design in a much more simple and efficient way. Daily energy usage throughout a building's life cycle, including air conditioning, lighting, and electric equipment, is very difficult for the building designer to predict. A good BCFES should provide a simplified and designer-friendly method to overcome this obstacle in predicting energy consumption. In this paper, the author has developed a simplified tool, the dynamic Energy Use Intensity (EUI) method, to accurately predict energy usage with simple multiplications and additions using EUI data and the designed efficiency levels for the building envelope, AC, lighting and electrical equipment. Remarkably simple to use, it can help designers pre-diagnose hotspots in building carbon footprint and further enhance low carbon designs. The BCFES-LCBA offers the advantages of an engineer-friendly component I/O database, simplified energy prediction methods, pre-diagnosis of carbon hotspots and sensitivity to good low carbon designs, making it an increasingly popular carbon management tool in Taiwan. To date, about thirty projects have been awarded BCFES-LCBA certification and the assessment has become mandatory in some cities.

Keywords: building carbon footprint, life cycle assessment, energy use intensity, building energy

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Authors: Razali Bin Abidin

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This paper presents the development of a portable water jet cutter for soft materials such as meat. Twelve geometries of nozzles were simulated using finite element method. Water pressure was set to 1500 lb/in². Through the simulation, highest average water output speed was 133.04 m/s. The nozzle was fabricated from Al - alloy 5052 with the Factor of Safety~ 3. This indicates that the nozzle made of Al-alloy 5052 is capable of performing the cutting process without any fracture. Preliminary design of mobile water jet hand tool is presented at the end of this paper.

Keywords: water jet, finite element, Al-alloy 5052, nozzle geometry

Procedia PDF Downloads 357

Authors: Bai-Chen Xie, Xian-Peng Chen

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China has become the world's largest energy producer and consumer, and its development of renewable energy is of great significance to global energy governance and the fight against climate change. The rapid growth of solar power in China could help achieve its ambitious carbon peak and carbon neutrality targets early. However, the non-technical costs of solar power in China are much higher than at international levels, meaning that inefficiencies are rooted in poor management and improper policy design and that efficiency distortions have become a serious challenge to the sustainable development of the renewable energy industry. Unlike fossil energy generation technologies, the output of solar power is closely related to the volatile solar resource, and the spatial unevenness of solar resource distribution leads to potential efficiency spatial distribution differences. It is necessary to develop an efficiency evaluation method that considers the volatility of solar resources and explores the mechanism of the influence of natural geography and social environment on the spatially varying characteristics of efficiency distribution to uncover the root causes of managing inefficiencies. The study sets solar resources as stochastic inputs, introduces a chance-constrained data envelopment analysis model combined with the directional distance function, and measures the solar resource utilization efficiency of 222 solar power plants in representative photovoltaic bases in northwestern China. By the meta-frontier analysis, we measured the characteristics of different power plant clusters and compared the differences among groups, discussed the mechanism of environmental factors influencing inefficiencies, and performed statistical tests through the system generalized method of moments. Rational localization of power plants is a systematic project that requires careful consideration of the full utilization of solar resources, low transmission costs, and power consumption guarantee. Suitable temperature, precipitation, and wind speed can improve the working performance of photovoltaic modules, reasonable terrain inclination can reduce land cost, and the proximity to cities strongly guarantees the consumption of electricity. The density of electricity demand and high-tech industries is more important than resource abundance because they trigger the clustering of power plants to result in a good demonstration and competitive effect. To ensure renewable energy consumption, increased support for rural grids and encouraging direct trading between generators and neighboring users will provide solutions. The study will provide proposals for improving the full life-cycle operational activities of solar power plants in China to reduce high non-technical costs and improve competitiveness against fossil energy sources.

Keywords: solar power plants, environmental factors, data envelopment analysis, efficiency evaluation

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Authors: M. Warburton

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Background: Case study examining hydrotherapy for a person with DSI. A 46 year-old lady completely deaf and blind post congenital rubella syndrome. Touch becomes the primary information gathering sense to optimise function in life. Communication is achieved via tactile finger spelling and signals onto her hand and skin. Hydrotherapy may provide a suitable mobility environment and somato-sensory input to people, and especially DSI persons. Buoyancy, warmth, hydrostatic pressure, viscosity and turbulence are elements of hydrotherapy that may offer a DSI person somato-sensory input to stimulate the mechanoreceptors, thermoreceptors and proprioceptors and offer a unique hydro-therapeutic environment. Purpose: The purpose of this case study was to establish what measurable benefits could be achieved from hydrotherapy with a DSI person. Methods: Hydrotherapy was provided for 8-weeks, 2 x week, 35-minute session duration. Pool temperature 32.5 degrees centigrade. Pool length 25-metres. Each session consisted of mobility encouragement and supervision, and activities to stimulate the somato-sensory system utilising aquatic properties of buoyancy, turbulence, viscosity, warmth and hydrostatic pressure. Somato-sensory activities focused on stimulating touch and tactile exploration including objects of various shape, size, weight, contour, texture, elasticity, pliability, softness and hardness. Outcomes were measured by the Goal Attainment Scale (GAS) and included mobility distance, attendance, and timed tactile responsiveness to varying objects. Results: Mobility distance and attendance exceeded baseline expectations. Timed tactile responsiveness to varying objects also changed positively from baseline. Average scale scores were 1.00 with an overall GAS t-score of 63.69. Conclusions: Hydrotherapy can be a quantifiable physio-therapeutic option for persons with DSI. It provides a relatively safe environment for mobility and allows the somato-sensory system to be fully engaged - important for the DSI population. Implications: Hydrotherapy can be a measurable therapeutic option for a DSI person. Physiotherapists should consider hydrotherapy for DSI people. Hydrotherapy can offer unique physical properties for the DSI population not available on land.

Keywords: chronic, disability, disease, rehabilitation

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Authors: Ahmed E. Hodaib, Mohamed A. Hashem

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In engineering applications, a design has to be as fully perfect as possible in some defined case. The designer has to overcome many challenges in order to reach the optimal solution to a specific problem. This process is called optimization. Generally, there is always a function called “objective function” that is required to be maximized or minimized by choosing input parameters called “degrees of freedom” within an allowed domain called “search space” and computing the values of the objective function for these input values. It becomes more complex when we have more than one objective for our design. As an example for Multi-Objective Optimization Problem (MOP): A structural design that aims to minimize weight and maximize strength. In such case, the Pareto Optimal Frontier (POF) is used, which is a curve plotting two objective functions for the best cases. At this point, a designer should make a decision to choose the point on the curve. Engineers use algorithms or iterative methods for optimization. In this paper, we will discuss the Evolutionary Algorithms (EA) which are widely used with Multi-objective Optimization Problems due to their robustness, simplicity, suitability to be coupled and to be parallelized. Evolutionary algorithms are developed to guarantee the convergence to an optimal solution. An EA uses mechanisms inspired by Darwinian evolution principles. Technically, they belong to the family of trial and error problem solvers and can be considered global optimization methods with a stochastic optimization character. The optimization is initialized by picking random solutions from the search space and then the solution progresses towards the optimal point by using operators such as Selection, Combination, Cross-over and/or Mutation. These operators are applied to the old solutions “parents” so that new sets of design variables called “children” appear. The process is repeated until the optimal solution to the problem is reached. Reliable and robust computational fluid dynamics solvers are nowadays commonly utilized in the design and analyses of various engineering systems, such as aircraft, turbo-machinery, and auto-motives. Coupling of Computational Fluid Dynamics “CFD” and Multi-Objective Evolutionary Algorithms “MOEA” has become substantial in aerospace engineering applications, such as in aerodynamic shape optimization and advanced turbo-machinery design.

Keywords: mathematical optimization, multi-objective evolutionary algorithms "MOEA", computational fluid dynamics "CFD", aerodynamic shape optimization

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Authors: Moustapha H. Ibrahim, Dahir Abdourahman

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This document presents a short-circuit fault detection process in a photovoltaic (PV) system. The proposed method is developed in MATLAB/Simulink. It determines whatever the size of the installation number of the short circuit module. The proposed algorithm indicates the presence or absence of an abnormality on the power of the PV system through measures of hourly global irradiation, power output, and ambient temperature. In case a fault is detected, it displays the number of modules in a short circuit. This fault detection method has been successfully tested on two different PV installations.

Keywords: PV system, short-circuit, fault detection, modelling, MATLAB-Simulink

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Authors: Boris Barbolyas, Kristina Buckova, Tomas Volensky, Cyril Belavy, Ladislav Dedik

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Background: Based on statokinezigram, the human balance control is often studied. Approach to human postural reaction analysis is based on a combination of stabilometry output signal with retroreflective marker data signal processing, analysis, and understanding, in this study. The study shows another original application of Method of Developed Statokinesigram Trajectory (MDST), too. Methods: In this study, the participants maintained quiet bipedal standing for 10 s on stabilometry platform. Consequently, bilateral vibration stimuli to Achilles tendons in 20 s interval was applied. Vibration stimuli caused that human postural system took the new pseudo-steady state. Vibration frequencies were 20, 60 and 80 Hz. Participant's body segments - head, shoulders, hips, knees, ankles and little fingers were marked by 12 retroreflective markers. Markers positions were scanned by six cameras system BTS SMART DX. Registration of their postural reaction lasted 60 s. Sampling frequency was 100 Hz. For measured data processing were used Method of Developed Statokinesigram Trajectory. Regression analysis of developed statokinesigram trajectory (DST) data and retroreflective marker developed trajectory (DMT) data were used to find out which marker trajectories most correlate with stabilometry platform output signals. Scaling coefficients (λ) between DST and DMT by linear regression analysis were evaluated, too. Results: Scaling coefficients for marker trajectories were identified for all body segments. Head markers trajectories reached maximal value and ankle markers trajectories had a minimal value of scaling coefficient. Hips, knees and ankles markers were approximately symmetrical in the meaning of scaling coefficient. Notable differences of scaling coefficient were detected in head and shoulders markers trajectories which were not symmetrical. The model of postural system behavior was identified by MDST. Conclusion: Value of scaling factor identifies which body segment is predisposed to postural instability. Hypothetically, if statokinesigram represents overall human postural system response to vibration stimuli, then markers data represented particular postural responses. It can be assumed that cumulative sum of particular marker postural responses is equal to statokinesigram.

Keywords: center of pressure (CoP), method of developed statokinesigram trajectory (MDST), model of postural system behavior, retroreflective marker data

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Authors: Garry A. Einicke, Langford B. White

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This paper describes an optimum filter and smoother for recovering a Markov process message from noisy measurements. The developments follow from an equivalence between a state space model and a hidden Markov chain. The ensuing filter and smoother employ transition probability matrices and approximate probability distribution vectors. The properties of the optimum solutions are retained, namely, the estimates are unbiased and minimize the variance of the output estimation error, provided that the assumed parameter set are correct. Methods for estimating unknown parameters from noisy measurements are discussed. Signal recovery examples are described in which performance benefits are demonstrated at an increased calculation cost.

Keywords: optimal filtering, smoothing, Markov chains

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Authors: Eliska Smidova, Petr Kabele

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This paper describes non-linear finite element simulation of laminated veneer lumber (LVL) under tensile and shear loads that induce cracking along fibers. For this purpose, we use 2D homogeneous orthotropic constitutive model of tensile and shear fracture in timber that has been recently developed and implemented into ATENA® finite element software by the authors. The model captures (i) material orthotropy for small deformations in both linear and non-linear range, (ii) elastic behavior until anisotropic failure criterion is fulfilled, (iii) inelastic behavior after failure criterion is satisfied, (iv) different post-failure response for cracks along and across the grain, (v) unloading/reloading behavior. The post-cracking response is treated by fixed smeared crack model where Reinhardt-Hordijk function is used. The model requires in total 14 input parameters that can be obtained from standard tests, off-axis test results and iterative numerical simulation of compact tension (CT) or compact tension-shear (CTS) test. New engineered timber composites, such as laminated veneer lumber (LVL), offer improved structural parameters compared to sawn timber. LVL is manufactured by laminating 3 mm thick wood veneers aligned in one direction using water-resistant adhesives (e.g. polyurethane). Thus, 3 main grain directions, namely longitudinal (L), tangential (T), and radial (R), are observed within the layered LVL product. The core of this work consists in 3 numerical simulations of experiments where Radiata Pine LVL and Yellow Poplar LVL were involved. The first analysis deals with calibration and validation of the proposed model through off-axis tensile test (at a load-grain angle of 0°, 10°, 45°, and 90°) and CTS test (at a load-grain angle of 30°, 60°, and 90°), both of which were conducted for Radiata Pine LVL. The second finite element simulation reproduces load-CMOD curve of compact tension (CT) test of Yellow Poplar with the aim of obtaining cohesive law parameters to be used as an input in the third finite element analysis. That is four point bending test of small-size arch of 780 mm span that is made of Yellow Poplar LVL. The arch is designed with a through crack between two middle layers in the crown. Curved laminated beams are exposed to high radial tensile stress compared to timber strength in radial tension in the crown area. Let us note that in this case the latter parameter stands for tensile strength in perpendicular direction with respect to the grain. Standard tests deliver most of the relevant input data whereas traction-separation law for crack along the grain can be obtained partly by inverse analysis of compact tension (CT) test or compact tension-shear test (CTS). The initial crack was modeled as a narrow gap separating two layers in the middle the arch crown. Calculated load-deflection curve is in good agreement with the experimental ones. Furthermore, crack pattern given by numerical simulation coincides with the most important observed crack paths.

Keywords: compact tension (CT) test, compact tension shear (CTS) test, fixed smeared crack model, four point bending test, laminated arch, laminated veneer lumber LVL, off-axis test, orthotropic elasticity, orthotropic fracture criterion, Radiata Pine LVL, traction-separation law, yellow poplar LVL, 2D constitutive model

Procedia PDF Downloads 266

Authors: Okpala Charles Chikwendu, Ezeanyim Okechukwu Chiedu, Onukwuli Somto Kenneth

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The demand for lightweight and fuel-efficient automobiles has led to the use of fiber-reinforced polymer composites in place of traditional metal parts. Coir, a natural fiber, offers qualities such as low cost, good tensile strength, and biodegradability, making it a potential filler material for automotive components. However, poor interfacial adhesion between coir and polymeric matrices has been a challenge. To address poor interfacial adhesion with polymeric matrices due to their moisture content and method of preparation, the extracted coir was chemically treated using NaOH. To develop a side view mirror encasement by investigating the mechanical effect of fiber percentage composition, fiber length and percentage composition of Epoxy in a coir fiber reinforced composite, polyester was adopted as the resin for the mold, while that of the product is Epoxy. Coir served as the filler material for the product. Specimens with varied compositions of fiber loading (15, 30 and 45) %, length (10, 15, 20, 30 and 45) mm, and (55, 70, 85) % weight of epoxy resin were fabricated using hand lay-up technique, while those specimens were later subjected to mechanical tests (Tensile, Flexural and Impact test). The results of the mechanical test showed that the optimal solution for the input factors is coir at 45%, epoxy at 54.543%, and 45mm coir length, which was used for the development of a vehicle’s side view mirror encasement. The optimal solutions for the response parameters are 49.333 Mpa for tensile strength, flexural for 57.118 Mpa, impact strength for 34.787 KJ/M2, young modulus for 4.788 GPa, stress for 4.534 KN, and 20.483 mm for strain. The models that were developed using Design Expert software revealed that the input factors can achieve the response parameters in the system with 94% desirability. The study showed that coir is quite durable for filler material in an epoxy composite for automobile applications and that fiber loading and length have a significant effect on the mechanical behavior of coir fiber-reinforced epoxy composites. The coir's low density, considerable tensile strength, and bio-degradability contribute to its eco-friendliness and potential for reducing the environmental hazards of synthetic automotive components.

Keywords: coir, composite, coir fiber, coconut husk, polymer, automobile, mechanical test

Procedia PDF Downloads 41

Authors: Muhammad Abu-Khaizaran, Ahmad Faza’, Tariq Othman, Yahia Yousef

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This paper presents a study to provide sufficient and reliable information about constructing a Photovoltaic energy profile of the Birzeit University campus (BZU) based on the weather forecast. The developed Photovoltaic energy profile helps to predict the energy yield of the Photovoltaic systems based on the weather forecast and hence helps planning energy production and consumption. Two models will be developed in this paper; a Clear Sky Irradiance model and a Cloud-Cover Radiation model to predict the irradiance for a clear sky day and a cloudy day, respectively. The adopted procedure for developing such models takes into consideration two levels of abstraction. First, irradiance and weather data were acquired by a sensory (measurement) system installed on the rooftop of the Information Technology College building at Birzeit University campus. Second, power readings of a fully operational 51kW commercial Photovoltaic system installed in the University at the rooftop of the adjacent College of Pharmacy-Nursing and Health Professions building are used to validate the output of a simulation model and to help refine its structure. Based on a comparison between a mathematical model, which calculates Clear Sky Irradiance for the University location and two sets of accumulated measured data, it is found that the simulation system offers an accurate resemblance to the installed PV power station on clear sky days. However, these comparisons show a divergence between the expected energy yield and actual energy yield in extreme weather conditions, including clouding and soiling effects. Therefore, a more accurate prediction model for irradiance that takes into consideration weather factors, such as relative humidity and cloudiness, which affect irradiance, was developed; Cloud-Cover Radiation Model (CRM). The equivalent mathematical formulas implement corrections to provide more accurate inputs to the simulation system. The results of the CRM show a very good match with the actual measured irradiance during a cloudy day. The developed Photovoltaic profile helps in predicting the output energy yield of the Photovoltaic system installed at the University campus based on the predicted weather conditions. The simulation and practical results for both models are in a very good match.

Keywords: clear-sky irradiance model, cloud-cover radiation model, photovoltaic, weather forecast

Procedia PDF Downloads 116