Comparison of BLISS 2000 and CO in Turbine Blade MDO for Aircraft Engine

2013 ◽  
Author(s):  
Junjie Yang ◽  
Jingyang Chen ◽  
Jiachao Yan
Keyword(s):  
Weight Reduction ◽  
Thermal Structure ◽  
Turbine Blades ◽  
Fem Analysis ◽  
Aircraft Engine ◽  
Surrogate Models ◽  
System Level ◽  
Computational Accuracy ◽  
Numerical Example ◽  
The Impact

In this paper, the two methods of CO and BLISS 2000 are compared by using a classical numerical example firstly. The results show that the BLISS 2000 performs better in both computational accuracy and efficiency, because the scale of the optimization problem, such as the number of variables and constraints, in the BLISS 2000 is less than that in the CO. Moreover, the BLISS 2000 optimizes directly the system objectives while the CO focuses on decreasing the discrepancy between the coupled variables in different fields. The two methods are then applied to an aerodynamics-thermal-structure coupled design problem for the turbine blades of an aircraft engine. Based on the results of sensitivity analysis, the number of design variables is reduced from 34 to 12. To eliminate the impact of the surrogate models on the different MDO algorithms as much as possible, the same initial Kriging surrogate models are not refreshed during the MDO procedures. Without the high fidelity simulation such as CFD and FEM analysis in the MDO processes, the BLISS 2000 method shows the more powerful capability of the convergence than that of the CO method, as shown in the numerical example. The optimization steps of the system level for BLISS 2000 are approximate 1/5 of those for CO, and the iteration number of step in the sub-system level with BLISS 2000 is only about 1/8 of that with CO. Based on the weight sum of two objectives, the BLISS 2000 shows more robust than the CO because both weight reduction and aerodynamic efficiency are improved in the BLISS 2000 but only the blade weight reduction is gained in the CO. For other multi-objective optimization approaches, however, it still needs to be demonstrated through more studies.

Comparative assessment of morphological mechanisms of maintaining structural liver homeostasis in the dynamics of exposure to coal-rock dust and sodium fluoride on the body

2020 ◽  
pp. 189-194
Author(s):  
M. S. Bugaeva ◽  
O. I. Bondarev ◽  
N. N. Mikhailova ◽  
L. G. Gorokhova
Keyword(s):  
Sodium Fluoride ◽  
Morphological Changes ◽  
The Body ◽  
System Level ◽  
Production Factor ◽  
Coal Rock ◽  
The Impact ◽  
Structural Homeostasis ◽  
Rock Dust

Introduction. The impact on the body of such factors of the production environment as coal-rock dust and fluorine compounds leads to certain shift s in strict indicators of homeostasis at the system level. Maintaining the relative constancy of the internal environment of the body is provided by the functional consistency of all organs and systems, the leading of which is the liver. Organ repair plays a crucial role in restoring the structure of genetic material and maintaining normal cell viability. When this mechanism is damaged, the compensatory capabilities of the organ are disrupted, homeostasis is disrupted at the cellular and organizational levels, and the development of the main pathological processes is noted.The aim of the study is to compare the morphological mechanisms of maintaining structural homeostasis of the liver in the dynamics of the impact on the body of coal-rock dust and sodium fluoride.Materials and methods. Experimental studies were conducted on adult white male laboratory rats. Features of morphological mechanisms for maintaining structural homeostasis of the liver in the dynamics of exposure to coal-rock dust and sodium fluoride were studied on experimental models of pneumoconiosis and fluoride intoxication. For histological examination in experimental animals, liver sampling was performed after 1, 3, 6, 9, 12 weeks of the experiment.Results. The specificity of morphological changes in the liver depending on the harmful production factor was revealed. It is shown that chronic exposure to coal-rock dust and sodium fluoride is characterized by the development of similar morphological changes in the liver and its vessels from the predominance of the initial compensatory-adaptive to pronounced violations of the stromal and parenchymal components. Long-term inhalation of coal-rock dust at 1–3 weeks of seeding triggers adaptive mechanisms in the liver in the form of increased functional activity of cells, formation of double-core hepatocytes, activation of immunocompetent cells and endotheliocytes, ensuring the preservation of the parenchyma and the general morphostructure of the organ until the 12th week of the experiment. Exposure to sodium fluoride leads to early disruption of liver compensatory mechanisms and the development of dystrophic changes in the parenchyma with the formation of necrosis foci as early as the 6th week of the experiment.Conclusions. The study of mechanisms for compensating the liver structure in conditions of long-term exposure to coal-rock dust and sodium fluoride, as well as processes that indicate their failure, and the timing of their occurrence, is of theoretical and practical importance for developing recommendations for the timely prevention and correction of pathological conditions developing in employees of the aluminum and coal industry.The authors declare no conflict of interests.

Design of a Robust Memristive Spiking Neuromorphic System with Unsupervised Learning in Hardware

2021 ◽  
Vol 17 (4) ◽  
pp. 1-26
Author(s):  
Md Musabbir Adnan ◽  
Sagarvarma Sayyaparaju ◽  
Samuel D. Brown ◽  
Mst Shamim Ara Shawkat ◽  
Catherine D. Schuman ◽  
...  
Keyword(s):  
Unsupervised Learning ◽  
Recognition Task ◽  
Single Layer ◽  
Process Variations ◽  
Spike Timing ◽  
System Level ◽  
Design Parameters ◽  
Digital Pulse ◽  
Neuromorphic System ◽  
The Impact

Spiking neural networks (SNN) offer a power efficient, biologically plausible learning paradigm by encoding information into spikes. The discovery of the memristor has accelerated the progress of spiking neuromorphic systems, as the intrinsic plasticity of the device makes it an ideal candidate to mimic a biological synapse. Despite providing a nanoscale form factor, non-volatility, and low-power operation, memristors suffer from device-level non-idealities, which impact system-level performance. To address these issues, this article presents a memristive crossbar-based neuromorphic system using unsupervised learning with twin-memristor synapses, fully digital pulse width modulated spike-timing-dependent plasticity, and homeostasis neurons. The implemented single-layer SNN was applied to a pattern-recognition task of classifying handwritten-digits. The performance of the system was analyzed by varying design parameters such as number of training epochs, neurons, and capacitors. Furthermore, the impact of memristor device non-idealities, such as device-switching mismatch, aging, failure, and process variations, were investigated and the resilience of the proposed system was demonstrated.

scholarly journals Impact of COVID-19 pandemic on the oncologic care continuum: urgent need to restore patients care to pre-COVID-19 era

2021 ◽  
pp. 1-11
Author(s):  
Ernest Osei ◽  
Ruth Francis ◽  
Ayan Mohamed ◽  
Lyba Sheraz ◽  
Fariba Soltani-Mayvan
Keyword(s):  
Cancer Care ◽  
Healthcare Professionals ◽  
Negative Impact ◽  
System Level ◽  
Care Continuum ◽  
Cancer Services ◽  
Number Of Patients ◽  
Prevention Programmes ◽  
Screening And Prevention ◽  
The Impact

Abstract Background: Globally, cancer is the second leading cause of death, and it is estimated that over 18·1 million new cases are diagnosed annually. The COVID-19 pandemic has significantly impacted almost every aspect of the provision and management of cancer care worldwide. The time-critical nature of COVID-19 diagnosis and the large number of patients requiring hospitalisation necessitated the rerouting of already limited resources available for cancer services and programmes to the care of COVID-19 patients. Furthermore, the stringent social distancing, restricted in-hospital visits and lockdown measures instituted by various governments resulted in the disruption of the oncologic continuum including screening, diagnostic and prevention programmes, treatments and follow-up services as well as research and clinical trial programmes. Materials and Methods: We searched several databases from October 2020 to January 2021 for relevant studies published in English between 2020 and 2021 and reporting on the impact of COVID-19 on the cancer care continuum. This narrative review paper describes the impact of the COVID-19 pandemic on the cancer patient care continuum from screening and prevention to treatments and ongoing management of patients. Conclusions: The COVID-19 pandemic has profoundly impacted cancer care and the management of cancer services and patients. Nevertheless, the oncology healthcare communities worldwide have done phenomenal work with joint and collaborative efforts, utilising best available evidence-based guidelines to continue to give safe and effective treatments for cancer patients while maintaining the safety of patients, healthcare professionals and the general population. Nevertheless, several healthcare centres are now faced with significant challenges with the management of the backlog of screening, diagnosis and treatment cases. It is imperative that governments, leaders of healthcare centres and healthcare professionals take all necessary actions and policies focused on minimising further system-level delays to cancer screening, diagnosis, treatment initiation and clearing of all backlogs cases from the COVID-19 pandemic in order to mitigate the negative impact on cancer outcomes.

scholarly journals Deep Neural Network and Polynomial Chaos Expansion-Based Surrogate Models for Sensitivity and Uncertainty Propagation: An Application to a Rockfill Dam

Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1830
Author(s):  
Gullnaz Shahzadi ◽  
Azzeddine Soulaïmani
Keyword(s):  
Polynomial Chaos ◽  
Complex Structure ◽  
Uncertainty Propagation ◽  
Surrogate Models ◽  
Polynomial Chaos Expansion ◽  
Soil Parameters ◽  
Chaos Expansion ◽  
Rockfill Dam ◽  
Parametric Studies ◽  
The Impact

Computational modeling plays a significant role in the design of rockfill dams. Various constitutive soil parameters are used to design such models, which often involve high uncertainties due to the complex structure of rockfill dams comprising various zones of different soil parameters. This study performs an uncertainty analysis and a global sensitivity analysis to assess the effect of constitutive soil parameters on the behavior of a rockfill dam. A Finite Element code (Plaxis) is utilized for the structure analysis. A database of the computed displacements at inclinometers installed in the dam is generated and compared to in situ measurements. Surrogate models are significant tools for approximating the relationship between input soil parameters and displacements and thereby reducing the computational costs of parametric studies. Polynomial chaos expansion and deep neural networks are used to build surrogate models to compute the Sobol indices required to identify the impact of soil parameters on dam behavior.

scholarly journals System Level Simulation of Microgrid Power Electronic Systems

Electronics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 644
Author(s):  
Michal Frivaldsky ◽  
Jan Morgos ◽  
Michal Prazenica ◽  
Kristian Takacs
Keyword(s):  
Smart Grid ◽  
Simulation Model ◽  
Real Time ◽  
Power Converter ◽  
System Level ◽  
Time Behavior ◽  
Operational Parameters ◽  
System Level Simulation ◽  
Time Operation ◽  
The Impact

In this paper, we describe a procedure for designing an accurate simulation model using a price-wised linear approach referred to as the power semiconductor converters of a DC microgrid concept. Initially, the selection of topologies of individual power stage blocs are identified. Due to the requirements for verifying the accuracy of the simulation model, physical samples of power converters are realized with a power ratio of 1:10. The focus was on optimization of operational parameters such as real-time behavior (variable waveforms within a time domain), efficiency, and the voltage/current ripples. The approach was compared to real-time operation and efficiency performance was evaluated showing the accuracy and suitability of the presented approach. The results show the potential for developing complex smart grid simulation models, with a high level of accuracy, and thus the possibility to investigate various operational scenarios and the impact of power converter characteristics on the performance of a smart gird. Two possible operational scenarios of the proposed smart grid concept are evaluated and demonstrate that an accurate hardware-in-the-loop (HIL) system can be designed.

Life Prediction of Power Turbine Components for High Exhaust Back Pressure Applications: Part I — Disks

2015 ◽  
Author(s):  
Dipankar Dua ◽  
Brahmaji Vasantharao
Keyword(s):  
Steady State ◽  
Secondary Flow ◽  
Gas Turbines ◽  
Life Prediction ◽  
Creep Damage ◽  
Back Pressure ◽  
System Level ◽  
Cyclic Life ◽  
Power Turbine ◽  
The Impact

Industrial and aeroderivative gas turbines when used in CHP and CCPP applications typically experience an increased exhaust back pressure due to pressure losses from the downstream balance-of-plant systems. This increased back pressure on the power turbine results not only in decreased thermodynamic performance but also changes power turbine secondary flow characteristics thus impacting lives of rotating and stationary components of the power turbine. This Paper discusses the Impact to Fatigue and Creep life of free power turbine disks subjected to high back pressure applications using Siemens Energy approach. Steady State and Transient stress fields have been calculated using finite element method. New Lifing Correlation [1] Criteria has been used to estimate Predicted Safe Cyclic Life (PSCL) of the disks. Walker Strain Initiation model [1] is utilized to predict cycles to crack initiation and a fracture mechanics based approach is used to estimate propagation life. Hyperbolic Tangent Model [2] has been used to estimate creep damage of the disks. Steady state and transient temperature fields in the disks are highly dependent on the secondary air flows and cavity dynamics thus directly impacting the Predicted Safe Cyclic Life and Overall Creep Damage. A System-level power turbine secondary flow analyses was carried out with and without high back pressure. In addition, numerical simulations were performed to understand the cavity flow dynamics. These results have been used to perform a sensitivity study on disk temperature distribution and understand the impact of various back pressure levels on turbine disk lives. The Steady Sate and Transient Thermal predictions were validated using full-scale engine test and have been found to correlate well with the test results. The Life Prediction Study shows that the impact on PSCL and Overall Creep damage for high back pressure applications meets the product design standards.

Passenger aircraft emissions analysis at Ordu-Giresun International Airport, Turkey in 2017

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ilkay Orhan
Keyword(s):  
Aircraft Engine ◽  
Civil Aviation ◽  
Exhaust Emission ◽  
Aircraft Emissions ◽  
Emission Data ◽  
Emission Analysis ◽  
Content Type ◽  
International Airport ◽  
Engine Emission ◽  
The Impact

Purpose The purpose of this study is to present the pollutant gas produced by hydrocarbons (HC), carbon monoxide (CO) and nitrogen oxides (NOx) and the quantity of fuel burned from commercial aircraft at Ordu-Giresun International Airport, Turkey during the landing and take-off (LTO) cycles in 2017. Design/methodology/approach The flight data recorded by the General Directorate of State Airports Authority and the aircraft engine emission data from International Civil Aviation Organization (ICAO) Engine Exhaust Emission Databank were used for calculation. The aircraft and engine types used by the airlines for flight at Ordu-Giresun International Airport were determined. To evaluate the effect of taxi time on emission amounts, analysis and evaluations were made by taking different taxi times into consideration. Findings As a result of the emission analysis, the amount of fuel consumed by the aircraft were calculated as 6,551.52 t/y, and the emission amounts for CO, HC and NOx were estimated as 66.81, 4.20 and 79.97 t/y, respectively. Practical implications This study is aimed to reveal the effect and contribution of taxi time on the emitted emission at the airport during the LTO phase of the aircraft. Originality/value This study helps aviation authorities explain the importance of developing procedures that ensure the delivery of aircraft to flights in minimum time by raising awareness of the impact of taxi time on emitted emissions, and contributes to the determination of an aircraft emission inventory at Ordu-Giresun International Airport.

scholarly journals A Statistical Modeling Methodology for Long-Term Wind Generation and Power Ramp Simulations in New Generation Locations

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2442 ◽  
Author(s):  
Jussi Ekström ◽  
Matti Koivisto ◽  
Ilkka Mellin ◽  
Robert Millar ◽  
Matti Lehtonen
Keyword(s):  
Power Generation ◽  
Wind Power ◽  
Statistical Modeling ◽  
Renewable Energy Sources ◽  
Measurement Data ◽  
Wind Power Generation ◽  
System Level ◽  
Wind Generation ◽  
The Impact

In future power systems, a large share of the energy will be generated with wind power plants (WPPs) and other renewable energy sources. With the increasing wind power penetration, the variability of the net generation in the system increases. Consequently, it is imperative to be able to assess and model the behavior of the WPP generation in detail. This paper presents an improved methodology for the detailed statistical modeling of wind power generation from multiple new WPPs without measurement data. A vector autoregressive based methodology, which can be applied to long-term Monte Carlo simulations of existing and new WPPs, is proposed. The proposed model improves the performance of the existing methodology and can more accurately analyze the temporal correlation structure of aggregated wind generation at the system level. This enables the model to assess the impact of new WPPs on the wind power ramp rates in a power system. To evaluate the performance of the proposed methodology, it is verified against hourly wind speed measurements from six locations in Finland and the aggregated wind power generation from Finland in 2015. Furthermore, a case study analyzing the impact of the geographical distribution of WPPs on wind power ramps is included.

scholarly journals Empirically evaluating the impact of adjudicative tribunals in the health sector: context, challenges and opportunities

2011 ◽  
Vol 7 (2) ◽  
pp. 147-174
Author(s):  
Steven J. Hoffman ◽  
Lorne Sossin
Keyword(s):  
Health System ◽  
Health Sector ◽  
Cost Effective ◽  
System Level ◽  
Challenges And Opportunities ◽  
External Impact ◽  
Health System Governance ◽  
Evaluation Matrix ◽  
The Impact ◽  
Methodological Difficulties

AbstractAdjudicative tribunals are an integral part of health system governance, yet their real-world impact remains largely unknown. Most assessments focus on internal accountability and use anecdotal methodologies; few, studies if any, empirically evaluate their external impact and use these data to test effectiveness, track performance, inform service improvements and ultimately strengthen health systems. Given that such assessments would yield important benefits and have been conducted successfully in similar settings (e.g. specialist courts), their absence is likely attributable to complexity in the health system, methodological difficulties and the legal environment within which tribunals operate. We suggest practical steps for potential evaluators to conduct empirical impact evaluations along with an evaluation matrix template featuring possible target outcomes and corresponding surrogate endpoints, performance indicators and empirical methodologies. Several system-level strategies for supporting such assessments have also been suggested for academics, health system institutions, health planners and research funders. Action is necessary to ensure that policymakers do not continue operating without evidence but can rather pursue data-driven strategies that are more likely to achieve their health system goals in a cost-effective way.

scholarly journals Eco-friendly technology of manufacturing complex products made of composites

2019 ◽  
Vol 140 ◽  
pp. 02004
Author(s):  
Aleksey Ignatov ◽  
Rustam Subkhankulov
Keyword(s):  
Composite Materials ◽  
Cross Section ◽  
Manufacturing Process ◽  
Volume Fraction ◽  
Turbine Blades ◽  
Variable Cross Section ◽  
Variable Cross ◽  
Technological Parameters ◽  
Technological Support ◽  
The Impact

Numerous studies in application of modern composite materials show that their advantages can be successfully implemented in manufacturing «smart» products. This study proposes an improved technological method of manufacturing multilayer environmentally friendly products with a variable cross section, which allows us to expand the possibilities of using modern polymer composite materials (PCM). The technology allows manufacturing products of the most complex geometric shapes, such as wind turbine blades. The aim of the study is the technological support of engineering production in the manufacture of multilayer products of variable cross section made from PCM. Scientific novelty consists in identifying the patterns of implementation and management of the manufacturing process of multilayer products of variable cross-section, and establishing the influence of structural and technological parameters of the manufacturing process on their operational characteristics. The relationship between the pressure of a hot directed air stream and the volume fraction of pores in the hardened material of a multilayer composite product with a variable cross section during layer-by-layer application is investigated. During the study, fundamental and applied principles of mechanical engineering technology, material resistance, adhesion theory, mathematical statistics tools and software were used to process the results of the experiment. Based on the results of laboratory studies, a methodology has been developed for effective prediction of pore content in the manufacturing of composite products. The introduction of the presented technology and the corresponding original methodology into production will reduce the complexity and energy costs of manufacturing composite products, improve their quality and reduce the impact of toxic components from composite materials on workers.

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