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نتیجه جستجو - GCM

تعداد مقالات یافته شده: 9
ردیف عنوان نوع
1 Projection of spatiotemporal variability of wave power in the Persian Gulf by the end of 21st century: GCM and CORDEX ensemble
پیش بینی تغییر پذیری مکانی و قدرت موج در خلیج فارس تا پایان قرن بیست و یکم: GCM و CORDEX-2020
This study investigates future variability of wave power in the Persian Gulf. The contribution of this paper is twofold: (a) to evaluate spatiotemporal resolutions, downscaling techniques and global circulation model (GCM) selection impacts running multi-climate models, and (b) to project wave energy resources and its variability by the end of 21st century using RCP4.5 and RCP8.5 as two different representative concentration pathways (RCPs). The SWAN (Simulating Waves Nearshore) model forcing with near surface wind components was employed for wave simulation. The numerical wave model was calibrated and validated using wave measurements by two buoys prior to wave energy computations. The results of wave models obtained from different climate models showed a wide range of variety for different climatic resources associated with GCM selection, temporal and spatial resolutions and downscaling approach. Outputs of the wave model forcing with 3 hourly wind data of CMCC-CM and CORDEX-MPI (Max Plank Institute) with daily temporal resolution were recognized as the models with the best performance. Using a weighted average of these two models, the wave characteristics were obtained and wave energy were computed for the historical and future periods. Temporal distribution of energy shows highly intra-annual and seasonal variability when the mean wave power for the strongest month exceeds 1000Watt per meter that is 10 times higher than the mean wave power in the weakest month. Similarly, a strong spatial variability in wave power distributionwas revealed where the middle part of the Gulf has found to have the highest energy and the eastern and northwestern regions have the lowest energy. The projections illustrated a decreasing trend on future wave energy up to 40% in the Iranian coastlines and lower rate of changes in the southern stripe of the study area.
Keywords: Renewable energy | Climate change | CORDEX | Representative concentration pathways | Energy management
مقاله انگلیسی
2 Steering control law for double-gimbal scissored-pair CMG
قانون کنترل فرمان دو حلقه قیچی جفت CMG-2020
Because control moment gyroscopes (CMGs) can generate a large torque compared to reaction wheels, they are used as actuators for attitude control of large spacecraft. However, when the number of Single-Gimbal CMG (SGCMG) units is five or less, there can be internal singularities that cannot generate torque around the desired direction. To construct a system that has no internal singularities, six or more SGCMGs are required, because an orthogonally arrayed, three scissored-pair CMG system has no internal singularities. Because CMG singularities are disruptive for attitude control, a great deal of effort has been devoted to overcoming the CMG singularity problem; the various designs include Variable-Speed CMGs (VSCMGs), Double-Gimbal CMGs (DGCMGs), and Double-Gimbal Variable- Speed CMGs (DGVSCMGs). However, these designs still have problems, such as a slow response to torque generation commands about the wheel axis in VSCMGs and DGVSCMGs, and difficulty in precise attitude tracking when perturbation torque is generated to avoid singularities. To overcome the problems of the traditional CMG configurations, this paper proposes a new CMG system configuration that we call the Double-Gimbal Scissored-pair CMG (DGSPCMG) system. Because the DGSPCMG system is a hybrid system combining a Scissored-Pair CMG and a DGCMG, the DGSPCMG system does not have internal singularities except at the origin and along the x-axis. Moreover, this system can recover from an internal singularity by null motion only, and from outer singularities (saturation singularities) by steering the scissored-pair gimbals only. Thus, generation of perturbation torque is unnecessary for recovering from singularities, and a precise attitude tracking maneuver can be more easily achieved. This paper presents a conceptual design of a DGSPCMG system and describes a steering control law for the proposed system. Furthermore, the validity of the proposed steering control law is demonstrated through numerical simulations and results of comparison experiments are shown to demonstrate the advantage of the DGSPCMG over a VSCMG.
Keywords: Scissored-pair CMG | Double gimbal CMG | Steering control law | Singularities
مقاله انگلیسی
3 Predicting the climate change impacts on water-carbon coupling cycles for a loess hilly-gully watershed
پیش بینی تأثیر تغییرات آب و هوا بر چرخه اتصال آب و کربن برای یک حوزه آبخیز کوهستانی -2020
Understanding the climate change impacts on water and carbon cycles is of great importance for comprehensive watershed management. Although many studies have been conducted on the future climate change impacts on either water cycle or carbon cycle, the potential impacts on water-carbon coupling cycles are still poorly understood. This study used an integrated hydro-biochemical model (SWAT-DayCent) to quantitatively investigate the climate change impacts on water-carbon coupling cycles with a case study of typical loess hilly-gully watershed- the Jinghe River Basin (JRB) on the Loess Plateau. We used climate scenarios data derived under the three Representative Concentration Pathways (RCPs2.6, 4.5 and 8.5) by five downscaled Global Circulation Models (GCMs) and set two future periods of 2020–2049 (near future, NF) and 2070–2099 (far future, FF). It was projected that the annual precipitation would generally decrease slightly during the NF period but increase by 4–11% during the FF period, while the maximum/minimum air temperatures would increase significantly. The average annual streamflow would decrease (with up to 20.1% under RCP8.5) and evapotranspiration (ET) would remain almost unchanged during the NF period; however, both of them would increase during the FF period. The net primary production (NPP) would be generally higher due to the CO2 fertilization, whereas the soil organic carbon would decrease across all scenarios due to the warmer climate. The NPP-ET was projected to be closely coupled across all scenarios, and this coupling was mainly controlled by the inter-annual variability (IAV) of precipitation. Moreover, the precipitation IAV combined with NPP-ET coupling could also jointly control the NPP variability in the JRB. These projections in water-carbon coupling cycles can be useful to make betterinformed decisions for future water resources and ecosystem management of the loess hilly-gully regions.
Keywords: Climate change | SOC | Streamflow | SWAT-DayCent | Water-carbon coupling
مقاله انگلیسی
4 Singularity radius gradient-based rapid singularity-escape steering law for SGCMGs
قانون فرمان یکپارچه فرار سریع تکینگی شعاع تکینگی برای SGCMG ها-2020
In order to visualize singularity of SGCMGs in gimbal angle space, a novel continuous bounded singularity parameter--Singularity Radius, whose sign can distinctly determine singularity type, is proposed. Then a rapid singularity-escape steering law is proposed basing on gradient of Singularity Radius and residual base vector to drive the SGCMG system to neighboring singular boundary, and quickly escape elliptic singularities. Finally, simulation results on Pyramid-type and skew-type configuration demonstrate the effectiveness and rapidness of the proposed steering law.
KEYWORDS : Gaussian curvature | Rapid singularity escape | Single gimbal control | moment gyroscope | Singularity-escape steering | law | Singularity parameter| Singularity type
مقاله انگلیسی
5 An enhanced extreme learning machine model for river flow forecasting: State-of-the-art, practical applications in water resource engineering area and future research direction
یک مدل ماشین پیشرفته افراطی برای پیش بینی جریان رودخانه: پیشرفته ترین برنامه ها ، کاربردهای عملی در منطقه مهندسی منابع آب و جهت گیری تحقیقات آینده-2019
Despite the massive diversity in the modeling requirements for practical hydrological applications, there remains a need to develop more reliable and intelligent expert systems used for real-time prediction purposes. The challenge in meeting the standards of an expert system is primarily due to the influence and behavior of hydrological processes that is driven by natural fluctuations over the physical scale, and the resulting variance in the underlying model input datasets. River flow forecasting is an imperative task for water resources operation and management, water demand assessments, irrigation and agriculture, early flood warning and hydropower generations. This paper aims to investigate the viability of the enhanced version of extreme learning machine (EELM) model in river flow forecasting applied in a tropical environment. Herein, we apply the complete orthogonal decomposition (COD) learning tool to tune the output-hidden layer of the ELM model’s internal neuronal system, instead of the conventional multi-resolution tool (e.g., singular value decomposition). ToA-ELM, AdaBoost.RT-extreme learning machine; AI, artificial intelligence; ANFIS, adaptive neuro-fuzzy inference system; ANN, artificial neural network; ARIMA, autoregressive integrated moving average; AtmP, atmospheric pressure; B-ANN, bootstrap-artificial neural network; BCSO, binary-coded swarm optimization; B-ELM, bootstrap-extreme learning machine; C-ELM, complex-extreme learning machine; Cl−1, chloride; COD, complete orthogonal decomposition (COD); CRO-ELM, coral reefs optimization-extreme learning machine; DE-ELM, deferential evolution-extreme learning machine; DID, department of Irrigation and Drainage; DO, dissolved oxygen concentration; EC-SVR, evolutionary computation-based support vector machine; EDI, effective drought index; ELM, extreme learning machine; EELM, enhanced extreme learning machine; EEMD, ensemble empirical mode decomposition; EL-ANFIS, extreme learning adaptive neuro-fuzzy inference system; EMD, empirical mode decomposition; Ens, Nash-Sutcliffe coefficient; Ensemble-ELM, ensemble-extreme learning machine; EPR, evolutionary polynomial regression; ESNs, echo state networks; ETo, evapotranspiration; Fe, iron; Fr, Froude number; FS, factor of safety; GA-ELM, genetic algorithm-extreme learning machine; GCM, general circulation model; G-ELM, geomorphology extreme learning machine; GP, genetic programming; GRNN, generalized regression neural network; HCO3 -1, bicarbonate; HDSR, diffuse solar radiation; HRT, hydraulic retention time; I-ELM, integrated extreme learning machine; KELM, Kernelextreme learning machine; LST, land surface temperature; LASSO, least absolute shrinkage and selection operator; LSTM, long short-term memory network; LSSVM, least square support vector machine; MAE, mean absolute error; MARS, multivariate adaptive regression spline; MBFIPS, Multi-objective binary-coded fully informed particle swarm optimization; MC-OS-ELM, meta cognitive-online sequential-extreme learning machine; MLPNN, multi-linear perceptron neural network; MLR, multiple linear regression; MME, multi-model ensemble; NEMR, northeast monsoon rainfall; NO2 -1, nitrite; NO3 -1, nitrate; NO2, nitrogen dioxide; NT, total nitrogen; O3, ozone; OP-ELM, optimally pruned-extreme learning machine; OSELM, online sequential extreme learning machine; PCA, principal component analysis; pH, power of hydrogen; PM10, air pollution “suspended particulate matters”; PO4 -3, phosphorus; R-ELM, radial basis-extreme learning machine; r, determination coefficient; RE, relative error; RF, rainfall; RH, relative humidity; RHmax, maximum relative humidity; RHmean, mean relative humidity; RHmin, minimum relative humidity; RMSE, root mean square error; RVM, relevance vector machine; SaE-ELM, self-adaptive evolutionary-extreme learning machine; SC, specific conductance; S-ELM, sigmoid-extreme learning machine; SHr, sunshine hour; SR, solar radiation; SO4 -2, sulfate; SiO2, Silicon; SO2,
مقاله انگلیسی
6 Cryptographic system for data applications, in the context of internet of things
سیستم رمزنگاری برای برنامه های داده ، در متن اینترنت اشیاء-2019
With each passing day, Internet of Things (IoT), has the potential to transform our society to a more dig- ital way. In this paper, a cryptographic system is proposed, which has been designed and implemented, following the IoT optimized technologies. As the benefits of IoT are numerous, the need for a privacy platform is more than necessary to be developed. This work aims to demonstrate this by, firstly, imple- menting efficient and flexible, the fundamentals primitives of cryptography and privacy. Secondly, this is achieved, by introducing applied cryptography, in a more interactive and flexible approach. The proposed system and the incorporation of this platform is scrutinized. In the context of this work, an application of symmetric cryptography is introduced, based on the Advanced Encryption Standard (AES) in Electronic Code Book (ECB), Cipher Block Chaining (CBC) and Counter (CTR) modes of operation, for both encryption and decryption of texts, images and electronic data applications. In addition two other security schemes are supported by the proposed system: AES Galois/Counter Mode (GCM) and AES Galois Message Authen- tication Code (GMAC). The GCM proposed integration, in an authentication scheme, designed to provide authenticity and confidentiality, at the same time. On the other hand, GMAC, can be applied as message authentication code. Both operations, are optimized in sense of implementation resources, since the ma- jor cost is targeted to AES core. In addition, based on the integrated hardware modules, user registration and validation is proposed and implemented, with no additional cost, and with no performance penalty. Furthermore, two factor authentication has been designed and proposed, based on One Time Passwords (OTP), which can been produced with a random procedure. After these, a reference to the security lev- els, as regards to the communication between the IoT layers of the architecture, is presented. IoT hard- ware platforms are facing lack of security level and this brings the opportunity to use advanced security mechanisms. Implementation comparison results emphasize the importance of testing and measuring the performance of the alternative encryption algorithms, supported by hardware platforms.
Keywords: Internet of things (IoT) | AES | UDOO Neo board | GCM | GMAC | One time passwords (OTP) | Two factor authentication | Security system
مقاله انگلیسی
7 Distributed probability of slope failure in Thailand under climate change
احتمال توزیع شده شکست شیب در تایلند تحت تغییرات آب و هوایی-2018
Landslides are more widespread compared to any other geological hazards in Thailand. The steep slope and high elevation areas have more potential for landslide hazards. However, weather extremes, particularly extreme rainfall, play a major role in the occurrence of landslides in Thailand. The objective of the present study is to analyze the changes in the probability of landslide occurrences in Thailand due to climate change. For this purpose, probabilistic landslide hazard maps for extreme rainfall values for 5-, 10-, 50-, and 100-year return periods are developed for historical and future climatic conditions, derived from 10 global climate models (GCMs) under two representative concentration pathway (RCP) scenarios, namely, RCP 4.5 and RCP 8.5. The results reveal that the 5-year return period extreme rainfall amount will reach 200 mm/month in the eastern and southern provinces for RCP 4.5 and the northwestern, eastern, and southern provinces for RCP 8.5. The increase in extreme rainfall will cause a sharp increase in the landslide probability in Thailand, except in low altitude regions. The probability of 100-year return period landslide will increase by 90% in 40% and 80% of the areas in Thailand under RCP 4.5 and RCP 8.5, respectively. It is expected that the landslide hazard maps developed in this study will help policy makers take necessary measures to mitigate increasing landslide events due to climate change.
keywords: Climate scenarios |Extreme rainfall |Global circulation models |Landslide |Thailand
مقاله انگلیسی
8 A scalable parallel algorithm for atmospheric general circulation models on a multi-core cluster
یک الگوریتم موازی مقیاس پذیر برای مدل های گردشی کلی جوی در یک خوشه چند هسته ای-2017
High-performance computing of atmospheric general circulation models (AGCMs) has been receiving increasing attention in earth science research. However, when scaling to large-scale multi-core computing, the parallelization of an AGCM which demands fast parallel computing for long-time integration or climate simulation becomes extremely challenging due to its inner complex numerical calculation. The previous Institute of Atmospheric Physics of the Chinese Academy of Sciences Atmospheric General Circulation Model version 4.0 (IAP AGCM4.0) with one-dimensional domain decomposition can only run on dozens of CPU cores, so the paper proposes a two-dimensional domain decomposition parallel algorithm for it. In the parallel implementation of the IAP AGCM4.0, its dynamical core utilizes a hybrid form of latitude/longitude decomposition and vertical direction/longitude circle direction decomposition. Through experiments on a multi-core cluster, we confirmed that our algorithm is efficient and scalable. The parallel efficiency of the IAP AGCM4.0 can reach up to 50.88% on 512 CPU cores, and the IAP AGCM4.0 can be run long-term simulations for climate change research.
Keywords: High performance computing | Parallel algorithm | Domain decomposition | Atmospheric general circulation model
مقاله انگلیسی
9 بررسی نتایج آب و هوای منطقه ای با مدل سیستم خبره مبتنی بر وب
سال انتشار: 2012 - تعداد صفحات فایل pdf انگلیسی: 7 - تعداد صفحات فایل doc فارسی: 13
سیستم تأیید با هدف نظارت بر کیفیت پیش بینی آب و هوا در طول زمان به وجود آمده است. سیستم تأیید با مقایسه بین نقاط قوت و ضعف پیش بینی های موجود با کیفیت پیش بینی های مختلف انجام شده دیگر ما را در انجام یک پیش بینی با کیفیت مناسب یاری می کند. به این ترتیب سیستم های مبتنی بروب به وجود آمده که برای تأیید نتایج حاصل از پیش بینی که توسط مرکز بین المللی فیزیک مدل آب وهوای منطقه V4 برای کشور ترکیه تولید شده است. پیش بینی ها و تحلیل کران می توانند داده ها را در زمان واقعی (در هر زمان) با این سیستم مبتنی بروب تجزیه نمایند. در این مطالعه مدل هایی که عملکرد بالایی داشته اند توسط ULAKBIM شبکه مرکز محاسبات بدست آمده است. نتایج حاصل با توجه به مقایسه مدل وارزش ایستگاهها بدست آمده و قابل مشاهده است.
بنابراین مدل ارزش شبکه با استفاده از نزدیک ترین همسایه (K-NN) (یروگزیما) روش درج به ایستگاه منتقل می شود. این فرآیند در ادبیات هواشناسی به عنوان شبکه به نقطه نامیده می شود. در روش تأیید پیش بینی متغیرها پیوسته مورد استفاده قرار می گیرند تا اینکه بررسی شود. پیش بینی های انجام شده با آن چیزی که مشاهده می شود یکی است. برخی از روشهای تأیید عبارتند از متوسط خطا، متوسط خطای مطلق و میانگین مربع خطا، برای اعتبار سنجی محاسبه می شود. نتایج تأیید به صورت جدول و گرافیک بر روی سیستم های مبتنی بروب است که توسط PHP نشان داده می شود. (پیش پردازنده ابر متن: PHP)
کلمات کلیدی: سیستم تایید کارشناس | مدل آب و هوا | شبکه برای تایید نقطه | regcm | فارغ التحصیلان
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