Defect Pool Numerical Model in Amorphous Semiconductor Device Modeling Program

Програма моделювання аморфних напівпровідникових приладів (ASDMP), розроблена професором P. Chatterjee і широко підтверджена експериментальними результатами, є детальною програмою, де рівняння Пуассона і рівняння безперервності електронів і дірок розв’язуються одночасно без жодного спрощення. Вона враховує кінетику захоплення і рекомбінації через стани у забороненій зоні. У цій програмі щільність станів моделюється за допомогою стандартної моделі (SM). Така модель описує дефекти двома гаусіанами поблизу центра забороненої зони та двома хвостами, експоненціально розподіленими за енергією, і припускає, що щільність станів однорідна у просторі. Defect pool model (DPM) є вдосконаленою моделлю формування дефектів у гідрогенізованому аморфному кремнії на основі ідеї, що сітка невпорядкованих атомів a-Si:H має великий спектр локальних середовищ, в яких може бути сформований дефект. Таким чином, ці дефекти вибирають місця, де їх енергія утворення мінімальна, і це стає можливим з рухом водню.Використовуючи підхід до опису дефектів, ми розробили чисельну DPM і застосували її у ASDMP при термодинамічній рівновазі. Ми використали ASDMP, щоб отримати щільність станів у кожній позиції сонячного елемента на основі стандартної структури p-i-n. Показано вплив допінгу на концентрацію дефектів та досліджено вплив положення рівня Фермі на розподіл щільності станів. Ми визнали використання ASDMP ключовим результатом того, що негативно заряджені дефекти в матеріалі n-типу розташовані нижче за енергією, ніж позитивно заряджені дефекти в матеріалі p-типу, навіть якщо енергія кореляції позитивна.Ми розрахували електричне поле і діаграми смуг при термодинамічній рівновазі як з DPM, так і з SM. Ми показали, що електричне поле, отримане від DPM, сильніше поблизу інтерфейсів і нижче в об'ємі, де діаграми смуг більш плоскі. Така поведінка електричного поля, розрахованого за даною моделлю, підкреслюється зі збільшенням нахилу хвостів валентної зони.Amorphous Semiconductor Device Modeling Program (ASDMP), developed by Professor P. Chatterjee and widely validated by experimental results, is a detailed program where the Poisson’s equation and the electron and hole continuity equations are simultaneously solved without any simplifying assumption. It takes into account the trapping and recombination kinetic through the gap states. In this program, the density of states is modeled using the standard model (SM). Such a model describes the defects by two Gaussians near the center of the gap and two tails exponentially distributed in energy, and assumes the density of states homogenous in space. The defect pool model (DPM) is an improved model for defect formation in hydrogenated amorphous silicon based on the idea that the a-Si:H network has a large spectrum of local environments at which a defect could be formed. So, these defects choose the sits where their formation energy is minimal and this becomes possible with hydrogen motion. Using the defect pool approach, we have developed a numerical DPM and inserted it in ASDMP at thermodynamic equilibrium. We have used ASDMP to get the density of states in each position of a solar cell based on a standard p-i-n structure. We have shown the effect of doping on defect concentration and studied the impact of the position of Fermi level on the distribution of the density of states. We recognized using ASDMP the key result that negatively charged defects in n-type material are situated lower in energy than positively charged defects in p-type material even when the correlation energy is positive. We calculated the electric field and the band diagrams at thermodynamic equilibrium both with the DPM and the SM. We showed that the electric field obtained from the DPM is stronger near the interfaces and lower in the bulk where the band diagrams are flatter. This behavior of the electric field calculated with this model is accentuated with the increase of the slope of the valence band tails

A new T-S fuzzy model predictive control for nonlinear processes

Abstract: In this paper, a novel fuzzy Generalized Predictive Control (GPC) is proposed for discrete-time nonlinear systems via Takagi-Sugeno system based Kernel Ridge Regression (TS-KRR). The TS-KRR strategy approximates the unknown nonlinear systems by learning the Takagi-Sugeno (TS) fuzzy parameters from the input-output data. Two main steps are required to construct the TS-KRR: the first step is to use a clustering algorithm such as the clustering based Particle Swarm Optimization (PSO) algorithm that separates the input data into clusters and obtains the antecedent TS fuzzy model parameters. In the second step, the consequent TS fuzzy parameters are obtained using a Kernel ridge regression algorithm. Furthermore, the TS based predictive control is created by integrating the TS-KRR into the Generalized Predictive Controller. Next, an adaptive, online, version of TS-KRR is proposed and integrated with the GPC controller resulting an efficient adaptive fuzzy generalized predictive control methodology that can deal with most of the industrial plants and has the ability to deal with disturbances and variations of the model parameters. In the adaptive TS-KRR algorithm, the antecedent parameters are initialized with a simple K-means algorithm and updated using a simple gradient algorithm. Then, the consequent parameters are obtained using the sliding-window Kernel Recursive Least squares (KRLS) algorithm. Finally, two nonlinear systems: A surge tank and Continuous Stirred Tank Reactor (CSTR) systems were used to investigate the performance of the new adaptive TS-KRR GPC controller. Furthermore, the results obtained by the adaptive TS-KRR GPC controller were compared with two other controllers. The numerical results demonstrate the reliability of the proposed adaptive TS-KRR GPC method for discrete-time nonlinear systems

Uniaxial Tensile Stress-Strain Relationships of RC Elements Strengthened with FRP Sheets

The shear behavior of fiber-reinforced-polymer–strengthened reinforced concrete (FRP-strengthened RC) members is not fully developed and accurately predicted because of the lack of accurate constitutive laws for the components of the composite members. This paper presents experimental and analytical investigations of tensile stress-strain relationships of concrete and steel in FRP-strengthened RC members. These stress-strain relationships are required in formulations of softened truss models to predict the shear behavior of the FRP-strengthened RC element. Thirteen full-scale FRP-strengthened RC prismatic specimens with different FRP reinforcement ratios, steel reinforcement ratios, and FRP wrapping schemes were tested under uniaxial tension loading. The results show that the tensile behavior of the concrete and steel is altered because of the externally bonded FRP sheets. Modified constitutive laws are proposed and incorporated in the softened membrane model (SMM) to demonstrate through two tests the behavior of FRP-strengthened RC element subjected to pure shear. Moreover, crack spacing and crack width were studied and compared with existing code provisions

Influence of Fiber-Reinforced Polymer Sheets on the Constitutive Relationships of Reinforced Concrete Elements

Fiber-reinforced polymer (FRP) started to find its way as an economical alternative material in civil engineering in the early 1970s. The behavior and failure modes for FRP composite structures were studied through extensive experimental and analytical investigations. Although research related to the flexural behavior of FRP-strengthened elements has reached a mature phase, studies related to FRP shear strengthening are less advanced. In all proposed models to predict shear capacity, the constitutive behaviors of concrete and FRP are described independently. The true behavior, however, should account for the high level of interaction between the two materials. Constitutive relations for FRP-strengthened reinforced concrete (RC) elements should provide a better understanding of the shear behavior of the composite structure. To generate these relations, large-scale tests of a series of FRP-strengthened RC panel elements subjected to pure shear were conducted. This paper presents the results of the test program and the calibration of the parameters of the constitutive model. These constitutive laws could easily be implemented in finite-element models to predict the behavior of externally bonded FRP-strengthened beams. The focus in this work is on elements failing because of concrete crushing and not because of FRP debonding. The newly developed model provides a good level of accuracy when compared with experimental results

OPTIMAL SIZING OF A HYBRID PHOTOVOLTAIC/WIND SYSTEM SUPPLYING A DESALINATION UNIT

This work presents the dimensioning of a wind-photovoltaic hybrid system for the supply of a seawater desalination plant (reverse osmosis desalination) located in Honaïne in the Tlemcen coastal region of Algeria. The plant has a production capacity of 200,000 m3 /day and supplies potable water for a population of about 555,000 people (the plant's energy demand is 1,825 MW). The main idea is to present a method for sizing and optimizing a hybrid system by introducing two scenarios: the first scenario treats the operation of the plant under good weather conditions. The second one introduces the notion of the worst month (poor weather conditions). For it, we developed a calculation code (Programming under the MATLAB environment) that allowed us to determine the size and optimization of the system, as well as the optimal technical and economic configuration (numbers of photovoltaic panels, wind turbines and batteries), as well as the total cost. The results obtained show on the one hand: the complementarity of the two scenarios, which allows a better reliability of the system, and this by using a number well defined of panels, wind turbines and batteries to ensure the long-term operation of the plant. On the other hand, the use of the hybrid system has allowed us to obtain a 51.46% benefit compared to fossil fuels, which gives the proposed study an important reliability, since it offers a very advantageous benefit in terms of cost and efficiency

Behavior of the parameters of microcrystalline silicon TFTs under mechanical strain

International audienceN-type and P-type microcrystalline silicon top-gate TFTs, processed directly on PEN plastic substrate at maximum temperature of 180 °C, were mechanically stressed. These TFTs were bent by different curvature radii varying between infinite (flat) and 0.5 cm. The tensile stress increases the electron mobility and the compressive stress decreases it. The tensile stress decreases the threshold voltage of N-type TFTs while the compressive stress increases it. These trends are inversed if the type of stress changes OR the type of TFTs changes. The total behavior under mechanical stress is exactly similar to that of single crystalline silicon MOSFETs in nano-scale technologies (90, 65, 45, 32 nm), where nano-scale stress is introduced in the goal to engineer the electrical parameters. The similarity originates from the microcrystalline silicon active layer that behaves like single crystalline silicon even if the stress effects are softened by the grain boundaries and the multiple crystalline orientations of the grains

Rubble Pile Characterization Model

Rubble piles created following the collapse of a building in a combat situation can significantly impact mission accomplishment, particularly in the area of movement and maneuver. Rubble characteristics must be known, for example, in order to predict the ability of a vehicle to override the collateral damage from weapon effects in urban areas. Two types of models are developed: a first-order model and a first-principles-based model. In both models, we assume complete rubblization of the building and develop a rubble profile model using the size and composition of the collapsed structure to predict the rubble volume. In both cases, this profile model includes the size of the footprint area surrounding the original building assuming that the rubble is free to expand horizontally as well as the resulting height of such a rubble pile. Empirical data is now needed to verify the predictive capabilities of these models

Intercropping Promotes the Ability of Legume and Cereal to Facilitate Phosphorus and Nitrogen Acquisition through Root- Induced Processes

Intercropping of cereal and legume can improve the use of resources for crop growth compared to cropping system. An increase in soil phosphorus (P) and nitrogen (N) acquisition by root-induced biochemical changes of intercropped species has been reported as key processes of facilitation and complementarily between both intercropping legumes and cereals. Indeed, the functional facilitation prevails over interspecific competition under nutrients limiting for crop growth. Results showed that P availability significantly increased in the rhizosphere of both species, especially in intercropping under the P-deficient soil conditions. This increase was associated with high efficiency efficiency in use of rhizobial, plant growth and resource use efficiency as indicated by higher land equivalent ratio (LER) and N nutrition index. In addition, the rhizosphere P availability and nodule biomass were positively correlated (r2 = 0.71**, and r2 = 0.62**) in the intercropped common bean grown at P-deficient soil. The increased P availability presumably improved biomass and yield in intercropping, although it mainly enhanced intercropped maize grain yield. Exploiting belowground parameters in a legume-cereal intercropping is likely necessary to maximize rhizosphere-interspecific interactions as a strategy to improve the symbiotic rhizobial efficiency and microbial activities, as a result of root-induced pH and N availability changes under low P soils