Statistics of Voltage Processes in Random Environment

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Mircea Grigoriu
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Dynamical Systems ◽  
Random Environment ◽  
Energy Demand ◽  
Output Voltage ◽  
Forcing Functions

Abstract A method is developed to characterize the performance of voltage processes X(t) harvested from primary-absorber dynamical systems subjected to Gaussian forcing functions. The method is based on properties of the Slepian model of X(t) and Monte Carlo simulation. Statistics are calculated for excursions of X(t) above levels which can be related to energy demand. The duration and the area of these excursions are used as metrics for the voltage process. Their statistics depend on the topology and the parameters of primary-absorber dynamical systems, which can be optimized to maximize the output voltage.

scholarly journals Integration of Regression Analysis and Monte Carlo Simulation for Probabilistic Energy Policy Guidelines in Pakistan

Resources ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 88
Author(s):  
Zaman Sajid ◽  
Asma Javaid ◽  
Muhammad Kashif Khan ◽  
Hamad Sadiq ◽  
Usman Hamid
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Energy Policy ◽  
Energy Demand ◽  
Sustainable Energy ◽  
Energy Resource ◽  
Demand And Supply ◽  
Energy Profiles ◽  
Trade Offs ◽  
Guidelines And Recommendations

Forecasting energy demand and supply is the most crucial concern for energy policymakers. However, forecasting may introduce uncertainty in the energy model, and an energy policy based on an uncertain model could be misleading. Without certainty in energy data, investors cannot quantify risk and trade-offs, which are compulsory for investments in energy projects. In this work, the energy policies of Pakistan are taken as a case study, and flaws in its energy policymaking are identified. A novel probabilistic model integrated with curve fitting methods was proposed and was applied to 17 different energy demand and supply variables. Monte Carlo simulation (MCS) was performed to develop probabilistic energy profiles for each year from 2017 to 2050. Results show that the forecasted energy supply of Pakistan in the years 2025 and 2050 would be 70.69 MTOE and 131.65 MTOE, respectively. The probabilistic analysis showed that there is 14% and 6% uncertainty in achieving these targets. The research shows the expected energy consumption of 70.33 MTOE and 189.48 MTOE in 2025 and 2050, respectively, indicating uncertainties of 65% and 31%. Based on the results, eight energy policy guidelines and recommendations are provided for sustainable energy resource management. This study recommends developing a robust and sustainable energy policy for Pakistan with the help of transparent governance.

scholarly journals A CMOS PSR Enhancer with 87.3 mV PVT-Insensitive Dropout Voltage for Sensor Circuits

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 7856
Author(s):  
Jianyu Zhang ◽  
Pak Kwong Chan
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Output Voltage ◽  
Supply Voltage ◽  
Absolute Temperature ◽  
Voltage Reference ◽  
Process Technology ◽  
Operation Condition ◽  
Worst Case ◽  
Operation Temperature

A new power supply rejection (PSR) based enhancer with small and stable dropout voltage is presented in this work. It is implemented using TSMC-40 nm process technology and powered by 1.2 V supply voltage. A number of circuit techniques are proposed in this work. These include the temperature compensation for Level-Shifted Flipped Voltage Follower (LSFVF) and the Complementary-To-Absolute Temperature (CTAT) current reference. The typical output voltage and dropout voltage of the enhancer is 1.1127 V and 87.3 mV, respectively. The Monte-Carlo simulation of this output voltage yields a mean T.C. of 29.4 ppm/°C from −20 °C and 80 °C. Besides, the dropout voltage has been verified with good immunity against Process, Temperature and Process (PVT) variation through the worst-case simulation. Consuming only 4.75 μA, the circuit can drive load up to 500 μA to yield additional PSR improvement of 36 dB and 20 dB of PSR at 1 Hz and 1 MHz, respectively for the sensor circuit of interest. This is demonstrated through the application of an enhancer on the instrumentation Differential Difference Amplifier (DDA) for sensing floating bridge sensor signal. The comparative Monte-Carlo simulation results on a respective DDA circuit have revealed that the process sensitivity of output voltage of this work has achieved 14 times reduction in transient metrics with respect to that of the conventional counterpart over the operation temperature range in typical operation condition. Due to simplicity without voltage reference and operational amplifier(s), low power and small consumption of supply voltage headroom, the proposed work is very useful for supply noise sensitive analog or sensor circuit applications.

scholarly journals simlandr: Simulation-Based Landscape Construction for Dynamical Systems

2021 ◽  
Author(s):  
Jingmeng Cui ◽  
Merlijn Olthof ◽  
Anna Lichtwarck-Aschoff ◽  
Tiejun Li ◽  
Fred Hasselman
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Dynamical Systems ◽  
Dynamic Systems ◽  
Model Simulation ◽  
Simulation Based ◽  
Generalized Potential ◽  
System States ◽  
The Stability ◽  
Potential Landscape

We present the simlandr package for R, which provides a set of tools for constructing potential landscapes for dynamic systems using Monte Carlo simulation. Potential landscapes can be used to quantify the stability of system states. While the canonical form of a potential function is defined for gradient systems, generalized potential functions can also be defined for non-gradient dynamical systems. Our method is based on the potential landscape definition by Wang, Xu, and Wang (2008), and can be used for a large variety of models. Using two multistable dynamical systems as examples, we illustrate how simlandr can be used for model simulation, landscape construction, and barrier height calculation.

Electron Scattering in Solids

1990 ◽  
Vol 48 (2) ◽  
pp. 4-5
Author(s):  
Ryuichi Shimizu ◽  
Ze-Jun Ding
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Angular Distribution ◽  
Elastic Scattering ◽  
Electron Scattering ◽  
Cross Sections ◽  
Expansion Method ◽  
Electron Excitation ◽  
Partial Wave Expansion ◽  
Backscattered Electrons

Monte Carlo simulation has been becoming most powerful tool to describe the electron scattering in solids, leading to more comprehensive understanding of the complicated mechanism of generation of various types of signals for microbeam analysis.The present paper proposes a practical model for the Monte Carlo simulation of scattering processes of a penetrating electron and the generation of the slow secondaries in solids. The model is based on the combined use of Gryzinski’s inner-shell electron excitation function and the dielectric function for taking into account the valence electron contribution in inelastic scattering processes, while the cross-sections derived by partial wave expansion method are used for describing elastic scattering processes. An improvement of the use of this elastic scattering cross-section can be seen in the success to describe the anisotropy of angular distribution of elastically backscattered electrons from Au in low energy region, shown in Fig.l. Fig.l(a) shows the elastic cross-sections of 600 eV electron for single Au-atom, clearly indicating that the angular distribution is no more smooth as expected from Rutherford scattering formula, but has the socalled lobes appearing at the large scattering angle.

Determination of Stoichiometry of GaAs Component in (Gaas)Ge Epitaxially Grown Thin Films by Electron Microprobe X-Ray Analysis

1990 ◽  
Vol 48 (2) ◽  
pp. 264-265
Author(s):  
D. R. Liu ◽  
S. S. Shinozaki ◽  
R. J. Baird
Keyword(s):  
Thin Film ◽  
Thin Films ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Compound Semiconductors ◽  
Energy Dispersive Analysis ◽  
X Ray ◽  
Metastable Alloys ◽  
Lower Voltage

The epitaxially grown (GaAs)Ge thin film has been arousing much interest because it is one of metastable alloys of III-V compound semiconductors with germanium and a possible candidate in optoelectronic applications. It is important to be able to accurately determine the composition of the film, particularly whether or not the GaAs component is in stoichiometry, but x-ray energy dispersive analysis (EDS) cannot meet this need. The thickness of the film is usually about 0.5-1.5 μm. If Kα peaks are used for quantification, the accelerating voltage must be more than 10 kV in order for these peaks to be excited. Under this voltage, the generation depth of x-ray photons approaches 1 μm, as evidenced by a Monte Carlo simulation and actual x-ray intensity measurement as discussed below. If a lower voltage is used to reduce the generation depth, their L peaks have to be used. But these L peaks actually are merged as one big hump simply because the atomic numbers of these three elements are relatively small and close together, and the EDS energy resolution is limited.

Sign in / Sign up

Export Citation Format

Share Document