Averaged Behavior Model of Current-Mode Buck Converters for Transient Power Noise Analysis

Accurate Evaluation and Simulation of Power Noise is Critical in the Development of Modern Electronic Devices. However, the Widely Used Target Impedance Fails to Predict the Low-Frequency Noise Generated in a Device Due to the Existence of the Dc–dc Converter, Whose Output Impedance Can Change under Different Loading Conditions. a Physical Circuit Model is Then Desired to Replicate the Behavior of a Voltage Regulator Module, and the Average Technique is an Efficient Method to Estimate the Noise of a Pulse Width-Modulated (PWM) Converter. with the Emergence of Converters with Adaptive On-Time (AOT) Controllers, More Complex Averaging Methods Are Required, But None of Them Supports Transient Simulation. a General, Efficient, and Accurate Modeling Technique is Presented in This Article, Whose Framework Supports Both Current-Mode PWM and AOT Controllers. in Addition, a Novel Two-Step Parameter Extraction Method is Proposed, Which Can Be Used to Evaluate the Equivalent Values of Internal Feedback Parameters of an Encrypted Simulation Model or from Measurement. the Modeling Method is Validated by Both Simulation and Measurement

Developing a robust geochemical and reactive transport model to evaluate possible sources of arsenic at the CO2 sequestration natural analog site in Chimayo, New Mexico

Migration of carbon dioxide (CO2) from deep storage formations into shallow drinking water aquifers is a possible system failure related to geologic CO2 sequestration. A CO2 leak may cause mineral precipitation/ dissolution reactions, changes in aqueous speciation, and alteration of pH and redox conditions leading to potential increases of trace metal concentrations above EPA National Primary Drinking Water Standards. In this study, the Chimayo site (NM) was examined for site-specific impacts of shallow groundwater interacting with CO2 from deep storage formations. Major ion and trace element chemistry for the site have been previously studied. This work focuses on arsenic (As), which is regulated by the EPA under the Safe Drinking Water Act and for which some wells in the Chimayo area have concentrations higher than the maximum contaminant level (MCL). Statistical analysis of the existing Chimayo groundwater data indicates that As is strongly correlated with trace metals U and Pb indicating that their source may be from the same deep subsurface water. Batch experiments and materials characterization, such as: X-ray diffraction (XRD), scanning electron microscopy (SEM), and synchrotron micro X-ray fluorescence (#2;-XRF), were used to identify As association with Fe-rich phases, such as clays or oxides, in the Chimayo sediments as the major factor controlling As fate in the subsurface. Batch laboratory experiments with Chimayo sediments and groundwater show that pH decreases as CO2 is introduced into the system and buffered by calcite. The introduction of CO2 causes an immediate increase in As solution concentration, which then decreases over time. A geochemical model was developed to simulate these batch experiments and successfully predicted the pH drop once CO2 was introduced into the experiment. In the model, sorption of As to illite, kaolinite and smectite through surface complexation proved to be the key reactions in simulating the drop in As concentration as a function of time in the batch experiments. Based on modeling, kaolinite precipitation is anticipated to occur during the experiment, which allows for additional sorption sites to form with time resulting in the slow decrease in As concentration. This mechanism can be viewed as trace metal “scavenging” due to sorption caused secondary mineral precipitation. Since deep geologic transport of these trace metals to the shallow subsurface by brine or CO2 intrusion is critical to assessing environmental impacts, the effective retardation of trace metal transport is an important parameter to estimate and it is dependent on multiple coupled reactions. At the field scale, As mobility is retarded due to the influence of sorption reactions, which can affect environmental performance assessment studies of a sequestration site

The effect of deep-case oxygen hardening on the tribological behaviour of a-C:H DLC coatings on Ti6Al4V alloy

Original article can be found at: http://www.sciencedirect.com/ Copyright Elsevier [Full text of this article is not available in the UHRA]A new duplex surface treatment combining the boost diffusion oxidation (BDO) treatment with amorphous hydrogenated diamond-like carbon hard coatings (BDO/a-C:H DLC) has been developed. Experiments results demonstrated that the BDO pre-treatment can effectively improve the scratch resistance and load bearing capacity of a-C:H DLC on Ti6Al4V. This is mainly because the hardened case in Ti6Al4V conferred by the BDO treatment can provide adequate mechanical support for the thin hard top carbon coating.Peer reviewe

A new model for simulating spring discharge recession and estimating effective porosity of karst aquifers

Quantitative analysis of recession curves of karst spring hydrographs is a vital tool for understanding karst hydrology and inferring hydraulic properties of karst aquifers. This paper presents a new model for simulating karst spring recession curves. The new model has the following characteristics: (1) the model considers two separate but hydraulically connected reservoirs: matrix reservoir and conduit reservoir; (2) the model separates karst spring hydrograph recession into three stages: conduit-drainage stage, mixed-drainage stage (with both conduit drainage and matrix drainage), and matrix-drainage stage; and (3) in the mixed-drainage stage, the model uses multiple conduit layers to present different levels of conduit development. The new model outperforms the classical Mangin model and the recently developed Fiorillo model for simulating observed discharge at the Madison Blue Spring located in northern Florida. This is attributed to the latter two characteristics of the new model. Based on the new model, a method is developed for estimating effective porosity of the matrix and conduit reservoirs for the three drainage stages. The estimated porosity values are consistent with measured matrix porosity at the study site and with estimated conduit porosity reported in literature. The new model for simulating karst spring hydrograph recession is mathematically general, and can be applied to a wide range of karst spring hydrographs to understand groundwater flow in karst aquifers. The limitations of the model are discussed at the end of this paper

Multiperspective Light Field Reconstruction Method via Transfer Reinforcement Learning

Compared with traditional imaging, the light field contains more comprehensive image information and higher image quality. However, the available data for light field reconstruction are limited, and the repeated calculation of data seriously affects the accuracy and the real-time performance of multiperspective light field reconstruction. To solve the problems, this paper proposes a multiperspective light field reconstruction method based on transfer reinforcement learning. Firstly, the similarity measurement model is established. According to the similarity threshold of the source domain and the target domain, the reinforcement learning model or the feature transfer learning model is autonomously selected. Secondly, the reinforcement learning model is established. The model uses multiagent (i.e., multiperspective) Q-learning to learn the feature set that is most similar to the target domain and the source domain and feeds it back to the source domain. This model increases the capacity of the source-domain samples and improves the accuracy of light field reconstruction. Finally, the feature transfer learning model is established. The model uses PCA to obtain the maximum embedding space of source-domain and target-domain features and maps similar features to a new space for label data migration. This model solves the problems of multiperspective data redundancy and repeated calculations and improves the real-time performance of maneuvering target recognition. Extensive experiments on PASCAL VOC datasets demonstrate the effectiveness of the proposed algorithm against the existing algorithms

An integrated assessment of the impact of precipitation and groundwater on vegetation growth in arid and semiarid areas

Increased demand for water resources together with the influence of climate change has degraded water conditions which support vegetation in many parts of the world, especially in arid and semiarid areas. This study develops an integrated framework to assess the impact of precipitation and groundwater on vegetation growth in the Xiliao River Plain of northern China. The integrated framework systematically combines remote sensing technology with water flow modeling in the vadose zone and field data analysis. The vegetation growth is quantitatively evaluated with the remote sensing data by the normalized difference vegetation index (NDVI) and the simulated plant water uptake rates. The correlations among precipitation, groundwater depth and NDVI are investigated using Pearson correlation equations. The results provide insights for understanding interactions between precipitation and groundwater and their contributions to vegetation growth. Strong correlations between groundwater depth, plant water uptake and NDVI are found in parts of the study area during a ten-year drought period. The numerical modeling results indicate that there is an increased correlation between the groundwater depth and vegetation growth and that groundwater significantly contributes to sustaining effective soil moisture for vegetation growth during the long drought period. Therefore, a decreasing groundwater table might pose a great threat to the survival of vegetation during a long drought period

Quantitative Analysis and Evaluation of Coal Mine Geological Structures Based on Fractal Theory

With the increasing depth of coal mining, the quantitative evaluation of the degree of geological structure development is becoming increasingly important for the control of mine water hazards in coal mining areas. Understanding the complexity of geological structure development can improve the safety and efficiency of coal production. At present, various evaluation indicators of the geological structure development cannot fully reflect the complexity of faults and folds, and the evaluation process is usually affected by subjective human factors. In this paper, the fractal dimension from fractal theory is used as the evaluation indicator to quantitatively analyze and evaluate the complexity of fault and fold structure in the mining area. To verify the evaluation results, the mathematical geology method is applied in an analysis of the trend surface of fault and fold networks. The results indicate that the fractal dimension can be applied for the quantitative analysis and evaluation of the complexity of fault and fold networks. In addition, the outcome of this work provides new insights into how to characterize the fault and fold structures of coal mining areas in northern China, and has some important implications to ensure the coal production safety