• International Journal of Aeronautical and Space Sciences
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• v.16 no.3
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• pp.370-379
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• 2015

Handling constantly evolving configurations of aircraft can be inefficient and frustrating to design engineers, especially true in the early design phase when many design parameters are changeable throughout trade-off studies. In this paper, a physics-based design framework using parametric modeling is introduced, which is designated as DIAMOND/AIRCRAFT and developed for structural design of transport aircraft in the conceptual and preliminary design phase. DIAMOND/AIRCRAFT can relieve the burden of labor-intensive and time-consuming configuration changes with powerful parametric modeling techniques that can manipulate ever-changing geometric parameters for external layout of design alternatives. Furthermore, the design framework is capable of generating FE model in an automated fashion based on the internal structural layout, basically a set of design parameters describing the structural members in terms of their physical properties such as location, spacing and quantities. The design framework performs structural sizing using the FE model including both primary and secondary structural levels. This physics-based approach improves the accuracy of weight estimation significantly as compared with empirical methods. In this study, combining a physics-based model with parameter modeling techniques delivers a high-fidelity design framework, remarkably expediting otherwise slow and tedious design process of the early design phase.

• Journal of Astronomy and Space Sciences
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• v.40 no.1
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• pp.11-18
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• 2023

The ionosphere is one of the key components of the near-Earth's space environment and has a practical consequence to the human society as a nearest region of the space environment to the Earth. Therefore, it becomes essential to specify and forecast the state of the ionosphere using both the observations and numerical models. In particular, numerical modeling of the ionosphere is a prerequisite not only for better understanding of the physical processes occurring within the ionosphere but also for the specification and forecast of the space weather. There are several approaches for modeling the ionosphere, including data-based empirical modeling, physics-based theoretical modeling and data assimilation modeling. In this review, these three types of the ionospheric model are briefly introduced with recently available models. And among those approaches, fundamental aspects of the physics-based ionospheric model will be described using the basic equations governing the mid-latitude ionosphere. Then a numerical solution of the equations will be discussed with required boundary conditions.

• Journal of Korea Multimedia Society
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• v.12 no.6
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• pp.842-855
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• 2009

We present a physics-based blending method for the second order algebraic implicit surface. Unlike other traditional blending techniques, the proposed method avoids complex mathematical operations and unwanted artifacts like bulge, which have highly limited the application of the second order algebraic implicit surface as a modeling primitive in spite of lots of its excellent properties. Instead, the proposed method provides the designer with flexibility to control the shapes of the blending surface on interactive basis; the designer can check and design the shape of blending surfaces accurately by simply adjusting several physics parameter in real time, which was impossible in the traditional blending methods. In the later parts of this paper, several results are also presented.

• Geomechanics and Engineering
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• v.13 no.1
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• pp.99-117
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• 2017

Rock physics modeling of sandstone reservoir from gas fields of Krishna-Godavari basin represents the link between reservoir parameters and seismic properties. The rock physics diagnostic models such as contact cement, constant cement and friable sand are chosen to characterize reservoir sands of two wells in this basin. Cementation is affected by the grain sorting and cement coating on the surface of the grain. The models show that the reservoir sands in two wells under examination have varying cementation from 2 to more than 6%. Distinct and separate velocity-porosity and elastic moduli-porosity trends are observed for reservoir zones of two wells. A methodology is adopted for generation of Rock Physics Template (RPT) based on fluid replacement modeling for Raghavapuram Shale and Gollapalli Sandstones of Early Cretaceous. The ratio of P-wave velocity to S-wave velocity (Vp/Vs) and P-impedance template, generated for this above formations is able to detect shale, brine sand and gas sand with varying water saturation and porosity from wells in the Endamuru and Suryaraopeta gas fields having same shallow marine depositional characters. This RPT predicted detection of water and gas sands are matched well with conventional neutron-density cross plot analysis.

• Journal of Soil and Groundwater Environment
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• v.22 no.6
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• pp.66-73
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• 2017

Empirical erosion models like Universal Soil Loss Equation (USLE) models have been widely used to make spatially distributed soil erosion vulnerability maps. Even if the models detect vulnerable sites relatively well utilizing big data related to climate, geography, geology, land use, etc within study domains, they do not adequately describe the physical process of soil erosion on the ground surface caused by rainfall or overland flow. In other words, such models are still powerful tools to distinguish the erosion-prone areas at large scale, but physics-based models are necessary to better analyze soil erosion and deposition as well as the eroded particle transport. In this study a physics-based soil erosion modeling system was developed to produce both runoff and sediment yield time series at watershed scale and reflect them in the erosion and deposition maps. The developed modeling system consists of 3 sub-systems: rainfall pre-processor, geography pre-processor, and main modeling processor. For modeling system validation, we applied the system for various erosion cases, in particular, rainfall-runoff-sediment yield simulation and estimation of probable maximum sediment (PMS) correlated with probable maximum rainfall (PMP). The system provided acceptable performances of both applications.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.601-602
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• 2006

A physics-based equivalent circuit model for LTCC Helical type Inductors is presented. All of the electromagnetic couplings between conductors are included in the model and the number of optimized parameters is minimized. The model can predict the measured results upto 12 GHz.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2006.11a
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• pp.299-302
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• 2006

We present an innovative means of numerically treating interfaces associated with chemically active energetic materials. Recent advances in wave tracking technique based on the Ghost Fluid Concept is extended to handle multi-material multi-phase interfaces associated with chemical environment associated with explosion. We show several work-in-progress applications of our code, including the impact problems involving both energetic and inert elements. Accurate modeling of the equation of state and the constitutive relations are also discussed

• Journal of Power Electronics
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• v.19 no.2
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• pp.519-528
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• 2019

The unified power quality conditioner (UPQC) is an effective custom power device that is used at the point of common coupling to protect loads from voltage and current-related PQ issues. Currently, most researchers have studied series unit and parallel unit models and an idealized transformer model. However, the interactions of the series and parallel converters in AC-link are difficult to analyze. This study utilizes an equivalent transformer model to accomplish an electric connection of series and parallel converters in the AC-link and to establishes a precise unified mathematical model of the UPQC. The strong coupling interactions of series and parallel units are analyzed, and they show a remarkable dependence on the excitation impedance of transformers. Afterward, a feed-forward decoupling method based on a unified model that contains the uncertainty components of the load impedance is applied. Thus, this study presents an adaptive method to estimate load impedance. Furthermore, simulation and experimental results verify the accuracy of the proposed modeling and decoupling algorithm.

• Advances in nano research
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• v.8 no.2
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• pp.135-148
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• 2020

The incorporation of carbon nanotubes in a polymer matrix makes it possible to obtain nanocomposite materials with exceptional properties. It's in this scientific background that this work was based. There are several theories that deal with the behavior of plates, in this research based on the Mindlin-Reissner theory that takes into account the transversal shear effect, for analysis of the critical buckling load of a reinforced polymer plate with parabolic distribution of carbon nanotubes. The equations of the model are derived and the critical loads of linear and parabolic distribution of carbon nanotubes are obtained. With different disposition of nanotubes of carbon in the polymer matrix, the effects of different parameters such as the volume fractions, the plate geometric ratios and the number of modes on the critical load buckling are analysed and discussed. The results show that the critical buckling load of parabolic distribution is larger than the linear distribution. This variation is attributed to the concentration of reinforcement (CNTs) at the top and bottom faces for the X-CNT type which make the plate more rigid against buckling.

• ETRI Journal
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• v.32 no.4
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• pp.530-539
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• 2010

As the conventional silicon metal-oxide-semiconductor field-effect transistor (MOSFET) approaches its scaling limits, quantum mechanical effects are expected to become more and more important. Accurate quantum transport simulators are required to explore the essential device physics as a design aid. However, because of the complexity of the analysis, it has been necessary to simulate the quantum mechanical model with high speed and accuracy. In this paper, the modeling of double gate MOSFET based on an adaptive neuro-fuzzy inference system (ANFIS) is presented. The ANFIS model reduces the computational time while keeping the accuracy of physics-based models, like non-equilibrium Green's function formalism. Finally, we import the ANFIS model into the circuit simulator software as a subcircuit. The results show that the compact model based on ANFIS is an efficient tool for the simulation of nanoscale circuits.