This document describes Snyder's synthetic unit hydrograph method. Snyder's method allows computation of key hydrograph characteristics using watershed properties. These include:
1. Lag time, which is related to watershed time of concentration based on length and slope.
2. Hydrograph duration, which is typically 1/5.5 of the lag time.
3. Peak discharge, which is related to watershed area, storage coefficient, and time parameters.
4. Other hydrograph properties like width can also be estimated using the peak discharge and empirical coefficients. The synthetic hydrograph provides an estimate of watershed runoff for both gauged and ungauged locations.
This document provides an overview of trigonometry unit 2, including:
1) Definitions of amplitude, frequency, period, and phase shift as they relate to graphing trigonometric functions.
2) Examples of applying these concepts to the functions y=4cos3x and y=-2sin2x.
3) Explanations of the inverse sine, cosine, and tangent functions using unit circle properties and examples.
This presentation summarizes key concepts related to hydrographs including:
1) A hydrograph shows the variation of discharge over time at a particular point in a river. It has three main components: the rising limb, peak, and recession curve.
2) Factors like area, slope, land use, and precipitation affect hydrograph shape.
3) A unit hydrograph represents the response of a watershed to 1 cm of direct runoff from rainfall of a given duration, and is used to estimate flood discharge from future rainfall.
4) Methods like superposition and S-curves are used to derive unit hydrographs from storm hydrographs and to estimate hydrographs for different rainfall scenarios.
This document discusses extending the ability of MadGraph to simulate multi-jet events for new physics searches at the LHC. It proposes dividing the MadGraph code into smaller pieces by color decomposition to allow compilation on standard PCs. Higher-order corrections are included by evaluating needed color flows and reweighting events. Results are shown for total cross sections and distributions of gluonic processes generated at leading order with MadGraph.
This document discusses seismic reflection acquisition, processing, and waveform analysis. It introduces key concepts like reflection coefficients, convolution, and how the earth acts as a filter on seismic energy. Examples are provided to illustrate convolution and how it is used to model seismic reflections within the earth. Key wave properties like amplitude, wavelength, velocity and their relationships are also defined. Homework problems at the end ask about wave properties and applications of seismic reflection and refraction methods.
Blind-Spectrum Non-uniform Sampling and its Application in Wideband Spectrum ...mravendi
This document proposes a method for blind-spectrum non-uniform sampling and its application in wideband spectrum sensing. It introduces a blind spectrum signal model and discusses parameters for the sampling method including the number of active bands (N), maximum frequency (fmax), and sampling parameters like the number of samples (L) and sampling pattern (C). It then describes two approaches for spectral recovery from the non-uniform samples using subspace and nonlinear least squares methods. Simulation results demonstrate the method's ability to sense and reconstruct multi-band signals from a reduced set of samples. The document proposes applying this sampling approach to wideband spectrum sensing to lower the sampling rate requirement compared to traditional methods.
IAHR2015 - Towards time and space evolving extreme wind fields, nieuwkoop, de...Deltares
1) The document discusses methods for generating time and space evolving extreme wind fields to model hydraulic loads along water defenses over long return periods as required by Dutch law.
2) It recommends using a max-stable method involving extreme value analysis at each location, selecting storm periods, transforming to unit distributions, and lifting the storms to reproduce target return levels.
3) The lifted wind fields were validated against a 35-year hindcast for a case study area. Results found the lifted fields reproduced hydraulic loads similarly to the hindcast within confidence intervals. Further study of lifting assumptions was recommended.
This document proposes a modular beamforming architecture for ultrasound imaging that uses FPGA DSP cells to overcome limitations of previous designs. It interleaves the interpolation and coherent summation processes, reducing hardware resources. This allows implementing a 128-channel beamformer in a single FPGA, achieving flexibility like FPGAs but with lower power consumption like ASICs. The design is scalable, allowing a tradeoff between number of channels, time resolution, and resource usage.
This document describes Snyder's synthetic unit hydrograph method. Snyder's method allows computation of key hydrograph characteristics using watershed properties. These include:
1. Lag time, which is related to watershed time of concentration based on length and slope.
2. Hydrograph duration, which is typically 1/5.5 of the lag time.
3. Peak discharge, which is related to watershed area, storage coefficient, and time parameters.
4. Other hydrograph properties like width can also be estimated using the peak discharge and empirical coefficients. The synthetic hydrograph provides an estimate of watershed runoff for both gauged and ungauged locations.
This document provides an overview of trigonometry unit 2, including:
1) Definitions of amplitude, frequency, period, and phase shift as they relate to graphing trigonometric functions.
2) Examples of applying these concepts to the functions y=4cos3x and y=-2sin2x.
3) Explanations of the inverse sine, cosine, and tangent functions using unit circle properties and examples.
This presentation summarizes key concepts related to hydrographs including:
1) A hydrograph shows the variation of discharge over time at a particular point in a river. It has three main components: the rising limb, peak, and recession curve.
2) Factors like area, slope, land use, and precipitation affect hydrograph shape.
3) A unit hydrograph represents the response of a watershed to 1 cm of direct runoff from rainfall of a given duration, and is used to estimate flood discharge from future rainfall.
4) Methods like superposition and S-curves are used to derive unit hydrographs from storm hydrographs and to estimate hydrographs for different rainfall scenarios.
This document discusses extending the ability of MadGraph to simulate multi-jet events for new physics searches at the LHC. It proposes dividing the MadGraph code into smaller pieces by color decomposition to allow compilation on standard PCs. Higher-order corrections are included by evaluating needed color flows and reweighting events. Results are shown for total cross sections and distributions of gluonic processes generated at leading order with MadGraph.
This document discusses seismic reflection acquisition, processing, and waveform analysis. It introduces key concepts like reflection coefficients, convolution, and how the earth acts as a filter on seismic energy. Examples are provided to illustrate convolution and how it is used to model seismic reflections within the earth. Key wave properties like amplitude, wavelength, velocity and their relationships are also defined. Homework problems at the end ask about wave properties and applications of seismic reflection and refraction methods.
Blind-Spectrum Non-uniform Sampling and its Application in Wideband Spectrum ...mravendi
This document proposes a method for blind-spectrum non-uniform sampling and its application in wideband spectrum sensing. It introduces a blind spectrum signal model and discusses parameters for the sampling method including the number of active bands (N), maximum frequency (fmax), and sampling parameters like the number of samples (L) and sampling pattern (C). It then describes two approaches for spectral recovery from the non-uniform samples using subspace and nonlinear least squares methods. Simulation results demonstrate the method's ability to sense and reconstruct multi-band signals from a reduced set of samples. The document proposes applying this sampling approach to wideband spectrum sensing to lower the sampling rate requirement compared to traditional methods.
IAHR2015 - Towards time and space evolving extreme wind fields, nieuwkoop, de...Deltares
1) The document discusses methods for generating time and space evolving extreme wind fields to model hydraulic loads along water defenses over long return periods as required by Dutch law.
2) It recommends using a max-stable method involving extreme value analysis at each location, selecting storm periods, transforming to unit distributions, and lifting the storms to reproduce target return levels.
3) The lifted wind fields were validated against a 35-year hindcast for a case study area. Results found the lifted fields reproduced hydraulic loads similarly to the hindcast within confidence intervals. Further study of lifting assumptions was recommended.
This document proposes a modular beamforming architecture for ultrasound imaging that uses FPGA DSP cells to overcome limitations of previous designs. It interleaves the interpolation and coherent summation processes, reducing hardware resources. This allows implementing a 128-channel beamformer in a single FPGA, achieving flexibility like FPGAs but with lower power consumption like ASICs. The design is scalable, allowing a tradeoff between number of channels, time resolution, and resource usage.
The document discusses seismic data acquisition and processing for the Shaybah Field. Over 120 million seismic traces were recorded over an area of 1,100 square kilometers using over 100,000 shot points. Processing of the data lasted about 18 months and was carried out in-house by Saudi Aramco. The document also discusses various seismic data processing techniques including normal moveout correction, velocity analysis, muting, and static corrections.
This document describes how to derive a required time (T) unit hydrograph from a given time (D) unit hydrograph when T is not a multiple of D using the S-curve method. It explains that an S-curve hydrograph is generated by continuous, uniform effective rainfall and rises continuously in the shape of an S until equilibrium is reached. The ordinates of the S-curve can be calculated using the equation S(t) = U(t) + S(t-D), where S(t) is the ordinate of the S-curve at time t, U(t) is the ordinate of the given unit hydrograph at time t, and S(t-D) is the
Modeling and Querying Metadata in the Semantic Sensor Web: stRDF and stSPARQLKostis Kyzirakos
This document discusses modeling and querying metadata in the semantic sensor web using stRDF and stSPARQL. It introduces stRDF, an extension of RDF that uses linear constraints to represent spatial and temporal metadata. It also introduces stSPARQL, an extension of SPARQL with spatial and temporal query capabilities. The talk outlines the motivation, data model, query language, implementation details, and examples of querying sensor metadata and observations.
The remote sensing working group has investigated methodology for atmospheric remotesensing retrievals, which are mathematical and computational procedures for inferring the state of the atmosphere from remote sensing observations. Satellite data with fine spatial and temporal
resolution present opportunities to combine information across satellite pixels using spatiotemporal statistical modeling. We present examples of this approach at the process level of a hierarchical model, with a nonlinear radiative transfer model incorporated into the likelihood. In
this framework, we assess the impact of various statistical properties on the relative performance of a multi-pixel retrieval strategy versus an operational one-at-a-time approach. The prospect of adopting the approach is illustrated in the context of estimating atmospheric carbon dioxide concentration with data from NASA's Orbiting Carbon Observatory-2 (OCO-2).
This document presents an equation for calculating emission rates of NH3 using average concentration measurements and background levels. It describes the Backward-Lagrangian Stochastic method, which simulates NH3 transport from source to measurement location to predict the ratio of average concentration to emission rate. This method requires inputs like wind speed, direction, surface roughness, stability, measured concentrations and background levels.
Over a seven day period in August 2017 Hurricane Harvey brought extreme levels of rainfall to the Houston area, resulting in catastrophic flooding that caused loss of human life and damage to personal property and public infrastructure. In the wake of this event, there is growing interest in understanding the degree to which this event was unusual and estimating the probability of experiencing a similar event in other locations. Additionally, we investigate the degree to which the sea surface temperature in the Gulf of Mexico is associated with extreme precipitation in the US Gulf Coast. This talk addresses these issues through the development of an extreme value model.
We assume that the annual maximum precipitation values at Gulf Coast locations approximately follow the Generalized Extreme Value (GEV) distribution. Because the observed precipitation record in this region is relatively short, we borrow strength across spatial locations to improve GEV parameter estimates. We model the GEV parameters at US Gulf Coast locations using a multivariate spatial hierarchical model; for inference, a two-stage approach is utilized. Spatial
interpolation is used to estimate GEV parameters at unobserved locations, allowing us to characterize precipitation extremes throughout the region. Analysis indicates that Harvey was highly unusual as a seven
-day event, and that GoM SST seems to be more strongly linked to extreme precipitation in the Western part of
the region.
Joint CSI Estimation, Beamforming and Scheduling Design for Wideband Massive ...T. E. BOGALE
The document presents a new design for joint channel estimation, beamforming, and scheduling for wideband massive MIMO systems. It proposes using non-orthogonal pilots for channel estimation and a two-phase scheduling approach. Simulation results show the proposed design achieves higher total rates than conventional OFDM and performs better in dense multipath environments, especially with larger bandwidths and antenna arrays. An open issue discussed is comparing the proposed non-orthogonal pilot scheme to non-orthogonal multiple access techniques.
A first order hyperbolic framework for large strain computational computation...Jibran Haider
An explicit Total Lagrangian momentum-strains mixed formulation in the form of a system of first order hyperbolic conservation laws, has recently been published to overcome the shortcomings posed by the traditional second order displacement based formulation when using linear tetrahedral elements.
The formulation, where the linear momentum and the deformation gradient are treated as unknown variables, has been implemented within the cell centred finite volume environment in OpenFOAM. The numerical solutions have performed extremely well in bending dominated nearly incompressible scenarios without the appearance of any spurious pressure modes, yielding an equal order of convergence for velocities and stresses.
To have more insight into my research, please visit my website:
http://jibranhaider.weebly.com/
The presentation will be delivered by Thanh-Nguyen Ngo at the 14th Asia-Pacific Web Conference (APWeb) on April 12th, 2012 in Kunming, China.
Publication: http://bit.ly/yD18Vj
Abstract:
This paper presents a new approach to measuring similarity over massive time-series data. Our approach is built on two principles: one is to parallelize the large amount computation using a scalable cloud serving system, called TimeCloud. The another is to benet from the lter-and-renement approach for query processing, such that similarity computation is eciently performed over approximated data at the lter step, and then the following renement step measures precise similarities for only a small number of candidates resulted from the ltering. To this end, we establish a set of rm theoretical backgrounds, as well as techniques for processing kNN queries. Our experimental results suggest that the approach proposed is ecient and scalable.
The document discusses acoustic modeling techniques for underwater sound propagation. It provides an overview of several common modeling approaches, including ray theory models, normal mode models, multipath expansion models, fast field models, and parabolic equation models. It also discusses how these approaches relate to solving the acoustic wave equation and Helmholtz equation. The key steps of ray theory modeling are outlined, including derivation of the eikonal and transport equations from the Helmholtz equation.
Duval l 20140318_s-journee-signal-image_adaptive-multiple-complex-waveletsLaurent Duval
This document discusses using adaptive filtering in continuous wavelet frames to suppress multiple reflections in geophysical signals. It introduces the problem of multiple reflections obscuring deeper geological layers in seismic data. Adaptive filtering with approximate templates is challenging due to variations in primaries and multiples. Continuous, complex wavelet frames can simplify adaptive filtering by spreading noise and highlighting signal features in the time-scale domain. The document explores using wavelet frames to adaptively filter and subtract multiples from seismic data through morphing in the time-scale domain rather than time domain.
This document discusses methods for locating earthquakes based on analyzing arrival times of seismic phases at stations. Accurate event location is important for various applications but also challenging due to uncertainties from measurement errors, velocity model inaccuracies, and the non-linear nature of the problem. The document reviews classical methods like Geiger's linearized inversion and also discusses more advanced non-linear techniques and using multiple events to better constrain locations. It emphasizes picking higher quality phase arrival times and using reference ground truth events to validate new location methods and velocity models.
The document describes methodology for estimating the channel impulse response from acoustic signals transmitted during the SAVEX15 experiment. Stationary source experiments involved transmitting chirp and m-sequence signals from a fixed source location and receiving the signals on a vertical receiver array up to 5 km away. Matched filtering of the received signals with the transmitted source signals was used to estimate the time-varying channel impulse response, which characterizes how the underwater acoustic channel responds to any input signal.
Large strain solid dynamics in OpenFOAMJibran Haider
The document describes a numerical methodology for simulating large strain solid dynamics using OpenFOAM. It proposes using a total Lagrangian formulation and first-order conservation laws similar to computational fluid dynamics to model solid mechanics problems involving large deformations. A cell-centered finite volume method is used for spatial discretization along with Riemann solvers and linear reconstruction to capture fluxes. A two-stage Runge-Kutta scheme is employed for time integration. Results are presented demonstrating the method's ability to handle problems involving mesh convergence, enhanced reconstruction, highly nonlinear behavior, plasticity, contact, unstructured meshes, and complex geometries.
This document summarizes a large eddy simulation of flow around a sharp-edged surface-mounted cube. The simulation was performed using the Petsc-Fem code developed at CIMEC. The flow conditions matched published benchmarks, with a Reynolds number of 40,000. An upstream channel flow was first simulated to provide turbulent inflow conditions. The simulation results are analyzed to validate the LES implementation and identify areas for improving turbulence modeling.
This document presents Specformer, a novel Transformer-based spectral graph neural network. Specformer uses a Transformer to encode eigenvalues of the graph Laplacian into representations that capture magnitude and relative differences. It then applies self-attention to learn relationships between eigenvalues. Specformer decodes the eigenvalue representations using learnable bases to perform graph convolutions. Experiments show Specformer outperforms other GNNs on node and graph classification tasks and learns meaningful patterns in the graph spectrum.
Sparsity based Joint Direction-of-Arrival and Offset Frequency EstimatorJason Fernandes
- The document proposes a method to jointly estimate direction-of-arrival (DoA) and offset frequency of signals impinging on an antenna array using sparse representation.
- It builds on previous work by extending the estimation to include both spatial (DoA) and temporal (offset frequency) dimensions. This is done by constructing a joint dictionary as the Kronecker product of discrete spatial and temporal steering vector grids.
- Sparse recovery algorithms can then be applied to estimate the sparse coefficients and jointly infer the DoAs and offset frequencies of impinging signals from compressed measurements of the antenna array output over multiple time snapshots.
Development, Optimization, and Analysis of Cellular Automaton Algorithms to S...IRJET Journal
This document summarizes research on using cellular automaton algorithms to solve stochastic partial differential equations (SPDEs). It proposes a finite-difference method to approximate an SPDE modeling a random walk with angular diffusion. A Monte Carlo algorithm is also developed for comparison. Analysis finds a moderate correlation between the two methods, suggesting the finite-difference approach is reasonably accurate. It also identifies an inverse-square relationship between variables, linking to a foundational stochastic analysis concept. The research concludes the finite-difference method shows promise for approximating SPDEs while considering boundary conditions.
A FINITE ELEMENT PREDICTION MODEL WITH VARIABLE ELEMENT SIZES - KELLEYRichard. Kelley
This document describes a finite element prediction model that uses variable element sizes. The model uses the shallow water equations on a periodic channel with a constant Coriolis parameter. Initial tests were run using a uniform element size as well as abruptly and smoothly varying element sizes. Uniform elements showed good wave propagation but some noise, while varying elements generated more noise. The goal was to develop a model that allows high resolution where needed without discontinuities at element size changes.
History and Applications of Finite Element Analysis
Theory of Elasticity
Finite Element Equation of Bar element
Finite Element Equation of Truss element
Finite Element Equation of Beam element
Tutorial related to
Bar element
Beam element
Finite element simulation using ANSYS 15.0
Bar element
Truss element
Beam element
The document discusses seismic data acquisition and processing for the Shaybah Field. Over 120 million seismic traces were recorded over an area of 1,100 square kilometers using over 100,000 shot points. Processing of the data lasted about 18 months and was carried out in-house by Saudi Aramco. The document also discusses various seismic data processing techniques including normal moveout correction, velocity analysis, muting, and static corrections.
This document describes how to derive a required time (T) unit hydrograph from a given time (D) unit hydrograph when T is not a multiple of D using the S-curve method. It explains that an S-curve hydrograph is generated by continuous, uniform effective rainfall and rises continuously in the shape of an S until equilibrium is reached. The ordinates of the S-curve can be calculated using the equation S(t) = U(t) + S(t-D), where S(t) is the ordinate of the S-curve at time t, U(t) is the ordinate of the given unit hydrograph at time t, and S(t-D) is the
Modeling and Querying Metadata in the Semantic Sensor Web: stRDF and stSPARQLKostis Kyzirakos
This document discusses modeling and querying metadata in the semantic sensor web using stRDF and stSPARQL. It introduces stRDF, an extension of RDF that uses linear constraints to represent spatial and temporal metadata. It also introduces stSPARQL, an extension of SPARQL with spatial and temporal query capabilities. The talk outlines the motivation, data model, query language, implementation details, and examples of querying sensor metadata and observations.
The remote sensing working group has investigated methodology for atmospheric remotesensing retrievals, which are mathematical and computational procedures for inferring the state of the atmosphere from remote sensing observations. Satellite data with fine spatial and temporal
resolution present opportunities to combine information across satellite pixels using spatiotemporal statistical modeling. We present examples of this approach at the process level of a hierarchical model, with a nonlinear radiative transfer model incorporated into the likelihood. In
this framework, we assess the impact of various statistical properties on the relative performance of a multi-pixel retrieval strategy versus an operational one-at-a-time approach. The prospect of adopting the approach is illustrated in the context of estimating atmospheric carbon dioxide concentration with data from NASA's Orbiting Carbon Observatory-2 (OCO-2).
This document presents an equation for calculating emission rates of NH3 using average concentration measurements and background levels. It describes the Backward-Lagrangian Stochastic method, which simulates NH3 transport from source to measurement location to predict the ratio of average concentration to emission rate. This method requires inputs like wind speed, direction, surface roughness, stability, measured concentrations and background levels.
Over a seven day period in August 2017 Hurricane Harvey brought extreme levels of rainfall to the Houston area, resulting in catastrophic flooding that caused loss of human life and damage to personal property and public infrastructure. In the wake of this event, there is growing interest in understanding the degree to which this event was unusual and estimating the probability of experiencing a similar event in other locations. Additionally, we investigate the degree to which the sea surface temperature in the Gulf of Mexico is associated with extreme precipitation in the US Gulf Coast. This talk addresses these issues through the development of an extreme value model.
We assume that the annual maximum precipitation values at Gulf Coast locations approximately follow the Generalized Extreme Value (GEV) distribution. Because the observed precipitation record in this region is relatively short, we borrow strength across spatial locations to improve GEV parameter estimates. We model the GEV parameters at US Gulf Coast locations using a multivariate spatial hierarchical model; for inference, a two-stage approach is utilized. Spatial
interpolation is used to estimate GEV parameters at unobserved locations, allowing us to characterize precipitation extremes throughout the region. Analysis indicates that Harvey was highly unusual as a seven
-day event, and that GoM SST seems to be more strongly linked to extreme precipitation in the Western part of
the region.
Joint CSI Estimation, Beamforming and Scheduling Design for Wideband Massive ...T. E. BOGALE
The document presents a new design for joint channel estimation, beamforming, and scheduling for wideband massive MIMO systems. It proposes using non-orthogonal pilots for channel estimation and a two-phase scheduling approach. Simulation results show the proposed design achieves higher total rates than conventional OFDM and performs better in dense multipath environments, especially with larger bandwidths and antenna arrays. An open issue discussed is comparing the proposed non-orthogonal pilot scheme to non-orthogonal multiple access techniques.
A first order hyperbolic framework for large strain computational computation...Jibran Haider
An explicit Total Lagrangian momentum-strains mixed formulation in the form of a system of first order hyperbolic conservation laws, has recently been published to overcome the shortcomings posed by the traditional second order displacement based formulation when using linear tetrahedral elements.
The formulation, where the linear momentum and the deformation gradient are treated as unknown variables, has been implemented within the cell centred finite volume environment in OpenFOAM. The numerical solutions have performed extremely well in bending dominated nearly incompressible scenarios without the appearance of any spurious pressure modes, yielding an equal order of convergence for velocities and stresses.
To have more insight into my research, please visit my website:
http://jibranhaider.weebly.com/
The presentation will be delivered by Thanh-Nguyen Ngo at the 14th Asia-Pacific Web Conference (APWeb) on April 12th, 2012 in Kunming, China.
Publication: http://bit.ly/yD18Vj
Abstract:
This paper presents a new approach to measuring similarity over massive time-series data. Our approach is built on two principles: one is to parallelize the large amount computation using a scalable cloud serving system, called TimeCloud. The another is to benet from the lter-and-renement approach for query processing, such that similarity computation is eciently performed over approximated data at the lter step, and then the following renement step measures precise similarities for only a small number of candidates resulted from the ltering. To this end, we establish a set of rm theoretical backgrounds, as well as techniques for processing kNN queries. Our experimental results suggest that the approach proposed is ecient and scalable.
The document discusses acoustic modeling techniques for underwater sound propagation. It provides an overview of several common modeling approaches, including ray theory models, normal mode models, multipath expansion models, fast field models, and parabolic equation models. It also discusses how these approaches relate to solving the acoustic wave equation and Helmholtz equation. The key steps of ray theory modeling are outlined, including derivation of the eikonal and transport equations from the Helmholtz equation.
Duval l 20140318_s-journee-signal-image_adaptive-multiple-complex-waveletsLaurent Duval
This document discusses using adaptive filtering in continuous wavelet frames to suppress multiple reflections in geophysical signals. It introduces the problem of multiple reflections obscuring deeper geological layers in seismic data. Adaptive filtering with approximate templates is challenging due to variations in primaries and multiples. Continuous, complex wavelet frames can simplify adaptive filtering by spreading noise and highlighting signal features in the time-scale domain. The document explores using wavelet frames to adaptively filter and subtract multiples from seismic data through morphing in the time-scale domain rather than time domain.
This document discusses methods for locating earthquakes based on analyzing arrival times of seismic phases at stations. Accurate event location is important for various applications but also challenging due to uncertainties from measurement errors, velocity model inaccuracies, and the non-linear nature of the problem. The document reviews classical methods like Geiger's linearized inversion and also discusses more advanced non-linear techniques and using multiple events to better constrain locations. It emphasizes picking higher quality phase arrival times and using reference ground truth events to validate new location methods and velocity models.
The document describes methodology for estimating the channel impulse response from acoustic signals transmitted during the SAVEX15 experiment. Stationary source experiments involved transmitting chirp and m-sequence signals from a fixed source location and receiving the signals on a vertical receiver array up to 5 km away. Matched filtering of the received signals with the transmitted source signals was used to estimate the time-varying channel impulse response, which characterizes how the underwater acoustic channel responds to any input signal.
Large strain solid dynamics in OpenFOAMJibran Haider
The document describes a numerical methodology for simulating large strain solid dynamics using OpenFOAM. It proposes using a total Lagrangian formulation and first-order conservation laws similar to computational fluid dynamics to model solid mechanics problems involving large deformations. A cell-centered finite volume method is used for spatial discretization along with Riemann solvers and linear reconstruction to capture fluxes. A two-stage Runge-Kutta scheme is employed for time integration. Results are presented demonstrating the method's ability to handle problems involving mesh convergence, enhanced reconstruction, highly nonlinear behavior, plasticity, contact, unstructured meshes, and complex geometries.
This document summarizes a large eddy simulation of flow around a sharp-edged surface-mounted cube. The simulation was performed using the Petsc-Fem code developed at CIMEC. The flow conditions matched published benchmarks, with a Reynolds number of 40,000. An upstream channel flow was first simulated to provide turbulent inflow conditions. The simulation results are analyzed to validate the LES implementation and identify areas for improving turbulence modeling.
This document presents Specformer, a novel Transformer-based spectral graph neural network. Specformer uses a Transformer to encode eigenvalues of the graph Laplacian into representations that capture magnitude and relative differences. It then applies self-attention to learn relationships between eigenvalues. Specformer decodes the eigenvalue representations using learnable bases to perform graph convolutions. Experiments show Specformer outperforms other GNNs on node and graph classification tasks and learns meaningful patterns in the graph spectrum.
Sparsity based Joint Direction-of-Arrival and Offset Frequency EstimatorJason Fernandes
- The document proposes a method to jointly estimate direction-of-arrival (DoA) and offset frequency of signals impinging on an antenna array using sparse representation.
- It builds on previous work by extending the estimation to include both spatial (DoA) and temporal (offset frequency) dimensions. This is done by constructing a joint dictionary as the Kronecker product of discrete spatial and temporal steering vector grids.
- Sparse recovery algorithms can then be applied to estimate the sparse coefficients and jointly infer the DoAs and offset frequencies of impinging signals from compressed measurements of the antenna array output over multiple time snapshots.
Development, Optimization, and Analysis of Cellular Automaton Algorithms to S...IRJET Journal
This document summarizes research on using cellular automaton algorithms to solve stochastic partial differential equations (SPDEs). It proposes a finite-difference method to approximate an SPDE modeling a random walk with angular diffusion. A Monte Carlo algorithm is also developed for comparison. Analysis finds a moderate correlation between the two methods, suggesting the finite-difference approach is reasonably accurate. It also identifies an inverse-square relationship between variables, linking to a foundational stochastic analysis concept. The research concludes the finite-difference method shows promise for approximating SPDEs while considering boundary conditions.
A FINITE ELEMENT PREDICTION MODEL WITH VARIABLE ELEMENT SIZES - KELLEYRichard. Kelley
This document describes a finite element prediction model that uses variable element sizes. The model uses the shallow water equations on a periodic channel with a constant Coriolis parameter. Initial tests were run using a uniform element size as well as abruptly and smoothly varying element sizes. Uniform elements showed good wave propagation but some noise, while varying elements generated more noise. The goal was to develop a model that allows high resolution where needed without discontinuities at element size changes.
History and Applications of Finite Element Analysis
Theory of Elasticity
Finite Element Equation of Bar element
Finite Element Equation of Truss element
Finite Element Equation of Beam element
Tutorial related to
Bar element
Beam element
Finite element simulation using ANSYS 15.0
Bar element
Truss element
Beam element
High-dimensional polytopes defined by oracles: algorithms, computations and a...Vissarion Fisikopoulos
This document summarizes a PhD thesis defense about algorithms and computations involving high-dimensional polytopes defined by oracles. It introduces polytope representations, oracle definitions, and discusses resultant polytopes arising in algebraic geometry. It outlines an output-sensitive algorithm for computing projections of resultant polytopes using mixed subdivisions. It also describes work on edge-skeleton computations, a volume algorithm, 4D resultant polytope combinatorics, and high-dimensional predicate software.
Adaptive ultrasonic imaging with the total focusing methodDanny Silva vasquez
This document describes an adaptive ultrasonic imaging technique using the Total Focusing Method (TFM) to image complex components immersed in water. The technique involves two key steps: 1) Using an optimized TFM algorithm to measure the surface geometry and reduce computation time, and 2) Calculating ultrasonic propagation paths through the reconstructed surface using Fermat's principle to generate an image below the surface. Experimental results on components with different geometries demonstrate the method's ability to image features below irregular, convex, and concave surfaces.
The document discusses the principles of chromatography. It describes how chromatography separates components in a mixture based on differences in their interactions with mobile and stationary phases. It discusses how Michael Tswett first demonstrated chromatography in 1903 and the key aspects of how it works. These include how retention time, partition coefficients, selectivity factors and efficiency parameters like plate number and height equivalent to a theoretical plate are used to characterize chromatographic separations.
This document provides an overview of high performance liquid chromatography (HPLC) fundamentals and theory. It contains slides created by Agilent Technologies for teaching purposes only regarding HPLC instrumentation, parameters that influence separations such as efficiency, selectivity, retention, and the Van Deemter equation. The document explains key HPLC concepts and how changing variables like stationary phase, mobile phase, temperature and column parameters can optimize separations.
Infinite series are useful in mathematics and fields like physics, chemistry, biology, and engineering. They allow complicated functions to be expressed as the sum of infinitely many terms, which can then be directly solved. Fourier analysis breaks functions into infinite trigonometric series, allowing the study of wave phenomena. The area inside the Koch snowflake, a fractal shape generated by infinite recursion, can be found by summing an infinite geometric series. However, its perimeter is infinite because the length grows without bound at each step of recursion. Infinite series commonly arise in solving differential equations and representing functions and are applied in fields such as image compression, sound analysis, and electrical engineering.
This document discusses discrete-time signal processing and audio signal processing. It covers topics like discrete-time signals, the z-transform, discrete Fourier transform (DFT) and fast Fourier transform (FFT). The key points are:
- Audio signals are typically sampled at 44.1 kHz and quantized to 16 bits per sample.
- The z-transform and discrete Fourier transform (DTFT) are used to analyze discrete-time signals in the transform domain, similar to the Laplace transform and continuous-time Fourier transform for analog signals.
- The discrete Fourier transform (DFT) provides a computational tool to calculate Fourier transforms by sampling the frequency domain at discrete points, resulting in periodicity in the time and
हिंदी वर्णमाला पीपीटी, hindi alphabet PPT presentation, hindi varnamala PPT, Hindi Varnamala pdf, हिंदी स्वर, हिंदी व्यंजन, sikhiye hindi varnmala, dr. mulla adam ali, hindi language and literature, hindi alphabet with drawing, hindi alphabet pdf, hindi varnamala for childrens, hindi language, hindi varnamala practice for kids, https://www.drmullaadamali.com
Main Java[All of the Base Concepts}.docxadhitya5119
This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.
How to Build a Module in Odoo 17 Using the Scaffold MethodCeline George
Odoo provides an option for creating a module by using a single line command. By using this command the user can make a whole structure of a module. It is very easy for a beginner to make a module. There is no need to make each file manually. This slide will show how to create a module using the scaffold method.
This presentation includes basic of PCOS their pathology and treatment and also Ayurveda correlation of PCOS and Ayurvedic line of treatment mentioned in classics.
This presentation was provided by Steph Pollock of The American Psychological Association’s Journals Program, and Damita Snow, of The American Society of Civil Engineers (ASCE), for the initial session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session One: 'Setting Expectations: a DEIA Primer,' was held June 6, 2024.
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
How to Fix the Import Error in the Odoo 17Celine George
An import error occurs when a program fails to import a module or library, disrupting its execution. In languages like Python, this issue arises when the specified module cannot be found or accessed, hindering the program's functionality. Resolving import errors is crucial for maintaining smooth software operation and uninterrupted development processes.
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...PECB
Denis is a dynamic and results-driven Chief Information Officer (CIO) with a distinguished career spanning information systems analysis and technical project management. With a proven track record of spearheading the design and delivery of cutting-edge Information Management solutions, he has consistently elevated business operations, streamlined reporting functions, and maximized process efficiency.
Certified as an ISO/IEC 27001: Information Security Management Systems (ISMS) Lead Implementer, Data Protection Officer, and Cyber Risks Analyst, Denis brings a heightened focus on data security, privacy, and cyber resilience to every endeavor.
His expertise extends across a diverse spectrum of reporting, database, and web development applications, underpinned by an exceptional grasp of data storage and virtualization technologies. His proficiency in application testing, database administration, and data cleansing ensures seamless execution of complex projects.
What sets Denis apart is his comprehensive understanding of Business and Systems Analysis technologies, honed through involvement in all phases of the Software Development Lifecycle (SDLC). From meticulous requirements gathering to precise analysis, innovative design, rigorous development, thorough testing, and successful implementation, he has consistently delivered exceptional results.
Throughout his career, he has taken on multifaceted roles, from leading technical project management teams to owning solutions that drive operational excellence. His conscientious and proactive approach is unwavering, whether he is working independently or collaboratively within a team. His ability to connect with colleagues on a personal level underscores his commitment to fostering a harmonious and productive workplace environment.
Date: May 29, 2024
Tags: Information Security, ISO/IEC 27001, ISO/IEC 42001, Artificial Intelligence, GDPR
-------------------------------------------------------------------------------
Find out more about ISO training and certification services
Training: ISO/IEC 27001 Information Security Management System - EN | PECB
ISO/IEC 42001 Artificial Intelligence Management System - EN | PECB
General Data Protection Regulation (GDPR) - Training Courses - EN | PECB
Webinars: https://pecb.com/webinars
Article: https://pecb.com/article
-------------------------------------------------------------------------------
For more information about PECB:
Website: https://pecb.com/
LinkedIn: https://www.linkedin.com/company/pecb/
Facebook: https://www.facebook.com/PECBInternational/
Slideshare: http://www.slideshare.net/PECBCERTIFICATION
How to Manage Your Lost Opportunities in Odoo 17 CRMCeline George
Odoo 17 CRM allows us to track why we lose sales opportunities with "Lost Reasons." This helps analyze our sales process and identify areas for improvement. Here's how to configure lost reasons in Odoo 17 CRM
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
12. Frequency vs Ome domain (1)
Normally signals appear in the time domain:
v(t) with t ∈ [0,T]
where T is the length of a record. If we assume that:
v(t +T) = v(t)
then the function is said to be periodic. Furthermore
if v(t) has a finite number of oscillations in [0,T] then
we can develop v(t) in a series:
v(t) = Ai
i=0
N/2
∑ cos(ωit)+ Bi sin(ωit)
which is known as a Fourier series and where Ai and Bi
denote the Euler coefficients.
21/03/18 12
17. Frequency versus Omeseries (5)
• EssenOally y=FFT(x) carries out a Fourier transform
• FFT algorithm input
– Real vector x(0..N-1) with N datasamples
– The record starts at 0 and is filled to N-1
• FFT algorithm output
– Euler coefficients are stored in the form of complex numbers
– Stored in y(i) are:
y(0) = A0 + I.B0 , y(1) = A1+ I.B1 , …, y(N/2) = AN/2 + I.BN/2
– I is a complex number:
– Be careful with scaling factors, check this always with a test funcOon of
which you now the Euler coefficients in advance
– Suitable test funcOons are for instance linear sin and cos expressions
• FFT algorithms exploit symmetries of sin and cos funcOons, please
use MATLAB because it is thoroughly debugged.
• Be aware that indices in MATLAB vectors start at 1 (and not 0)
I = −1
21/03/18 17
25. Aliasing = Folding
frequency
power
Watch how a part of the spectrum above the Nyquist frequency folds back
onto the lower part of the spectrum, this is what we call aliasing
Nyquist
frequency
34. Ocean tides (chapter 16)
• Purpose of this part is to describe motions of fluids
with a system of differential equations.
• We are only interested in representing currents and
water levels at time and space scales appropriate to
ocean tides. (several km to global, hours to days)
• Where is the input, what is the response, is it linear?
40. ConOnuity equaOon (5)
If we allow variations along x the u component
becomes:
dydzdx
x
u
udx
x
))((
∂
∂
+
∂
∂
+
ρ
ρ
When this is allowed for all components we get:
0
1
=⎥
⎦
⎤
⎢
⎣
⎡
∂
∂
+
∂
∂
+
∂
∂
+
z
w
y
v
x
u
dt
dρ
ρ
For non-compressible fluids the first term will vanish
42. Momentum equaOon (2)
Why is the pressure gradient like shown? (Pressure = force / area,
Force = pressure times area)
dx
dy
dz
P P+dP
Force effect x direction: zyx
x
P
zydPzydPPzyP δδδδδδδδδ .....).(..
∂
∂
−=−=+−
44. Momentum equaOon (4)
How to get the Coriolis term? Answer: consider an inertial
(i) and a rotating coordinate system (a).
a
a
a
a
a
a
i
i
a
a
a
a
i
i
a
a
i
i
xxxx
xxx
xx
eeeex
eeex
eex
!!!!!!!!!!
!!!!
++==
+==
==
2
Unit vectors coordinate basis: e
Point ordinates on a chosen basis: x
45. Momentum equaOon (6)
For a rotating basis we have:
aaa
aa
eωωeωe
eωe
××+×=
×=
!!!
!
And the consequence is:
aaaaI xωxωωxωxx ×+××+×+= !!!!!! 2
“frame”“centrifugal”
46. Momentum equaOon (7)
Du
Dt
=
−1
ρ
∇P − 2ω × u + g + F
The final result is:
Note:
• pressure and density symbols (watch the symbols)
• g does contain a centrifugal term!
• rotation is considered constant
• this equation holds in an Earth fixed frame
• contains Friction and ForcingF
47. Navier Stokes equaOons
€
Du
Dt
=
−1
ρ
∂p
∂x
+ 2Ωsinφv − 2Ωcosφ w + Fx
Dv
Dt
=
−1
ρ
∂p
∂y
− 2Ωsinφ u + Fy
Dw
Dt
=
−1
ρ
∂p
∂z
+ 2Ωcosφ u − g + Fz
Notes:
- w equation: largest terms result in hydrostatic equation
- D./Dt includes local derivative and advection (later)
For a suitable local coordinate frame we find:
48. HydrostaOc equaOon
For the w-equation we get:
€
∂p
∂z
= −gρ
p(z) = − gρdzH
−η
∫ = gρ(H +η)
Example:
• At 1000 m the pressure is approximately 100 bar
• Density changes in the oceans are relatively small (3%)
49. Velocity depth averaged equaOon
f = 2Ωsinϕ
€
Du
Dt
= −g
∂η
∂x
+ fv + Fx
Dv
Dt
= −g
∂η
∂y
− fu + Fy
Dη
Dt
= −(H +η)
∂u
∂x
+
∂v
∂y
%
&
'
(
)
*
In these equations u and v are averaged over the entire water
column. The Coriolis term
50. Laplace Odal equaOons
€
Du
Dt
= −g
∂η
∂x
+ fv + Fx
Dv
Dt
= −g
∂η
∂y
− fu + Fy
Dη
Dt
= −(H +η)
∂u
∂x
+
∂v
∂y
%
&
'
(
)
*
€
Fx
Fy
"
#
$
%
&
' =
∂Γ ∂x
∂Γ ∂y
"
#
$
%
&
' +
rx
ry
"
#
$
%
&
'
Γ = Hω
ω
∑ cos(χω (t) − Gω )
The terms u,v and η represent velocity and water level, f is a
Coriolis term, H is the depth of the ocean, Γ is a forcing
function, r represents dissipative forcing. (Chapter 16)
55. Helmholtz equaOon (4)
If you substitute the characteristic solutions for all dependent
variables in the shallow water equations:
(ω2
− f 2
) ˆη + c2 ∂2
ˆη
∂x2
+
∂2
ˆη
∂y2
⎛
⎝⎜
⎞
⎠⎟ ≈ 0
c = gH
In this relation c is the surface speed of the tide. You can
obtain it by substitution of the test function in the Laplace
tidal equations.
59. Forcing
• Question: what are Fx and Fy in the momentum equation?
• Answer: this depends on the type of problem
• Some examples are:
• Gradients tide generating potential
• Friction
• (Advection is not a forcing term)
60. Linearity
Ocean tides show a linear behavior when sea bottom friction
is linear and when advection is ignored:
rx =
Cu
H
and ry =
Cv
H
€
Γ(t) = ˆΓexp( jωt)
In reality sea bottom friction is quadratic:
r = Cu u
64. FricOon
• This is described by
• Fx acts on a molecular level.
• The term ν describes kinemaOc molecular viscosity, ν is
about 10-6 m2/s
• FricOon always introduces dissipaOon
• To apply fricOon in Ode models you have to re-scale fricOon
by means of horizontal and verOcal eddy viscosity terms
• Scale factor depends on numerical consideraOons
Fx =ν
∂2
u
∂x2
+
∂2
u
∂y2
+
∂2
u
∂z2
"
#
$
%
&
'
68. Dispersion relaOon
u(t) = ˆuexp( j(ωt − kx − ly))
v(t) = ˆvexp( j(ωt − kx − ly))
η(t) = ˆηexp( j(ωt − kx − ly))
∇F = 0
Unforced or free waves fulfill the following relation:
Show that this results in the following dispersion relation
)()( 2222
lkgHf +=−ω
Do free waves exist for all frequencies at all latitudes?
69. Simple Ode model
€
h(φ,λ,t) = Hi φ,λ( )
i
∑ cos wi t − t0( )− Gi φ,λ( )( )
Hi φ,λ( ): tidal amplitude
Gi φ,λ( ): Greenwich phase
Deep ocean tides can be predicted by the model:
The tidal frequency is astronomically determined, for a
location at which the tides are predicted it is sufficient to
have a series of H and G values available, t0 is a reference
time, t is the time of observation.
70. M2 tide with phase lines in hours.
North Sea Tides
90. Local DissipaOon (1)
∂u
∂t
+ f ×u = −g∇ζ + ∇Γ − F
∂ζ
∂t
= −∇.(uH )
W − P = D
W = ρH < u.∇Γ >
P = gρH∇.< uζ >
D = ρH < u.F >
W: Work
P: Divergence Energy Flux
D: Dissipation
∫
+=
=
=
Ttt
tt
dtFu
T
D
0
0
).(
1
100. Conclusions (1)
• Global dissipaOon:
– There are consistent values for most models,
• The M2 dissipaOon converges at 2.42 TW to within 2%
– Independent methods to determine the rate of energy
dissipaOon (LLR, satellite geodesy). LLR arrives at 2.5 TW
for M2
– Comparison to astronomic/geodeOc values:
• 0.2 TW at S2 for dissipaOon in the atmosphere
• 0.1 TW at M2 for dissipaOon in the solid earth
• gravimetric confirmaOon of the 0.1 TW is very challenging
– History of Earth rotaOon relies of dissipaOon esOmates from paleo-
oceanographic ocean Ode models.